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Abstract Background Health guideline developers engage with interested people and groups to ensure that guidelines and their recommendations are relevant and useful to those who will be affected by them. These ‘interest‐holders’ include patients, payers/purchasers of health services, payers of health research, peer review editors, product makers, programme managers, policymakers, providers, principal investigators, and the public. The Guidelines International Network (GIN) and McMaster University Guideline Development Checklist describes 146 steps of the guideline process organized into 18 topics. While one topic focuses on engagement, it does not describe how to engage with interest‐holders. In addition, interest‐holder input could be sought throughout the guideline development process. This scoping review is part of a series of four related reviews. The three other reviews address barriers and facilitators to engagement in guideline development, managing conflicts of interest in guideline development, and assessing the impact of interest‐holder engagement on guideline development. The four reviews will inform the development of guidance for multi‐interest‐holder engagement in guideline development; the GIN‐McMaster Guideline Development Checklist Extension for Engagement. Objectives The objective of this scoping review is to identify, describe, and summarise existing guidance and methods for multi‐interest‐holder engagement throughout the health guideline development process. Search Methods We conducted one comprehensive search for studies of engagement in guidelines to meet the inclusion criteria of one or more of the four systematic reviews in this series. We searched MEDLINE (OVID), CINAHL (EBSCO), EMBASE (OVID), PsycInfo (OVID) and SCOPUS databases up to September 2022. We did not include limits for date, study design, or language. We searched websites of agencies and organizations that engage interest‐holder groups, such as the Agency for Healthcare Research and Quality (AHRQ), CIHR Strategy for Patient‐Oriented Research (SPOR), National Institute for Health and Care Research (NIHR) Be Part of Research, Guidelines International Network (G‐I‐N), the National Institute for Health and Care Excellence, and the PatientCentred Outcomes Research Institute (PCORI). We handsearched the websites of guideline producing agencies. We solicited additional grey literature from the members of the MuSE Consortium. Selection Criteria Studies were included in this review if they reported on engagement of any of our identified groups, patients, payers/funders of research, payers/purchasers of health services, policymakers, programme managers, providers, principal investigators/researchers, peer review editors, product makers in the development of a health guideline. Titles and abstracts of identified citations were screened independently, in duplicate. The full text of potentially relevant papers were screened for eligibility into one or more of the four reviews in the series. Screening was done independently, by two reviewers. The team held weekly meetings with all reviewers involved in screening to discuss and resolve conflicts. Data Collection and Analysis Two reviewers extracted relevant data into a pilot‐tested data extraction form using Excel. We used the GIN‐McMaster guideline development checklist as a framework for extracting the available guidance for each of our identified interest‐holder groups throughout the development process. We presented descriptive statistics of the number of papers reporting guidance for each groups across the steps of the guideline process. We synthesized the relevant text using a qualitative meta‐summary approach. Main Results We included 16 papers (from 17 reports). These papers were from Australia, Denmark, the Netherlands, the UK, and the USA, and eight papers were international (countries not specified). The papers provided guidance for at least one of our interest‐holder groups for at least one stage of guideline development. We mapped this guidance to the GIN‐McMaster Guideline Development Checklist to identify the available guidance for each of our interest‐holder groups across all stages of the guideline development process. Guidance was available for patient engagement in 15 of the 16 papers. At least two papers provided guidance for each of the 18 topics of the GIN‐McMaster Guideline Development Checklist. For healthcare providers, 9 papers provided guidance for their engagement across 10 of the 18 guideline development topics. Guidance for engaging with the public was provided for 14 of the 18 topics and reported in 4 of our included papers. For payers/purchasers of health services, policymakers, product makers, programme managers, and principal investigators, 2–3 papers provided guidance for these groups across 4–7 topics of the GIN‐McMaster checklist. We did not identify any specific guidance for payers of health research or for editors of peer‐reviewed journals. Authors' Conclusions Guidance for interst‐holder engagement in guidelines is available but has focused primarily on patients. We will utilize the guidance identified in this scoping review to inform the GIN‐McMaster Guideline Development Checklist Extension for engagement. Combined with the information obtained from the other systematic reviews in this series, we will address the gaps in guidance for the other identified interest‐holder groups.

Abstract This is the protocol for a Campbell systematic review. The objectives are as follows. The objective of this review is to identify and synthesize empirical research on the impacts of interest‐holder engagement on the guideline development process and content. Our research questions are as follows: (1) What are the empirical examples of impact on the process in health guideline development across any of the 18 steps of the GIN‐McMaster checklist? (2) What are the empirical examples of impact on the content in health guideline development across any of the 18 steps of the GIN‐McMaster checklist?

Abstract Despite the recent increase in landscape conservation and the design processes agencies are undertaking, there remains an implementation gap due to an inability to evaluate general strategies and account for uncertainties faced by managers. We demonstrated how a decision support process (DSP), recently developed to inform landscape conservation design, can address uncertainties and complexities inherent in landscape conservation to facilitate long‐term, large‐scale conservation planning. We applied the DSP to landscape conservation efforts within conservation opportunity areas (COA) of states in the Gulf Coastal Plains and Ozarks region. We engaged state planners within the region to identify important landscape conservation uncertainties they face in planning. We developed, simulated, and modeled the impacts of conservation addressing 3 uncertainties identified by state wildlife managers and evaluated the impacts by examining the responses of state and local populations of 2 bird species of conservation concern, prairie warbler (Setophaga discolor) and wood thrush (Hylocichla mustelina). The responses of prairie warbler populations to conservation strategies indicated that both approaches of protecting quality habitat from land‐use change and restoring and enhancing lower quality and nonhabitat improved their viability at regional, statewide, and COA scales. However, we noted that the relative effectiveness of strategies varied among states in ways that suggest a state's process for delineating COAs and what threats they face could influence which conservation approach to consider. Our findings highlight the need for regional coordination and the use of decision‐support processes to guide effective conservation at landscape scales.

Abstract Pitfall traps are frequently used to capture ground‐dwelling arthropods, particularly beetles, ants and spiders. The capture efficiency of a pitfall trapping system strongly depends on the number and opening size of traps, how traps are distributed over the sampling area (spatial arrangement) and the movement characteristics of arthropods. We use numerical simulations for a single species to analyse the trap count patterns that emerge from these variables. Arthropod movement of individuals is modelled as correlated random walks, with multiple traps placed over an area, and catches are simulated as individual interaction with traps. We consider four different types of spatial arrangements of traps across a homogeneous landscape: grid (i.e. rectangular array), transect, nested‐cross and randomised. We contextualise our results by considering the locomotion of Pterostichus melanarius, a highly active carabid beetle often serving as a biocontrol agent for the suppression of pest insects and weeds. By simulating the trapping of randomly moving ground‐dwelling arthropods, we show that there is an optimal inter‐trap separation distance (trap spacing) that maximises captures, that can be expressed using exact formulae in terms of trap opening sizes, sampling area and trap number. Moreover, for the grid and nested‐cross arrangements, larger trap spacing to maximise spatial coverage over the whole sampling area is suboptimal. Also, we find that over a large sampling area, there is a hierarchical order for spatial arrangements in relation to capture efficiency: grid, randomised, transect, followed by the nested‐cross. However, over smaller sampling areas, this order is changed as the rate at which trap counts accumulate with trap number varies across arrangements—eventually saturating at different levels. In terms of movement effects, capture efficiency is maximised over a narrow diffusive range and does not depend strongly on the type of spatial arrangement—indicating an approximate optimal mode of arthropod activity, i.e. rate of spread. Our approach simultaneously considers several important experimental design aspects of pitfall trapping providing a basis to optimise and adapt sampling protocols to other types of traps to better reflect their various purposes, such as monitoring, conservation or pest management.

Abstract Step selection analysis (SSA) is a common framework for understanding animal movement and resource selection using telemetry data. Such data are, however, inherently autocorrelated in space, a complication that could impact SSA‐based inference if left unaddressed. Accounting for spatial correlation is standard statistical practice when analysing spatial data, and its importance is increasingly recognized in ecological models (e.g. species distribution models). Nonetheless, no framework yet exists to account for such correlation when analysing animal movement using SSA. Here, we extend the popular method integrated step selection analysis (iSSA) by including a Gaussian field (GF) in the linear predictor to account for spatial correlation. For this, we use the Bayesian framework R‐INLA and the stochastic partial differential equations (SPDE) technique. We show through a simulation study that our method provides accurate fixed effects estimates, quantifies their uncertainty well and improves the predictions. In addition, we demonstrate the practical utility of our method by applying it to three wolverine (Gulo gulo) tracks. Our method solves the problems of assuming spatially independent residuals in the SSA framework. In addition, it offers new possibilities for making long‐term predictions of habitat usage.

Abstract Successful epilepsy surgery depends on localizing and resecting cerebral abnormalities and networks that generate seizures. Abnormalities, however, may be widely distributed across multiple discontiguous areas. We propose spatially constrained clusters as candidate areas for further investigation and potential resection. We quantified the spatial overlap between the abnormality cluster and subsequent resection, hypothesizing a greater overlap in seizure‐free patients. Thirty‐four individuals with refractory focal epilepsy underwent pre‐surgical resting‐state interictal magnetoencephalography (MEG) recording. Fourteen individuals were totally seizure‐free (ILAE 1) after surgery and 20 continued to have some seizures post‐operatively (ILAE 2+). Band power abnormality maps were derived using controls as a baseline. Patient abnormalities were spatially clustered using the k‐means algorithm. The tissue within the cluster containing the most abnormal region was compared with the resection volume using the dice score. The proposed abnormality cluster overlapped with the resection in 71% of ILAE 1 patients. Conversely, an overlap only occurred in 15% of ILAE 2+ patients. This effect discriminated outcome groups well (AUC = 0.82). Our novel approach identifies clusters of spatially similar tissue with high abnormality. This is clinically valuable, providing (a) a data‐driven framework to validate current hypotheses of the epileptogenic zone localization or (b) to guide further investigation.

Abstract Background Meningoencephalitis of unknown origin (MUO) comprises a group of debilitating inflammatory diseases affecting the central nervous system of dogs. Currently, no validated clinical scale is available for the objective assessment of MUO severity. Objectives Design a neurodisability scale (NDS) to grade clinical severity and determine its reliability and whether or not the score at presentation correlates with outcome. Animals One hundred dogs with MUO were included for retrospective review and 31 dogs were subsequently enrolled for prospective evaluation. Methods Medical records were retrospectively reviewed for 100 dogs diagnosed with MUO to identify the most frequent neurological examination findings. The NDS was designed based on these results and evaluated for prospective and retrospective use in a new population of MUO patients (n = 31) by different groups of independent blinded assessors, including calculation of interobserver agreement and association with outcome. Results The most common clinical signs in MUO patients were used to inform categories for scoring in the NDS: seizure activity, ambulatory status, posture and cerebral, cerebellar, brainstem, and visual functions. The intraclass correlation coefficient (ICC) for prospective use of the NDS was 0.83 (95% confidence interval [CI], 0.68‐0.91) indicating good agreement, and moderate agreement was found between prospective and retrospective assessors (ICC, 0.71; 95% CI, 0.56‐0.83). No association was found between NDS score and long‐term outcome. Conclusions and Clinical Importance The NDS is a novel clinical measure for objective assessment of neurological dysfunction and showed good reliability when used prospectively in MUO patients but, in this small population, no association with outcome could be identified.

Abstract Background Treatment of nasal tumors in dogs is associated with high morbidity and reliable prognostic factors are lacking. Dynamic contrast‐enhanced computed tomography (DCECT) can be used to assess tumor perfusion. Objectives To assess perfusion parameters of nasal tumors (correlating with tumor type) before and during radiotherapy (RT) and find potential correlation with survival. Animals Twenty‐four client‐owned dogs with nasal tumors, including 16 epithelial tumors and 8 sarcomas. Methods Prospective cross‐sectional study. All dogs had baseline DCECT to assess fractional vascular volume (BV), blood flow (BF), and transit time (TT). Thirteen dogs had repeat DCECT after 12 Gy of megavoltage RT. Survival times were calculated. Results Median BV was 17.83 mL/100 g (range, 3.63‐66.02), median BF was 122.63 mL/100 g/minute (range, 23.65‐279.99), and median TT was 8.91 seconds (range, 4.57‐14.23). Sarcomas had a significantly lower BF than adenocarcinomas (P = .002), carcinomas (P = .01), and other carcinomas (P = .001), and significantly lower BV than adenocarcinomas (P = .03) and other carcinomas (P = .004). Significant associations were found between epithelial tumors and sarcoma for change in tumor volume (P = .01), width (P = .004), and length (P = .02) in that epithelial tumors decreased in volume whereas sarcomas increased in volume. Perfusion parameters were not correlated with survival. Conclusions and Clinical Importance Nasal sarcomas have lower BV and BF than nasal carcinomas, and sarcomas have a lower size reduction than carcinomas early on during RT. Baseline results and changes in perfusion parameters may not be correlated with survival.

Conclusion: While clinical trial enrollment remains low for men with advanced prostate cancer in this contemporary population-based cohort, rates of participation for Hispanic/Latino men, but not Black men, are significantly lower. Increased attention is needed to better understand the reasons behind these racial disparities and to develop effective interventions to promote access.

Abstract Global change is affecting soil biodiversity and functioning across all terrestrial ecosystems. Still, much is unknown about how soil biodiversity and function will change in the future in response to simultaneous alterations in climate and land use, as well as other environmental drivers. It is crucial to understand the direct, indirect and interactive effects of global change drivers on soil communities and ecosystems across environmental contexts, not only today but also in the near future. This is particularly relevant for international efforts to tackle climate change like the Paris Agreement, and considering the failure to achieve the 2020 biodiversity targets, especially the target of halting soil degradation. Here, we outline the main frontiers related to soil ecology that were presented and discussed at the thematic sessions of the World Biodiversity Forum 2022 in Davos, Switzerland. We highlight multiple frontiers of knowledge associated with data integration, causal inference, soil biodiversity and function scenarios, critical soil biodiversity facets, underrepresented drivers, global collaboration, knowledge application and transdisciplinarity, as well as policy and public communication. These identified research priorities are not only of immediate interest to the scientific community but may also be considered in research priority programmes and calls for funding.

Abstract The brown‐headed nuthatch (Sitta pusilla) was likely extirpated from Missouri in the early 1900s as a result of habitat loss through extensive logging. Conservation partners including the Missouri Department of Conservation, United States Forest Service, University of Missouri, and others, relocated 102 brown‐headed nuthatches from Ouachita National Forest in Arkansas to Mark Twain National Forest in Missouri in 2020 and 2021 to establish a local population. We tracked 50 individuals for 24 ± 11 (median ± SD) days after release using radio telemetry and monitored movements in relation to sex and whether a bird was captured alone or as part of a group. We examined 25‐day survival using a spatial Cormack Jolly Seber (sCJS) model to account for likely dispersal outside of our study area. All birds survived capture, transport, and release. The 25‐day survival estimate was 0.56 (95% CI = 0.36–0.78) in 2020 and 0.68 (95% CI = 0.46–0.89) in 2021. Mean total distance moved following release was 5,670 (SD = 3,407) m and mean daily movement was 243 (SD = 135) m which was less than the mean daily dispersal distance estimated from our sCJS model (420 m, SD = 221). Our short‐term monitoring suggests initial success of the translocation, but continued monitoring is needed to evaluate long‐term success. Our survival analysis approach, which included movement data, illustrates the importance of considering dispersal when estimating survival.

Abstract Background A key question for any psychopathological diagnosis is whether the condition is continuous or discontinuous with typical variation. The primary objective of this study was to use a multi‐method approach to examine the broad latent categorical versus dimensional structure of autism spectrum disorder (ASD). Method Data were aggregated across seven independent samples of participants with ASD, other neurodevelopmental disorders (NDD), and non‐ASD/NDD controls (aggregate Ns = 512–16,755; ages 1.5–22). Scores from four distinct phenotype measures formed composite “indicators” of the latent ASD construct. The primary indicator set included eye gaze metrics from seven distinct social stimulus paradigms. Logistic regressions were used to combine gaze metrics within/across paradigms, and derived predicted probabilities served as indicator values. Secondary indicator sets were constructed from clinical observation and parent‐report measures of ASD symptoms. Indicator sets were submitted to taxometric‐ and latent class analyses. Results Across all indicator sets and analytic methods, there was strong support for categorical structure corresponding closely to ASD diagnosis. Consistent with notions of substantial phenotypic heterogeneity, the ASD category had a wide range of symptom severity. Despite the examination of a large sample with a wide range of IQs in both genders, males and children with lower IQ were over‐represented in the ASD category, similar to observations in diagnosed cases. Conclusions Our findings provide strong support for categorical structure corresponding closely to ASD diagnosis. The present results bolster the use of well‐diagnosed and representative ASD groups within etiologic and clinical research, motivating the ongoing search for major drivers of the ASD phenotype. Despite the categorical structure of ASD, quantitative symptom measurements appear more useful for examining relationships with other factors.

Abstract The National Forestry Commission of Mexico continuously monitors forest structure within the country's continental territory by the implementation of the National Forest and Soils Inventory (INFyS). Due to the challenges involved in collecting data exclusively from field surveys, there are spatial information gaps for important forest attributes. This can produce bias or increase uncertainty when generating estimates required to support forest management decisions. Our objective is to predict the spatial distribution of tree height and tree density in all Mexican forests. We performed wall‐to‐wall spatial predictions of both attributes in 1‐km grids, using ensemble machine learning across each forest type in Mexico. Predictor variables include remote sensing imagery and other geospatial data (e.g., mean precipitation, surface temperature, canopy cover). Training data is from the 2009 to 2014 cycle (n > 26,000 sampling plots). Spatial cross validation suggested that the model had a better performance when predicting tree height r2 = .35 [.12, .51] (mean [min, max]) than for tree density r2 = .23 [.05, .42]. The best predictive performance when mapping tree height was for broadleaf and coniferous‐broadleaf forests (model explained ~50% of variance). The best predictive performance when mapping tree density was for tropical forest (model explained ~40% of variance). Although most forests had relatively low uncertainty for tree height predictions, e.g., values 80%. Uncertainty values for tree density predictions were >80% in most forests. The applied open science approach we present is easily replicable and scalable, thus it is helpful to assist in the decision‐making and future of the National Forest and Soils Inventory. This work highlights the need for analytical tools that help us exploit the full potential of the Mexican forest inventory datasets.

Abstract In the northeast Pacific Ocean, there is high interest in developing eDNA‐based survey methods to aid management of invasive populations of European green crab (Carcinus maenas). Expected benefits are improved sensitivity for early detection of secondary spread and to assess the outcome of eradication efforts. A new eDNA‐based approach we term “targeted next‐generation sequencing (tNGS)” is introduced here and shown to improve detection relative to qPCR at sites with lower green crab CPUE values measured by trapping. DNA standards (gBlock) with starting molecule copies that were 10 to 100 times lower than the qPCR limit of detection returned significant numbers of sequencing reads, which in our field assessments translated to a 7%–10% increase in detection probability from tNGS relative to qPCR at sites with lower CPUE. We also found the number of sequencing reads from tNGS was significantly correlated with green crab CPUE whereas Ct values from qPCR were not. When sources of variation were partitioned for each assay, we found the difference between mean within‐site and mean between‐site variation was much larger and had non‐overlapping confidence intervals for tNGS relative to qPCR, suggesting the former may offer more power for detecting spatial variation in eDNA availability. Results presented here indicate this approach is suitable for species of known low abundances where a positive detection has high economic or environmental consequences, or for labs doing eDNA surveys for whom NGS‐based workflows are operationally more efficient than qPCR given its upward scalability. Any species with an existing qPCR assay can be easily tested with a tNGS assay using the approach presented here. We conclude with a discussion on the fitness for purpose of tNGS vs. qPCR for various applications and on how to best apply molecular surveys in management programs.

Abstract Under controlled laboratory conditions, previous studies have shown that selection can produce repeatable evolutionary trajectories. Yet, the question remains for many of these studies if, given identical starting populations, evolution in the wild proceeds in a non‐random direction. In the present study, we investigated the extent to which rapid evolution in the wild is parallel by monitoring the genetic composition of replicate populations of Daphnia in field mesocosms containing two clonal genotypes. We found parallel changes across all nine mesocosms, in which the same genotype increased in frequency. To probe whether genotype‐specific response to resource abundance could have led to this frequency change, we conducted a life‐history assay under high‐resource abundance and low‐resource abundance. We found that resource exploitation differed by genotype, in that, while one genotype (the winner in the field mesocosms) was more fit than the other genotype at high resources, the other genotype performed slightly better at low resources. We suspect that levels of resource abundance found in the summer field mesocosms had values in which the genotype better with abundant resources had the advantage. These findings suggest that variation in certain traits associated with resource acquisition can drive genotype frequency change.

Abstract Various morphological proxies have been used to infer habitat preferences among fossil turtles and their early ancestors, but most are tightly linked to phylogeny, thereby minimizing their predictive power. One particularly widely used model incorporates linear measurements of the forelimb (humerus + ulna + manus), but in addition to the issue of phylogenetic correlation, it does not estimate the likelihood of habitat assignment. Here, we introduce a new model that uses intramanual measurements (digit III metacarpal + non‐ungual phalanges + ungual) to statistically estimate habitat likelihood and that has greater predictive strength than prior estimators. Application of the model supports the hypothesis that stem‐turtles were primarily terrestrial in nature and recovers the nanhsiungchelyid Basilemys (a fossil crown‐group turtle) as having lived primarily on land, despite some prior claims to the contrary.

Abstract Background The evidence based on the inclusion of patients and other stakeholders as partners in the clinical research process has grown substantially. However, little has been reported on how stakeholders are engaged in the governance of large‐scale clinical research networks and the infrastructure used by research networks to support engagement in network‐affiliated activities. Objectives The objective was to document engagement activities and practices emerging from Clinical Research Networks (CRNs) participating in PCORnet, the National Patient‐Centered Clinical Research Network, specifically regarding governance and engagement infrastructure. Methods We conducted an environmental scan of PCORnet CRN engagement structures, assets, and services, focusing on network oversight structures for policy development and strategic decision‐making. The scan included assets and services for supporting patient/stakeholder engagement. Data were collected by searching web‐based literature and tool repositories, review of CRN Engagement Plans, analysis of previously collected key informant interviews, and CRN‐based iterative review of structured worksheets. Results We identified 87 discrete engagement structures, assets, and services across nine CRNs. All CRNs engage patients/stakeholders in their governance, maintain workgroups and/or staff dedicated to overseeing engagement strategies, and offer one or more services to non‐CRN researchers to enhance conducting engaged clinical research. Conclusions This work provides an important resource for the research community to explore engagement across peers, reflect on progress, consider opportunities to leverage existing infrastructure, and identify new collaborators. It also serves to highlight PCORnet as a resource for non‐CRN researchers seeking to efficiently conduct engaged clinical research and a venue for advancing the science of engagement.

Abstract That phytochemicals are a critical part of enhancing healthspan is in our minds a linchpin of responsible public health messaging, yet, recent dietary guidelines and strategies for implementing precision nutrition largely ignore roles of phytochemicals. Epidemiological evidence points strongly to beneficial effects of phytochemical‐rich foods on the prevention of essentially all chronic diseases. An extraordinary multitude of phytochemicals have been shown in preclinical settings to be potent allies in our fight against the entire spectrum of chronic diseases and many acute conditions such as infections. Yet unequivocal proof of this concept is problematic due to the nature of the clinical trials that must be part of such a proof. More rigor in the design and implementation of such trials is essential. Artificial intelligence, machine learning, metabolomics, microbiomics, proteomics, and other high‐powered data processing modalities, may inform the phyto‐dynamic actions on very specific metabolic pathways. As phytochemical abundance appears to be declining in our food supply, the need for better and more strategically focused science is great.

Abstract This study describes the evolution of knockdown resistance (kdr) haplotypes in Aedes aegypti in response to pyrethroid insecticide use over the course of 18 years in Iquitos, Peru. Based on the duration and intensiveness of sampling (~10,000 samples), this is the most thorough study of kdr population genetics in Ae. aegypti to date within a city. We provide evidence for the direct connection between programmatic citywide pyrethroid spraying and the increase in frequency of specific kdr haplotypes by identifying two evolutionary events in the population. The relatively high selection coefficients, even under infrequent insecticide pressure, emphasize how quickly Ae. aegypti populations can evolve. In our examination of the literature on mosquitoes and other insect pests, we could find no cases where a pest evolved so quickly to so few exposures to low or nonresidual insecticide applications. The observed rapid increase in frequency of resistance alleles might have been aided by the incomplete dominance of resistance‐conferring alleles over corresponding susceptibility alleles. In addition to dramatic temporal shifts, spatial suppression experiments reveal that genetic heterogeneity existed not only at the citywide scale, but also on a very fine scale within the city.

Abstract A growing body of work examines the direct and indirect effects of climate change on ecosystems, typically by using manipulative experiments at a single site or performing meta‐analyses across many independent experiments. However, results from single‐site studies tend to have limited generality. Although meta‐analytic approaches can help overcome this by exploring trends across sites, the inherent limitations in combining disparate datasets from independent approaches remain a major challenge. In this paper, we present a globally distributed experimental network that can be used to disentangle the direct and indirect effects of climate change. We discuss how natural gradients, experimental approaches, and statistical techniques can be combined to best inform predictions about responses to climate change, and we present a globally distributed experiment that utilizes natural environmental gradients to better understand long‐term community and ecosystem responses to environmental change. The warming and (species) removal in mountains (WaRM) network employs experimental warming and plant species removals at high‐ and low‐elevation sites in a factorial design to examine the combined and relative effects of climatic warming and the loss of dominant species on community structure and ecosystem function, both above‐ and belowground. The experimental design of the network allows for increasingly common statistical approaches to further elucidate the direct and indirect effects of warming. We argue that combining ecological observations and experiments along gradients is a powerful approach to make stronger predictions of how ecosystems will function in a warming world as species are lost, or gained, in local communities.

Background Intracoronary imaging (ICI) has been shown to improve survival after percutaneous coronary intervention (PCI). Whether this prognostic benefit is sustained across different indications remains unclear. Methods and Results All PCI procedures performed in England and Wales between April, 2014 and March 31, 2020, were retrospectively analyzed. The association between ICI use and in‐hospital major acute cardiovascular and cerebrovascular events; composite of all‐cause mortality, stroke, and reinfarction and mortality was examined using multivariable logistic regression analysis for different imaging‐recommended indications as set by European Association for Percutaneous Cardiovascular Interventions consensus. Of 555 398 PCI procedures, 10.8% (n=59 752) were ICI‐guided. ICI use doubled between 2014 (7.8%) and 2020 (17.5%) and was highest in left main PCI (41.2%) and lowest in acute coronary syndrome (9%). Only specific European Association for Percutaneous Cardiovascular Interventions imaging‐recommended indications were associated with reduced major acute cardiovascular and cerebrovascular events and mortality, including left main PCI (odds ratio [OR], 0.45 [95% CI, 0.39–0.52] and 0.41 [95% CI, 0.35–0.48], respectively), acute coronary syndrome (OR, 0.76 [95% CI, 0.70–0.82] and 0.70 [95% CI, 0.63–0.77]), and stent length >60 mm (OR, 0.75 [95% CI, 0.59–0.94] and 0.72 [95% CI, 0.54–0.95]). Stent thrombosis and renal failure were associated with lower mortality (OR, 0.69 [95% CI, 0.52–0.91]) and major acute cardiovascular and cerebrovascular events (OR, 0.77 [95% CI, 0.60–0.99]), respectively. Conclusions ICI use has more than doubled over a 7‐year period at a national level but remains low, with

Abstract The introduction of artificial nighttime lighting due to human settlements and transport networks is increasingly altering the timing, intensity, and spectra of natural light regimes worldwide. Much of the research on the impacts of nighttime light pollution on organisms has focused on animal species. Little is known about the impacts of daylength extension due to outdoor lighting technologies on wild plant communities, despite the fact that plant growth and development are under photoperiodic control. In a five‐year field experiment, artificial ecosystems (“mesocosms”) of grassland communities both alone or in combination with invertebrate herbivores and predators were exposed to light treatments that simulated street lighting technologies (low‐pressure sodium, and light‐emitting diode [LED]‐based white lighting), at ground‐level illuminance. Most of the plant species in the mesocosms did not exhibit changes in biomass accumulation after 5 years of exposure to the light treatments. However, the white LED treatment had a significant negative effect on biomass production in the herbaceous species Lotus pedunculatus. Likewise, the interaction between the white LED treatment and the presence of herbivores significantly reduced the mean shoot/root ratio of the grass species Holcus lanatus. Artificial nighttime lighting had no effect on the foliar carbon or nitrogen in most of the grassland species. Nevertheless, the white LED treatment significantly increased the leaf nitrogen content in Lotus corniculatus in the presence of herbivores. Long‐term exposure to artificial light at night had no general effects on plant biomass responses in experimental grassland communities. However, species‐specific and negative effects of cool white LED lighting at ground‐level illuminance on biomass production and allocation in mixed plant communities are suggested by our findings. Further studies on the impacts of light pollution on biomass accumulation in plant communities are required as these effects could be mediated by different factors, including herbivory, competition, and soil nutrient availability.

Abstract The Chauvet‐Pont‐d'Arc Cave (Ardèche, France) contains some of the oldest Paleolithic paintings recorded to date, as well as thousands of bones of the extinct cave bear, and some remains and footprints of other animals. As part of the interdisciplinary research project devoted to this reference cave site, we analyzed a coprolite collected within the deep cave. AMS radiocarbon dating of bone fragments from the coprolite yielded an age of 30,450 ± 550 RC yr. BP (AAR‐19656; 36,150–34,000 cal BP), similar to ages assigned to Paleolithic artwork and cave bear remains from the same cave sector. Using high‐throughput shotgun DNA sequencing, we demonstrated a high abundance of canid DNA and lesser amounts of DNA from the extinct cave bear. We interpret the sample as feces from a canid that had consumed cave bear tissue. The high amount of canid DNA allowed us to reconstruct a complete canid mitochondrial genome sequence (average coverage: 83×) belonging to a deeply divergent clade of extinct mitochondrial wolf lineages that are most closely related to coeval (~35 ka) Belgian wolves. Analysis of the nuclear genome yielded a similar coverage for the X chromosome (2.4×) and the autosomes (range: 2.3–3.2×), indicating that the Chauvet canid was a female. Comparing the relationship of the nuclear genome of this specimen with that of a variety of canids, we found it more closely related to gray wolves' genomes than to other wild canid or dog genomes, especially wolf genomes from Europe and the Middle East. We conclude that the coprolite is feces from an animal within an extinct wolf lineage. The consumption of cave bear by this wolf likely explains its intrusion into the dark cave sectors and sheds new light on the paleoecology of a major cave site.

Abstract Aim To investigate whether the frequently advocated climate‐matching species distribution modeling approach could predict the well‐characterized colonization of Florida by the Madagascar giant day gecko Phelsuma grandis. Location Madagascar and Florida, USA. Methods To determine the climatic conditions associated with the native range of P. grandis, we used native‐range presence‐only records and Bioclim climatic data to build a Maxent species distribution model and projected the climatic thresholds of the native range onto Florida. We then built an analogous model using Florida presence‐only data and projected it onto Madagascar. We constructed a third model using native‐range presences for both P. grandis and the closely related parapatric species P. kochi. Results Despite performing well within the native range, our Madagascar Bioclim model failed to identify suitable climatic habitat currently occupied by P. grandis in Florida. The model constructed using Florida presences also failed to reflect the distribution in Madagascar by overpredicting distribution, especially in western areas occupied by P. kochi. The model built using the combined P. kochi/P. grandis dataset modestly improved the prediction of the range of P. grandis in Florida, thereby implying competitive exclusion of P. grandis by P. kochi from habitat within the former's fundamental niche. These findings thus suggest ecological release of P. grandis in Florida. However, because ecological release cannot fully explain the divergent occupied niches of P. grandis in Madagascar versus Florida, our findings also demonstrate some degree of in situ adaptation in Florida. Main conclusions Our models suggest that the discrepancy between the predicted and observed range of P. grandis in Florida is attributable to either in situ adaptation by P. grandis within Florida, or a combination of such in situ adaptation and competition with P. kochi in Madagascar. Our study demonstrates that climate‐matching species distribution models can severely underpredict the establishment risk posed by non‐native herpetofauna.

Abstract Over the last century, anthropogenic activities have caused substantial declines in the abundance of chum salmon (Oncorhynchus keta) throughout their range in western North America. As a result, chum salmon were listed as threatened under the U.S. Endangered Species Act in 1999. Recovery strategies have been developed, but limited baseline data on distribution impedes implementation of these strategies. Traditional methods for identifying spawning distribution (e.g., spawning ground surveys) may be inadequate for rare species like chum salmon because of a low detection probability. In contrast, environmental DNA (eDNA) sampling is extremely sensitive to species presence and has the potential to supplement or replace existing methods for monitoring listed species. However, legal and administrative issues associated with accurately describing distribution of a listed species put a premium on understanding factors that influence detection of a species by eDNA sampling. In this study, we (a) developed and tested a quantitative PCR‐based eDNA assay for chum salmon, (b) collected eDNA samples to describe the spawning distribution of this species in Columbia River tributaries between Bonneville and The Dalles Dams, and (c) tested whether spawn surveyors could inadvertently transport chum salmon DNA between streams on their boots and waders. The newly developed assay was specific and sensitive to chum salmon DNA in both tissue and eDNA samples. Chum salmon DNA was detected in the positive control site and in four streams, which increased known contemporary spawning locations in the study area. In the contamination trial, surveyors successfully introduced chum salmon DNA into the study area but eDNA was only detected intermittently and locally over the next 11 days. The accuracy of eDNA sampling, combined with success in detecting a rare species at the population scale, makes this technique well‐suited for monitoring recolonization of chum salmon during the recovery process.

Abstract A lineage of the Mountain Sucker species complex (Pantosteus jordani) exists as a genetically and morphologically distinct taxon restricted to the Missouri River basin. This species is thought to be declining throughout its range and is assumed to be extirpated from the southern portion of its distribution. We developed a quantitative PCR‐based environmental DNA assay for P. jordani to help define and monitor its current range. The assay is both specific to P. jordani and sensitive to low amounts of DNA, with a detection limit of 10 DNA copies per reaction. In vitro experiments involved testing DNA from twenty tissue samples, collected from the Missouri River basin in Montana and Wyoming. The assay efficiently detected DNA of all P. jordani samples and did not amplify DNA of any closely related nontarget species. Additionally, 29 environmental DNA samples were taken in 19 waterbodies within P. jordani range and its presence or absence was determined prior to sampling at six of 29 sites. All sites where P. jordani was known absent produced negative results, and all sites where it was known present were confirmed with environmental DNA detections. The new assay was able to detect P. jordani at ten sites which were not previously known to contain individuals, demonstrating that this tool has the potential to rapidly expand the current understanding of this taxon's distribution.

Abstract Fire regimes in North American forests are diverse and modern fire records are often too short to capture important patterns, trends, feedbacks, and drivers of variability. Tree‐ring fire scars provide valuable perspectives on fire regimes, including centuries‐long records of fire year, season, frequency, severity, and size. Here, we introduce the newly compiled North American tree‐ring fire‐scar network (NAFSN), which contains 2562 sites, >37,000 fire‐scarred trees, and covers large parts of North America. We investigate the NAFSN in terms of geography, sample depth, vegetation, topography, climate, and human land use. Fire scars are found in most ecoregions, from boreal forests in northern Alaska and Canada to subtropical forests in southern Florida and Mexico. The network includes 91 tree species, but is dominated by gymnosperms in the genus Pinus. Fire scars are found from sea level to >4000‐m elevation and across a range of topographic settings that vary by ecoregion. Multiple regions are densely sampled (e.g., >1000 fire‐scarred trees), enabling new spatial analyses such as reconstructions of area burned. To demonstrate the potential of the network, we compared the climate space of the NAFSN to those of modern fires and forests; the NAFSN spans a climate space largely representative of the forested areas in North America, with notable gaps in warmer tropical climates. Modern fires are burning in similar climate spaces as historical fires, but disproportionately in warmer regions compared to the historical record, possibly related to under‐sampling of warm subtropical forests or supporting observations of changing fire regimes. The historical influence of Indigenous and non‐Indigenous human land use on fire regimes varies in space and time. A 20th century fire deficit associated with human activities is evident in many regions, yet fire regimes characterized by frequent surface fires are still active in some areas (e.g., Mexico and the southeastern United States). These analyses provide a foundation and framework for future studies using the hundreds of thousands of annually‐ to sub‐annually‐resolved tree‐ring records of fire spanning centuries, which will further advance our understanding of the interactions among fire, climate, topography, vegetation, and humans across North America.

Abstract Purpose Several cases of symptomatic reinfection with severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) after full recovery from a prior episode have been reported. As reinfection has become an increasingly common phenomenon, an improved understanding of the risk factors for reinfection and the character and duration of the serological responses to infection and vaccination is critical for managing the coronavirus disease 2019 (COVID‐19) pandemic. Methods We described four cases of SARS‐CoV‐2 reinfection in individuals representing a spectrum of healthy and immunocompromised states, including (1) a healthy 41‐year‐old pediatrician, (2) an immunocompromised 31‐year‐old with granulomatosis with polyangiitis, (3) a healthy 26‐year‐old pregnant woman, and (4) a 50‐year‐old with hypertension and hyperlipidemia. We performed confirmatory quantitative reverse transcription‐polymerase chain reaction and qualitative immunoglobulin M and quantitative IgG testing on all available patient samples to confirm the presence of infection and serological response to infection. Results Our analysis showed that patients 1 and 2, a healthy and an immunocompromised patient, both failed to mount a robust serologic response to the initial infection. In contrast, patients 3 and 4, with minimal comorbid disease, both mounted a strong serological response to their initial infection, but were still susceptible to reinfection. Conclusion Repeat episodes of COVID‐19 are capable of occurring in patients regardless of the presence of known risk factors for infection or level of serological response to infection, although this did not trigger critical illness in any instance.

Abstract For wildlife inhabiting snowy environments, snow properties such as onset date, depth, strength, and distribution can influence many aspects of ecology, including movement, community dynamics, energy expenditure, and forage accessibility. As a result, snow plays a considerable role in individual fitness and ultimately population dynamics, and its evaluation is, therefore, important for comprehensive understanding of ecosystem processes in regions experiencing snow. Such understanding, and particularly study of how wildlife–snow relationships may be changing, grows more urgent as winter processes become less predictable and often more extreme under global climate change. However, studying and monitoring wildlife–snow relationships continue to be challenging because characterizing snow, an inherently complex and constantly changing environmental feature, and identifying, accessing, and applying relevant snow information at appropriate spatial and temporal scales, often require a detailed understanding of physical snow science and technologies that typically lie outside the expertise of wildlife researchers and managers. We argue that thoroughly assessing the role of snow in wildlife ecology requires substantive collaboration between researchers with expertise in each of these two fields, leveraging the discipline‐specific knowledge brought by both wildlife and snow professionals. To facilitate this collaboration and encourage more effective exploration of wildlife–snow questions, we provide a five‐step protocol: (1) identify relevant snow property information; (2) specify spatial, temporal, and informational requirements; (3) build the necessary datasets; (4) implement quality control procedures; and (5) incorporate snow information into wildlife analyses. Additionally, we explore the types of snow information that can be used within this collaborative framework. We illustrate, in the context of two examples, field observations, remote‐sensing datasets, and four example modeling tools that simulate spatiotemporal snow property distributions and, in some cases, evolutions. For each type of snow data, we highlight the collaborative opportunities for wildlife and snow professionals when designing snow data collection efforts, processing snow remote sensing products, producing tailored snow datasets, and applying the resulting snow information in wildlife analyses. We seek to provide a clear path for wildlife professionals to address wildlife–snow questions and improve ecological inference by integrating the best available snow science through collaboration with snow professionals.

Abstract Background There is a need for the development of comprehensive, global, evidence‐based guidance for stakeholder engagement in guideline development. Stakeholders are any individual or group who is responsible for or affected by health‐ and healthcare‐related decisions. This includes patients, the public, providers of health care and policymakers for example. As part of the guidance development process, Multi‐Stakeholder Engagement (MuSE) Consortium set out to conduct four concurrent systematic reviews to summarise the evidence on: (1) existing guidance for stakeholder engagement in guideline development, (2) barriers and facilitators to stakeholder engagement in guideline development, (3) managing conflicts of interest in stakeholder engagement in guideline development and (4) measuring the impact of stakeholder engagement in guideline development. This protocol addresses the second systematic review in the series. Objectives The objective of this review is to identify and synthesise the existing evidence on barriers and facilitators to stakeholder engagement in health guideline development. We will address this objective through two research questions: (1) What are the barriers to multi‐stakeholder engagement in health guideline development across any of the 18 steps of the GIN‐McMaster checklist? (2) What are the facilitators to multi‐stakeholder engagement in health guideline development across any of the 18 steps of the GIN‐McMaster checklist? Search Methods A comprehensive search strategy will be developed and peer‐reviewed in consultation with a medical librarian. We will search the following databases: MEDLINE, Cumulative Index to Nursing & Allied Health Literature (CINAHL), EMBASE, PsycInfo, Scopus, and Sociological Abstracts. To identify grey literature, we will search the websites of agencies who actively engage stakeholder groups such as the AHRQ, Canadian Institutes of Health Research (CIHR) Strategy for Patient‐Oriented Research (SPOR), INVOLVE, the National Institute for Health and Care Excellence (NICE) and the PCORI. We will also search the websites of guideline‐producing agencies, such as the American Academy of Pediatrics, Australia's National Health Medical Research Council (NHMRC) and the WHO. We will invite members of the team to suggest grey literature sources and we plan to broaden the search by soliciting suggestions via social media, such as Twitter. Selection Criteria We will include empirical qualitative and mixed‐method primary research studies which qualitatively report on the barriers or facilitators to stakeholder engagement in health guideline development. The population of interest is stakeholders in health guideline development. Building on previous work, we have identified 13 types of stakeholders whose input can enhance the relevance and uptake of guidelines: Patients, caregivers and patient advocates; Public; Providers of health care; Payers of health services; Payers of research; Policy makers; Program managers; Product makers; Purchasers; Principal investigators and their research teams; and Peer‐review editors/publishers. Eligible studies must describe stakeholder engagement at any of the following steps of the GIN‐McMaster Checklist for Guideline Development. Data Collection and Analysis All identified citations from electronic databases will be imported into Covidence software for screening and selection. Documents identified through our grey literature search will be managed and screened using an Excel spreadsheet. A two‐part study selection process will be used for all identified citations: (1) a title and abstract review and (2) full‐text review. At each stage, teams of two review authors will independently assess all potential studies in duplicate using a priori inclusion and exclusion criteria. Data will be extracted by two review authors independently and in duplicate according to a standardised data extraction form. Main Results The results of this review will be used to inform the development of guidance for multi‐stakeholder engagement in guideline development and implementation. This guidance will be official GRADE (Grading of Recommendations Assessment, Development and Evaluation) Working Group guidance. The GRADE system is internationally recognised as a standard for guideline development. The findings of this review will assist organisations who develop healthcare, public health and health policy guidelines, such as the World Health Organization, to involve multiple stakeholders in the guideline development process to ensure the development of relevant, high quality and transparent guidelines.