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Invasive species threaten biodiversity globally. Amphibians are one of the most threatened vertebrate taxa and are particularly sensitive to invasive species, including other amphibians. African clawed frogs ( Xenopus laevis ) are native to Southern Africa but have subsequently become invasive on multiple continents-including multiple parts of North America-due to releases from the pet and biomedical trades. Despite their prevalence as a global invader, the impact of X. laevis remains understudied. This includes the Pacific Northwest of the USA, which now hosts multiple expanding X. laevis populations. For many amphibians, chemical cues communicate important information, including the presence of predators. Here, we tested the role chemical cues may play in mediating interactions between feral X. laevis and native amphibians in the Pacific Northwest. We tested whether native red-legged frog ( Rana aurora ) tadpoles display an antipredator response to non-native frog ( X. laevis ) or native newt (rough-skinned newts, Taricha granulosa ) predator chemical stimuli. We found that R. aurora tadpoles exhibited pronounced anti-predator responses when exposed to chemical cues from T. granulosa but did not display anti-predator response to invasive X. laevis chemical cues. We also began experimentally testing whether T. granulosa -which produce a powerful neurotoxin tetrodotoxin (TTX)-may elicit an anti-predator response in X. laevis , that could serve to deter co-occupation. However, our short-duration experiments found that X. laevis were attracted to newt chemical stimuli rather than deterred. Our findings show that X. laevis likely poses a threat to native amphibians, and that these native species may also be particularly vulnerable to this invasive predator, compared to native predators, because toxic native newts may not limit X. laevis invasions. Our research provides some of the first indications that native Pacific Northwest species may be threatened by feral X. laevis and provides a foundation for future experiments testing potential management techniques for X. laevis ., Competing Interests: Max Lambert is an Academic Editor for PeerJ., (©2024 Anderson et al.)

Artificial light at night (ALAN) is a growing conservation concern for seabirds, which can become disoriented and grounded by lights from buildings, bridges and boats. Many fledgling seabirds, especially Procellariiformes such as petrels and shearwaters, are susceptible to light pollution. The Hauraki Gulf, a seabird hotspot located near Tāmaki Makaurau/Auckland, Aotearoa-New Zealand's largest urban city, with a considerable amount of light pollution and regularly documented events of seabird groundings. We aim to identify the characteristics of locations especially prone to seabird groundings. We used an online database of seabirds taken to a wildlife rescue facility by the public to map 3 years of seabird groundings and test for correlations between seabird groundings and the natural night sky brightness. We found that areas with lower amounts of natural night sky brightness and greater light pollution often had a higher number of seabirds grounded. Further, we identified important seasonal patterns and species differences in groundings. Such differences may be a by-product of species ecology, visual ecology and breeding locations, all of which may influence attraction to lights. In general, seabird groundings correlate with the brightness of the area and are species-specific. Groundings may not be indicative of human or seabird population abundance considering some areas have a lower human population with high light levels and had high amounts of seabird groundings. These findings can be applied worldwide to mitigate groundings by searching and targeting specific brightly lit anthropogenic structures. Those targeted structures and areas can then be the focus of light mitigation efforts to reduce seabird groundings. Finally, this study illustrates how a combination of community science, and a concern for seabirds grounded from light attraction, in addition to detailed animal welfare data and natural night sky brightness data can be a powerful, collaborative tool to aid global conservation efforts for highly-at-risk animals such as seabirds., Competing Interests: The authors declare that they have no competing interests., (© 2022 Heswall et al.)

Passive acoustic monitoring (PAM) coupled with automated species identification is a promising tool for species monitoring and conservation worldwide. However, high false indications of presence are still an important limitation and a crucial factor for acceptance of these techniques in wildlife surveys. Here we present the Assemblage of Focal Species Recognizers-AFSR, a novel approach for decreasing false positives and increasing models' precision in multispecies contexts. AFSR focusses on decreasing false positives by excluding unreliable sound file segments that are prone to misidentification. We used MatlabHTK, a hidden Markov models interface for bioacoustics analyses, for illustrating AFSR technique by comparing two approaches, 1) a multispecies recognizer where all species are identified simultaneously, and 2) an assemblage of focal species recognizers (AFSR), where several recognizers that each prioritise a single focal species are then summarised into a single output, according to a set of rules designed to exclude unreliable segments. Both approaches (the multispecies recognizer and AFSR) used the same sound files training dataset, but different processing workflow. We applied these recognisers to PAM recordings from a remote island colony with five seabird species and compared their outputs with manual species identifications. False positives and precision improved for all the five species when using AFSR, achieving remarkable 0% false positives and 100% precision for three of five seabird species, and < 6% false positives, and >90% precision for the other two species. AFSR' output was also used to generate daily calling activity patterns for each species. Instead of attempting to withdraw useful information from every fragment in a sound recording, AFSR prioritises more trustworthy information from sections with better quality data. AFSR can be applied to automated species identification from multispecies PAM recordings worldwide., Competing Interests: The authors have declared that no competing interests exist.

Sensory-based conservation harnesses species' natural communication and signalling behaviours to mitigate threats to wild populations. To evaluate this emerging field, we assess how sensory-based manipulations, sensory mode, and target taxa affect success. To facilitate broader, cross-species application of successful techniques, we test which behavioural and life-history traits correlate with positive conservation outcomes. We focus on seabirds, one of the world's most rapidly declining groups, whose philopatry, activity patterns, foraging, mate choice, and parental care behaviours all involve reliance on, and therefore strong selection for, sophisticated sensory physiology and accurate assessment of intra- and inter-species signals and cues in several sensory modes. We review the use of auditory, olfactory, and visual methods, especially for attracting seabirds to newly restored habitat or deterring birds from fishing boats and equipment. We found that more sensory-based conservation has been attempted with Procellariiformes (tube-nosed seabirds) and Charadriiformes (e.g. terns and gulls) than other orders, and that successful outcomes are more likely for Procellariiformes. Evolutionary and behavioural traits are likely to facilitate sensory-based techniques, such as social attraction to suitable habitat, across seabird species. More broadly, successful application of sensory-based conservation to other at-risk animal groups is likely to be associated with these behavioural and life-history traits: coloniality, philopatry, nocturnal, migratory, long-distance foraging, parental care, and pair bonds/monogamy., (© 2016 Cambridge Philosophical Society.)

Background: West Nile Virus (WNV) was first isolated in 1937. Since the 1950s, many outbreaks have occurred in various countries. The first appearance of infected birds in Manitoba, Canada was in 2002., Objective: This paper describes the data preparation phase of setting up a geographic information system (GIS) simulation environment for WNV Agent-Based Modelling in Manitoba., Methods: The main technology used in this protocol is based on AnyLogic and ArcGIS software. A diverse variety of topics and techniques regarding the data collection phase are presented, as modelling WNV has many disparate attributes, including landscape and weather impacts on mosquito population dynamics and birds' roosting locations, population count, and movement patterns., Results: Different maps were combined to create a grid land cover map of Manitoba, Canada in a shapefile format compatible with AnyLogic, in order to modulate mosquito parameters. A significant amount of data regarding 152 bird species, along with their population estimates and locations in Manitoba, were gathered and assembled. Municipality shapefile maps were converted to built-in AnyLogic GIS regions for better compatibility with census data and initial placement of human agents. Accessing shapefiles and their databases in AnyLogic are also discussed., Conclusions: AnyLogic simulation software in combination with Esri ArcGIS provides a powerful toolbox for developers and modellers to simulate almost any GIS-based environment or process. This research should be useful to others working on a variety of mosquito-borne diseases (eg, Zika, dengue, and chikungunya) by demonstrating the importance of data relating to Manitoba and/or introducing procedures to compile such data., (©Hamid Reza Nasrinpour, Alexander A Reimer, Marcia R Friesen, Robert D McLeod. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 17.07.2017.)

This paper reports on the findings of a user trial of a mHealth application for pressure ulcer (bedsore) documentation. Pressure ulcers are a leading iatrogenic cause of death in developed countries and significantly impact quality of life for those affected. Pressure ulcers will be an increasing public health concern as the population ages. Electronic information systems are being explored to improve consistency and accuracy of documentation, improve patient and caregiver experience and ultimately improve patient outcomes. A software application was developed for Android Smartphones and tablets and was trialed in a personal care home in Western Canada. The software application provides an electronic medical record for chronic wounds, replacing nurses' paper-based charting and is positioned for integration with facility's larger eHealth framework. The mHealth application offers three intended benefits over paper-based charting of chronic wounds, including: (1) the capacity for remote consultation (telehealth between facilities, practitioners, and/or remote communities), (2) data organization and analysis, including built-in alerts, automatically-generated text-based and graph-based wound histories including wound images, and (3) tutorial support for non-specialized caregivers. The user trial yielded insights regarding the software application's design and functionality in the clinical setting, and highlighted the key role of wound photographs in enhancing patient and caregiver experiences, enhancing communication between multiple healthcare professionals, and leveraging the software's telehealth capacities.

This work uses agent-based modelling (ABM) to simulate sexually transmitted infection (STIs) spread within a population of 1000 agents over a 10-year period, as a preliminary investigation of the suitability of ABM methodology to simulate STI spread. The work contrasts compartmentalized mathematical models that fail to account for individual agents, and ABMs commonly applied to simulate the spread of respiratory infections. The model was developed in C++ using the Boost 1.47.0 libraries for the normal distribution and OpenGL for visualization. Sixteen agent parameters interact individually and in combination to govern agent profiles and behaviours relative to infection probabilities. The simulation results provide qualitative comparisons of STI mitigation strategies, including the impact of condom use, promiscuity, the form of the friend network, and mandatory STI testing. Individual and population-wide impacts were explored, with individual risk being impacted much more dramatically by population-level behaviour changes as compared to individual behaviour changes.

The objective of this paper was to develop an agent-based modeling framework in order to simulate the spread of influenza virus infection on a layout based on a representative hospital emergency department in Winnipeg, Canada. In doing so, the study complements mathematical modeling techniques for disease spread, as well as modeling applications focused on the spread of antibiotic-resistant nosocomial infections in hospitals. Twenty different emergency department scenarios were simulated, with further simulation of four infection control strategies. The agent-based modeling approach represents systems modeling, in which the emergency department was modeled as a collection of agents (patients and healthcare workers) and their individual characteristics, behaviors, and interactions. The framework was coded in C++ using Qt4 libraries running under the Linux operating system. A simple ordinary least squares (OLS) regression was used to analyze the data, in which the percentage of patients that became infected in one day within the simulation was the dependent variable. The results suggest that within the given instance context, patient-oriented infection control policies (alternate treatment streams, masking symptomatic patients) tend to have a larger effect than policies that target healthcare workers. The agent-based modeling framework is a flexible tool that can be made to reflect any given environment; it is also a decision support tool for practitioners and policymakers to assess the relative impact of infection control strategies. The framework illuminates scenarios worthy of further investigation, as well as counterintuitive findings.

This work is contextualized in research in modeling and simulation of infection spread within a community or population, with the objective to provide a public health and policy tool in assessing the dynamics of infection spread and the qualitative impacts of public health interventions. This work uses the integration of real data sources into an Agent Based Model (ABM) to simulate respiratory infection spread within a small municipality. Novelty is derived in that the data sources are not necessarily obvious within ABM infection spread models. The ABM is a spatial-temporal model inclusive of behavioral and interaction patterns between individual agents on a real topography. The agent behaviours (movements and interactions) are fed by census / demographic data, integrated with real data from a telecommunication service provider (cellular records) and person-person contact data obtained via a custom 3G Smartphone application that logs Bluetooth connectivity between devices. Each source provides data of varying type and granularity, thereby enhancing the robustness of the model. The work demonstrates opportunities in data mining and fusion that can be used by policy and decision makers. The data become real-world inputs into individual SIR disease spread models and variants, thereby building credible and non-intrusive models to qualitatively simulate and assess public health interventions at the population level.

Background: Emergency Department (ED) overcrowding is an important healthcare issue facing increasing public and regulatory scrutiny in Canada and around the world. Many approaches to alleviate excessive waiting times and lengths of stay have been studied. In theory, optimal ED patient flow may be assisted via balancing patient loads between EDs (in essence spreading patients more evenly throughout this system). This investigation utilizes simulation to explore "Crowdinforming" as a basis for a process control strategy aimed to balance patient loads between six EDs within a mid-sized Canadian city., Methods: Anonymous patient visit data comprising 120,000 ED patient visits over six months to six ED facilities were obtained from the region's Emergency Department Information System (EDIS) to (1) determine trends in ED visits and interactions between parameters; (2) to develop a process control strategy integrating crowdinforming; and, (3) apply and evaluate the model in a simulated environment to explore the potential impact on patient self-redirection and load balancing between EDs., Results: As in reality, the data available and subsequent model demonstrated that there are many factors that impact ED patient flow. Initial results suggest that for this particular data set used, ED arrival rates were the most useful metric for ED 'busyness' in a process control strategy, and that Emergency Department performance may benefit from load balancing efforts., Conclusions: The simulation supports the use of crowdinforming as a potential tool when used in a process control strategy to balance the patient loads between EDs. The work also revealed that the value of several parameters intuitively expected to be meaningful metrics of ED 'busyness' was not evident, highlighting the importance of finding parameters meaningful within one's particular data set. The information provided in the crowdinforming model is already available in a local context at some ED sites. The extension to a wider dissemination of information via an Internet web service accessible by smart phones is readily achievable and not a technological obstacle. Similarly, the system could be extended to help direct patients by including future estimates or predictions in the crowdinformed data. The contribution of the simulation is to allow for effective policy evaluation to better inform the public of ED 'busyness' as part of their decision making process in attending an emergency department. In effect, this is a means of providing additional decision support insights garnered from a simulation, prior to a real world implementation.

This work extends ongoing development of a framework for modeling the spread of contact-transmission infectious diseases. The framework is built upon Agent Based Modeling (ABM), with emphasis on urban scale modelling integrated with institutional models of hospital emergency departments. The method presented here includes ABM modeling an outbreak of influenza-like illness (ILI) with concomitant surges at hospital emergency departments, and illustrates the preliminary modeling of 'crowdinforming' as an intervention. 'Crowdinforming', a component of 'crowdsourcing', is characterized as the dissemination of collected and processed information back to the 'crowd' via public access. The objective of the simulation is to allow for effective policy evaluation to better inform the public of expected wait times as part of their decision making process in attending an emergency department or clinic. In effect, this is a means of providing additional decision support garnered from a simulation, prior to real world implementation. The conjecture is that more optimal service delivery can be achieved under balanced patient loads, compared to situations where some emergency departments are overextended while others are underutilized. Load balancing optimization is a common notion in many operations, and the simulation illustrates that 'crowdinforming' is a potential tool when used as a process control parameter to balance the load at emergency departments as well as serving as an effective means to direct patients during an ILI outbreak with temporary clinics deployed. The information provided in the 'crowdinforming' model is readily available in a local context, although it requires thoughtful consideration in its interpretation. The extension to a wider dissemination of information via a web service is readily achievable and presents no technical obstacles, although political obstacles may be present. The 'crowdinforming' simulation is not limited to arrivals of patients at emergency departments due to ILI; it applies equally to any scenarios where patients arrive in any arrival pattern that may cause disparity in the waiting times at multiple facilities.

In this paper, we apply both agent-based models and queuing models to investigate patient access and patient flow through emergency departments. The objective of this work is to gain insights into the comparative contributions and limitations of these complementary techniques, in their ability to contribute empirical input into healthcare policy and practice guidelines. The models were developed independently, with a view to compare their suitability to emergency department simulation. The current models implement relatively simple general scenarios, and rely on a combination of simulated and real data to simulate patient flow in a single emergency department or in multiple interacting emergency departments. In addition, several concepts from telecommunications engineering are translated into this modeling context. The framework of multiple-priority queue systems and the genetic programming paradigm of evolutionary machine learning are applied as a means of forecasting patient wait times and as a means of evolving healthcare policy, respectively. The models' utility lies in their ability to provide qualitative insights into the relative sensitivities and impacts of model input parameters, to illuminate scenarios worthy of more complex investigation, and to iteratively validate the models as they continue to be refined and extended. The paper discusses future efforts to refine, extend, and validate the models with more data and real data relative to physical (spatial-topographical) and social inputs (staffing, patient care models, etc.). Real data obtained through proximity location and tracking system technologies is one example discussed.

The convergent validity of the Child Abuse Potential Inventory (CAP) was investigated (N = 254). Because the CAP was designed to measure elements of individual pathology and interactional problems related to physical child abuse, it was predicted that CAP scores would be related to a measure of psychological status, the Mental Health Index (MHI). Specifically, it was predicted that the CAP would be correlated positively with MHI measures of psychological distress and, to a lesser degree, correlated inversely with MHI measures of psychological well-being. Because the CAP measures variables predictive of abusive behavior, a substantial relationship was expected between the CAP and the MHI Loss of Behavioral/Emotional Control scale. All hypotheses were supported.