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Abstract Climate change is altering the thermal habitats of freshwater fish species. We analyze modeled daily temperature profiles from 12,688 lakes in the US to track changes in thermal habitat of 60 lake fish species from different thermal guilds during 1980-2021. We quantify changes in each species’ preferred days, defined as the number of days per year when a lake contains the species’ preferred temperature. We find that cooler-water species are losing preferred days more rapidly than warmer-water species are gaining them. This asymmetric impact cannot be attributed to differences in geographic distribution among species; instead, it is linked to the seasonal dynamics of lake temperatures and increased thermal homogenization of the water column. The potential advantages of an increase in warmer-water species may not fully compensate for the losses in cooler-water species as warming continues, emphasizing the importance of mitigating climate change to support effective freshwater fisheries management.

Free use and redistribution of data (i.e., Open Data) increases the reproducibility, transparency, and pace of aquatic sciences research. However, barriers to both data users and data providers may limit the adoption of Open Data practices. Here, we describe common Open Data challenges faced by data users and data providers within the aquatic sciences community (i.e., oceanography, limnology, hydrology, and others). These challenges were synthesized from literature, authors’ experiences, and a broad survey of 174 data users and data providers across academia, government agencies, industry, and other sectors. Through this work, we identified seven main challenges: 1) metadata shortcomings, 2) variable data quality and reusability, 3) open data inaccessibility, 4) lack of standardization, 5) authorship and acknowledgement issues 6) lack of funding, and 7) unequal barriers around the globe. Our key recommendation is to improve resources to advance Open Data practices. This includes dedicated funds for capacity building, hiring and maintaining of skilled personnel, and robust digital infrastructures for preparation, storage, and long-term maintenance of Open Data. Further, to incentivize data sharing we reinforce the need for standardized best practices to handle data acknowledgement and citations for both data users and data providers. We also highlight and discuss regional disparities in resources and research practices within a global perspective.

Abstract As a key water quality parameter, dissolved oxygen (DO) concentration, and particularly changes in bottom water DO is fundamental for understanding the biogeochemical processes in lake ecosystems. Based on two machine learning (ML) models, Gradient Boost Regressor (GBR) and long‐short‐term‐memory (LSTM) network, this study developed three ML model approaches: direct GBR; direct LSTM; and a 2‐step mixed ML model workflow combining both GBR and LSTM. They were used to simulate multi‐year surface and bottom DO concentrations in five lakes. All approaches were trained with readily available environmental data as predictors. Indices of lake thermal structure and mixing provided by a one‐dimensional (1‐D) hydrodynamic model were also included as predictors in the ML models. The advantages of each ML approach were not consistent for all the tested lakes, but the best one of them was defined that can estimate DO concentration with coefficient of determination (R2) up to 0.6–0.7 in each lake. All three approaches have normalized mean absolute error (NMAE) under 0.15. In a polymictic lake, the 2‐step mixed model workflow showed better representation of bottom DO concentrations, with a highest true positive rate (TPR) of hypolimnetic hypoxia detection of over 90%, while the other workflows resulted in, TPRs are around 50%. In most of the tested lakes, the predicted surface DO concentrations and variables indicating stratified conditions (i.e., Wedderburn number and the temperature difference between surface and bottom water) are essential for simulating bottom DO. The ML approaches showed promising results and could be used to support short‐ and long‐term water management plans.

Abstract Background Respect is essential to providing high quality healthcare, particularly for groups that are historically marginalized and stigmatized. While ethical principles taught to health professionals focus on patient autonomy as the object of respect for persons, limited studies explore patients’ views of respect. The purpose of this study was to explore the perspectives of a multiculturally diverse group of low-income women living with HIV (WLH) regarding their experience of respect from their medical physicians. Methods We analyzed 57 semi-structured interviews conducted at HIV case management sites in South Florida as part of a larger qualitative study that explored practices facilitating retention and adherence in care. Women were eligible to participate if they identified as African American (n = 28), Hispanic/Latina (n = 22), or Haitian (n = 7). They were asked to describe instances when they were treated with respect by their medical physicians. Interviews were conducted by a fluent research interviewer in either English, Spanish, or Haitian Creole, depending on participant’s language preference. Transcripts were translated, back-translated and reviewed in entirety for any statements or comments about “respect.” After independent coding by 3 investigators, we used a consensual thematic analysis approach to determine themes. Results Results from this study grouped into two overarching classifications: respect manifested in physicians’ orientation towards the patient (i.e., interpersonal behaviors in interactions) and respect in medical professionalism (i.e., clinic procedures and practices). Four main themes emerged regarding respect in provider’s orientation towards the patient: being treated as a person, treated as an equal, treated without blame or prejudice, and treated with concern/emotional support. Two main themes emerged regarding respect as evidenced in medical professionalism: physician availability and considerations of privacy. Conclusions Findings suggest a more robust conception of what ‘respect for persons’ entails in medical ethics for a diverse group of low-income women living with HIV. Findings have implications for broadening areas of focus of future bioethics education, training, and research to include components of interpersonal relationship development, communication, and clinic procedures. We suggest these areas of training may increase respectful medical care experiences and potentially serve to influence persistent and known social and structural determinants of health through provider interactions and health care delivery.

Abstract Species invasions can disrupt aquatic ecosystems by re‐wiring food webs. A trophic cascade triggered by the invasion of the predatory zooplankter spiny water flea (Bythotrephes cederströmii) resulted in increased phytoplankton due to decreased zooplankton grazing. Here, we show that increased phytoplankton biomass led to an increase in lake anoxia. The temporal and spatial extent of anoxia experienced a step change increase coincident with the invasion, and anoxic factor increased by 11 d. Post‐invasion, anoxia established more quickly following spring stratification, driven by an increase in phytoplankton biomass. A shift in spring phytoplankton phenology encompassed both abundance and community composition. Diatoms (Bacillaryophyta) drove the increase in spring phytoplankton biomass, but not all phytoplankton community members increased, shifting the community composition. We infer that increased phytoplankton biomass increased labile organic matter and drove hypolimnetic oxygen consumption. These results demonstrate how a species invasion can shift lake phenology and biogeochemistry.

Abstract Lake trophic state is a key ecosystem property that integrates a lake’s physical, chemical, and biological processes. Despite the importance of trophic state as a gauge of lake water quality, standardized and machine-readable observations are uncommon. Remote sensing presents an opportunity to detect and analyze lake trophic state with reproducible, robust methods across time and space. We used Landsat surface reflectance data to create the first compendium of annual lake trophic state for 55,662 lakes of at least 10 ha in area throughout the contiguous United States from 1984 through 2020. The dataset was constructed with FAIR data principles (Findable, Accessible, Interoperable, and Reproducible) in mind, where data are publicly available, relational keys from parent datasets are retained, and all data wrangling and modeling routines are scripted for future reuse. Together, this resource offers critical data to address basic and applied research questions about lake water quality at a suite of spatial and temporal scales.

Abstract Anthropogenic freshwater salinization affects thousands of lakes worldwide, and yet little is known about how salt loading may shift timing of lake stratification and spring mixing in dimictic lakes. Here, we investigate the impact of salinization on mixing in Lakes Mendota and Monona, Wisconsin, by deploying under‐ice buoys to record salinity gradients, using an analytical approach to quantify salinity thresholds that prevent spring mixing, and running an ensemble of vertical one‐dimensional hydrodynamic lake models (GLM, GOTM, and Simstrat) to investigate the long‐term impact of winter salt loading on mixing and stratification. We found that spring salinity gradients between surface and bottom waters persist up to a month after ice‐off, and that theory predicts a salinity gradient of 1.3–1.4 g kg−1 would prevent spring mixing. Numerical models project that salt loading delays spring mixing and increases water column stability, with ramifications for oxygenation of bottom waters, biogeochemistry, and lake habitability.

Alors qu’une pandémie dévastatrice affecte le monde entier, il est essentiel que les décideurs tiennent compte des problèmes de méthodologie et de mesure qui pourraient être associés aux indicateurs de santé publique de la maladie à coronavirus 2019 (COVID-19). Ce commentaire comprend quatre variables principales pour illustrer les questions de mesure et de méthodologie qui peuvent compliquer les comparaisons entre les administrations. L’administration désigne une variété de régions géographiques, comme un pays, un État, une province ou un territoire. Ces variables jouent un rôle essentiel dans la façon dont nous comprenons la trajectoire de la propagation de la maladie. Ces variables contribuent également à notre compréhension des stratégies de prévention et de leur efficacité connexe, reflétant l’impact de la COVID-19 sur les hôpitaux. Il est essentiel que les intervenants en santé publique et le public reconnaissent que ces quatre simples variables peuvent varier considérablement d’une administration à l’autre.

Stratification has a considerable influence on lake ecology, but there is little understanding of past or future changes in its seasonality. Here, the authors use modelling and empirical data to determine that between 1901–2099, climate change causes stratification to start earlier and end later.

As people around the world experience a devastating pandemic, it is critical that policy-makers consider the methodological and measurement issues that might be associated with coronavirus disease 2019 (COVID-19) public health indicators. This commentary uses four primary variables to illustrate measurement and methodological issues that can complicate comparisons between jurisdictions. Jurisdiction refers to a variety of geographic areas, such as a country, a state, or a province/territory. These variables play a critical role in determining how we understand the trajectory of disease spread. These variables also contribute to our understanding of prevention strategies and their associated efficacy, reflecting the impact of COVID-19 on hospitals. It is critical for public health stakeholders and the public to recognize that these four simple variables can vary substantially across jurisdictions.

In this work, a new method for aerial robot remote sensing using stereo vision is proposed. A variable baseline and flexible configuration stereo setup is achieved by separating the left camera and right camera on two separate quadrotor aerial robots. Monocular cameras, one on each aerial robot, are used as a stereo pair, allowing independent adjustment of the pose of the stereo pair. In contrast to conventional stereo vision where two cameras are fixed, having a flexible configuration system allows a large degree of independence in changing the configuration in accordance with various kinds of applications. Larger baselines can be used for stereo vision of farther away targets while using a vertical stereo configuration in tasks where there would be a loss of horizontal overlap caused by a lack of suitable horizontal configuration. Additionally, a method for the practical use of variable baseline stereo vision is introduced, combining multiple point clouds from multiple stereo baselines. Issues from using an inappropriate baseline, such as estimation error induced by insufficient baseline, and occlusions from using too large a baseline can be avoided with this solution.

In Miami-Dade County, women with HIV (WWH) enrolled in Ryan White Program (RWP) services belong to groups that have historically faced structural barriers to care. To examine provider perceptions of WWH's barriers to care and elicit possible solutions, we conducted semi-structured interviews (n = 20) with medical case managers and human immunodeficiency virus (HIV) healthcare providers from medical case management sites serving WWH enrolled in the Miami-Dade RWP. Verbatim transcripts were analyzed thematically by two coders through an iterative process; disagreements were resolved through consensus. Barriers included lack of disclosure and stigma, additional psychosocial barriers to care, structural and logistical barriers, and negative interactions with health care providers. Participant suggestions to address these barriers included strategies that support women and foster individualized services that are responsive to their lived experiences and needs. Other solutions, such as those related to transportation, housing, and general funding for the RWP, will require advocacy and policy change.

In aerial manipulation, the position and size of a manipulator attached to an aerial robot defines its workspace relative to the robot. However, the working region of a multipurpose robot is determined by its task and is not always predictable prior to deployment. In this paper, the development of a multipurpose manipulator design for a three-armed UAV with a large workspace around its airframe is proposed. The manipulator is designed to be lightweight and slim in order to not disrupt the UAV during in-flight manipulator movements. In the experiments, we demonstrate various advanced and critical tasks required of an aerial robot when deployed in a remote environment, focusing on the landing and docking tasks, which is accomplished using a single manipulator system.

UAVs are one of the fastest types of robots that can be deployed in a remote environment. Unfortunately, they have a limited flight time and therefore may need to stop occasionally in an unknown, uncontrolled area. However, conventional UAVs require flat and stationary surfaces for a safe landing and take-off. Some studies on adaptive landing approach for UAVs can be found in the past, but adaptive take-off from non-flat surfaces has not been discussed for the most part, yet. In this work, we discuss the problems associated with a conventional UAV take-off from non-flat surfaces and provide a novel approach for UAV take-off from a sloped or rocking surface. We also discuss the design of a novel multitasking three-arm aerial manipulator system with parallel link mechanism and achieve the above-mentioned task. With experiments, we show that the system can provide stability for a UAV landing on a rocking surface that allows for a safe take-off.