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Abstract Non‐native annual grasses can dramatically alter fire frequency and reduce forage quality and biodiversity in the ecosystems they invade. Effective management techniques are needed to reduce these undesirable invasive species and maintain ecosystem services. Well‐timed management strategies, such as grazing, that are applied when invasive grasses are active prior to native plants can control invasive species spread and reduce their impact; however, anticipating the timing of key phenological stages that are susceptible to management over vast landscapes is difficult, as the phenology of these species can vary greatly over time and space. To address this challenge, we created range‐wide phenology forecasts for two problematic invasive annual grasses: cheatgrass (Bromus tectorum), and red brome (Bromus rubens). We tested a suite of 18 mechanistic phenology models using observations from monitoring experiments, volunteer science, herbarium records, timelapse camera imagery, and downscaled gridded climate data to identify the models that best predicted the dates of flowering and senescence of the two invasive grass species. We found that the timing of flowering and senescence of cheatgrass and red brome were best predicted by photothermal time models that had been adjusted for topography using gridded continuous heat‐insolation load index values. Phenology forecasts based on these models can help managers make decisions about when to schedule management actions such as grazing to reduce undesirable invasive grasses and promote forage production, quality, and biodiversity in grasslands; to predict the timing of greatest fire risk after annual grasses dry out; and to select remote sensing imagery to accurately map invasive grasses across topographic and latitudinal gradients. These phenology models also have the potential to be operationalized for within‐season or within‐year decision support.

Abstract Quantifying assemblage variation across environmental gradients provides insight into the ecological and evolutionary mechanisms that differentiate assemblages locally within a larger climate regime. We assessed how vascular plant functional composition and diversity varied across microenvironment to identify ecological differences in assemblages in a mountainous fieldsite in northeastern Utah, USA. Then, we looked at how life‐history strategies and information about phylogenetic differences affect the relationship between functional metrics and environment. We found less functionally dispersed assemblages that were shorter and more resource‐conservative on south‐facing slopes where intra‐annual soil temperature was hotter and more variable. In contrast, we found more functionally dispersed assemblages, that were taller and more resource‐acquisitive on north‐facing slopes where intra‐annual temperature was cooler and less variable. Herbaceous and woody perennials drove these trends. Additionally, including information about phylogenetic differences in a dispersion metric indicated that phylogeny accounts for traits we did not measure. At this fieldsite, soil temperature acts as an environmental filter across aspect. If soil temperature increases and becomes more variable, intra‐annually, the function of north‐ versus south‐facing assemblages may be at risk for contrasting reasons. On south‐facing slopes, assemblages may not have the variance in functional diversity needed to respond to more intense, stressful conditions. Conversely, assemblages on north‐facing slopes may not have the resource‐conservative strategies needed to persist if temperatures become hotter and more variable intra‐annually. Given these results, we advocate for the inclusion of aspect differentiation in studies seeking to understand species and assemblage shifts in response to changing climate conditions.

Abstract Background Recent calls to action highlight the need to address gaps in our understanding of survivorship for those living with advanced gynecological cancer to support optimal care. To ensure future research fills these knowledge gaps, we need to understand the breadth of existing survivorship research in this patient group, including the outcomes assessed, the populations included and the duration and retention in follow‐up. Methods We conducted a systematic scoping review searching PubMed, PsychINFO, and CINAHL during the month of November 2022 to identify prospective cohort studies measuring survivorship outcomes among participants with advanced (stage III–IV) gynecological cancer, or in cohorts in which ≥50% of participants had advanced cancer, or which provide results separately for patients with advanced cancer. Articles were screened, and data extracted using a standard form. Results We assessed 33 articles from 21 unique studies, which overall included 6023 participants with gynecological cancer. Of these, 45% had cervical cancer, 44% ovarian, 10% endometrial/uterine, and 1% vaginal/vulvar cancer. The most frequently measured survivorship outcome was quality of life. Of the 33 articles, most reported on participant age (n = 31), but relatively few reported on comorbidities (n = 10), physical status (n = 6), ethnic background (n = 4), the country of birth (n = 2), or the area of participant residence (n = 2). None included details on indigenous status. Recruitment proportions ranged from 48% to 100%. Retention proportions ranged from 15% to 97%. Conclusion Our findings highlight gaps in survivorship research for advanced gynecological cancers and emphasize the need for future studies to include and describe the experiences of diverse and underrepresented groups.

Abstract Wildlife species confront threats from climate and land use change, exacerbating the influence of extreme climatic events on populations and biodiversity. Migratory waterbirds are especially vulnerable to hydrological drought via reduced availability of surface water habitats. We assessed how whooping cranes (Grus americana) modified habitat use and migration strategies during drought to evaluate their resilience to changing conditions and adaptive capacity. We categorized >8000 night‐roost sites used by 146 cranes from 2010 to 2022 and examined relative use during non‐drought, moderate drought, and extreme drought conditions. We found cultivated and uncultivated palustrine and lacustrine wetlands were generally used less during droughts than non‐drought conditions. Conversely, impounded palustrine and lacustrine systems and rivers served more frequently as drought refugia (i.e., used more during drought than non‐drought conditions). Night roosts occurred primarily on private lands (86% overall); public land use decreased with latitude and increased with drought severity, with greatest use (56%) occurring during severe autumn drought in the southern Great Plains. Quantifying use of identified critical habitats in the United States indicated that Cheyenne Bottoms State Waterfowl Management Area and Quivira National Wildlife Refuge were used less during drought, and the Central Platte River and Salt Plains National Wildlife Refuge received similar use during drought compared to non‐drought conditions. Our findings provide insights into compensatory use of habitats, where impounded surface water may function in a complementary fashion with natural wetlands. Collectively, these and other types of wetlands distributed across the migration corridor provided a reliable network of habitat available across the Great Plains. A diversity of wetlands available during variable environmental conditions would be useful in supporting continued recovery of whooping cranes and likely have benefits for a wide array of migratory birds.

Abstract Effective habitat management for rare and endangered species requires a thorough understanding of their specific habitat requirements. Although machine learning models have been increasingly used in the analyses of habitat use by wildlife, the primary focus of these models has been on generating spatial predictions. In this study, we used machine learning models in combination with simulated management actions to guide planning and inform managers. We used data from 61 whooping cranes (Grus americana) tagged with GPS telemetry collars between 2009 and 2018 near Aransas National Wildlife Refuge in coastal Texas. We included variables based on topography, land use classification, vegetation height, plant phenology, drought, storm surge events, and both wild and prescribed fires. We then built models at multiple scales: population level, home range level, and roosting and daytime within home range level. We simulated responses to the two primary management actions used to enhance whooping crane habitat on Aransas National Wildlife Refuge: prescribed fire and removal of woody vegetation. At the population and home range scales, land use classification variables had the highest importance values, whereas the combined elevation and bathymetry layer was the most important predictor at both roosting and daytime within home range scales. Our findings revealed that the effects of fire, although generally modest, varied spatially. Areas dominated by estuarine wetlands exhibited higher predicted use within the first months after a fire, whereas those dominated by palustrine wetlands were more likely to be avoided in the immediate postfire years. Our simulation of vegetation removal identified the areas on Aransas National Wildlife Refuge where whooping cranes were predicted to benefit the most if vegetation were removed. These techniques can be used by other researchers wanting to examine and predict the effects of potential management actions on target species habitat.

Abstract Populations composed of individuals descended from multiple distinct genetic lineages often feature significant differences in phenotypic frequencies. We considered hatchery production of steelhead, the migratory anadromous form of the salmonid species Oncorhynchus mykiss, and investigated how differences among genetic lineages and environmental variation impacted life history traits. We genotyped 23,670 steelhead returning to the four California Central Valley hatcheries over 9 years from 2011 to 2019, confidently assigning parentage to 13,576 individuals to determine age and date of spawning and rates of iteroparity and repeat spawning within each year. We found steelhead from different genetic lineages showed significant differences in adult life history traits despite inhabiting similar environments. Differences between coastal and Central Valley steelhead lineages contributed to significant differences in age at return, timing of spawning, and rates of iteroparity among programs. In addition, adaptive genomic variation associated with life history development in this species varied among hatchery programs and was associated with the age of steelhead spawners only in the coastal lineage population. Environmental variation likely contributed to variations in phenotypic patterns observed over time, as our study period spanned both a marine heatwave and a serious drought in California. Our results highlight evidence of a strong genetic component underlying known phenotypic differences in life history traits between two steelhead lineages.

Abstract Prolonged water stress can shift rhizoplane microbial communities, yet whether plant phylogenetic relatedness or drought tolerance predicts microbial responses is poorly understood. To explore this question, eight members of the Streptanthus clade with varying affinity to serpentine soil were subjected to three watering regimes. Rhizoplane bacterial communities were characterized using 16S rRNA gene amplicon sequencing and we compared the impact of watering treatment, soil affinity, and plant species identity on bacterial alpha and diversity. We determined which taxa were enriched among drought treatments using DESeq2 and identified features of soil affinity using random forest analysis. We show that water stress has a greater impact on microbial community structure than soil affinity or plant identity, even within a genus. Drought reduced alpha diversity overall, but plant species did not strongly differentiate alpha diversity. Watering altered the relative abundance of bacterial genera within Proteobacteria, Firmicutes, Bacteroidetes, Planctomycetes, and Acidobacteria, which responded similarly in the rhizoplane of most plant species. In addition, bacterial communities were more similar when plants received less water. Pseudarthrobacter was identified as a feature of affinity to serpentine soil while Bradyrhizobium, Chitinophaga, Rhodanobacter, and Paenibacillus were features associated with affinity to nonserpentine soils among Streptanthus. The homogenizing effect of drought on microbial communities and the increasing prevalence of Gram‐negative bacteria across all plant species suggest that effects of water stress on root‐associated microbiome structure may be predictable among closely related plant species that inhabit very different soil environments. The functional implications of observed changes in microbiome composition remain to be studied.

Abstract Midcontinent sandhill cranes (Antigone canadensis) are managed as a single population, but hunting regulations are structured so harvest is targeted towards the more numerous lesser sandhill cranes (A. c. canadensis). However, research indicates that greater sandhill cranes (A. c. tabida) have been disproportionally exposed to harvest at a rate exceeding their proportion within the midcontinent population. In addition, harvest has increased 22% per year in the U.S. Central Flyway states. The midcontinent population appears to be growing in recent years, but variability in annual abundance estimates has increased substantially. With limited resources and harvest management uncertainty increasing, we developed methods for a citizen science, photography‐based harvest survey to estimate age and subspecies composition of harvested midcontinent sandhill cranes. To develop survey methods, we collected physical parts from 284 sandhill cranes in North Dakota in 2019 and 2020. We manually measured the culmen and tarsus using calipers, and digitally measured these parts using photographs and computer software. All digitally derived measurements were 2.5% to 5.9% larger than manual measurements; therefore, we developed linear models that adjusted digital measurements, facilitating subspecies prediction using an existing morphometric‐based technique. In 2021, we requested an equal number of hunters to participate using 2 data collection methods to test if hunters could reliably take photographs suitable for digital measurement. Collection method 1 involved photographing the head and leg simultaneously, and Collection method 2 involved photographing the head only. Hunters submitted a total of 239 photographs. Only 80 of these photographs were submitted using Collection method 1, and 72% were suitable for digital measurement. Conversely, hunters submitted twice as many photographs using Collection method 2, and 88% of these photographs were deemed suitable. Although obtaining the tarsus measurement slightly improved subspecies predictability, Collection method 2 increased participation and usable data. We believe our results could be used to develop an operational survey of age and subspecies composition of midcontinent sandhill cranes, wherein a sample of crane hunters throughout the midcontinent population range would be asked to electronically submit a photograph of the head of each bird they harvest. A time series of age and subspecies composition of this population would provide managers with valuable information and improve harvest management at minimal additional cost and burden, compared to a traditional parts collection survey administered by mail.

Abstract Annual phenology and distributions of migratory wildlife have been noticeably influenced by climate change, leading to concerns about sustainable populations. Recent studies exploring conditions influencing autumn migration departure have provided conflicting insights regarding factors influencing the movements of Mallards (Anas platyrhynchos), a popular game species. We determined factors affecting timing and magnitude of long‐distance movements of 97 juvenile Mallards during autumn‐winter across the midcontinent of North America marked with implanted transmitters in North and South Dakota, 2018–2019. Factors influencing variation in movement timing, along with direction and magnitudes, depended on type of movement (i.e., regional [25–310 km], initial migration, or subsequent migration movements [>310 km]). Photoperiod influenced probability of initiating all movements, although the effect was most influential for regional movements. Minimum temperature most influenced initial migration events (probability of movement increased 29% for each 1°C decrease); favorable winds also increased likelihood of initial migration events. Probability of subsequent migration events increased 80% for each 1 cm increase in depth of snow. Subsequent migration movements also were 2.0 times more likely to occur on weekend days, indicating disturbance from humans may influence movements. Migration distances increased 166 km for each 1°C reduction in minimum temperature. We also observed markedly different autumn‐winter distributions of marked birds between years. Median locations during autumn‐winter 2018–2019 were ~250 km farther north and ~300 km farther west during mid‐December–January compared to the same time in 2019–2020. Concurrently, harvest rates for marked females and males were 10% and 26% during autumn‐winter 2018–2019 and 26% and 31% during autumn‐winter 2019–2020. Climate‐related changes may result in increasingly variable autumn‐winter distributions, with implications for wildlife recreationalists, conservation planners, and harvest managers.

Abstract Nest survival has been identified as one of the most influential vital rates causing population change in game birds, and depredation, often influenced by habitat loss and fragmentation, is the primary cause of nest failure of upland game birds. We were interested in quantifying and comparing the perspectives of landowners and biologists in South Dakota regarding complex predator‐prey interactions to improve communication and management efficacy. We developed a questionnaire regarding the following: 1) general attitude statements about game bird species; 2) perceived impacts of 9 factors (e.g., development, pollution, predators) and 13 potential predators on game bird abundances; and 3) attitude statements regarding use of lethal predator control and nesting habitat management practices. A cluster analysis using landowner attitude statements about predator management identified 3 landowner segments that had strong (most supportive; 37%), moderate (moderately supportive; 35%), or weak (least supportive; 28%) attitude statements about lethal predator control. Landowner segments most supportive and moderately supportive of predator control rated predators as the primary negative factor impacting game bird abundances and agreed that predators were the primary cause of game bird abundance declines, whereas the landowner segment least supportive of predator control rated habitat loss as the top factor and disagreed that predators were the primary cause of game bird declines. Biologists rated habitat loss as the top factor negatively impacting game bird abundances and disagreed that predators were the primary cause of game bird abundance declines. Thus, when considering the effectiveness of strategies to reduce nest depredation, most landowners focused on the direct cause of nest failures (predators), whereas biologists focused on an indirect cause (habitat loss). Perception differences among these groups emphasizes the need for better communication on proximate and ultimate factors affecting game bird populations and how these differences may impact management decisions.

Abstract Traits have become a crucial part of ecological and evolutionary sciences, helping researchers understand the function of an organism's morphology, physiology, growth and life history, with effects on fitness, behaviour, interactions with the environment and ecosystem processes. However, measuring, compiling and analysing trait data comes with data‐scientific challenges. We offer 10 (mostly) simple rules, with some detailed extensions, as a guide in making critical decisions that consider the entire life cycle of trait data. This article is particularly motivated by its last rule, that is, to propagate good practice. It has the intention of bringing awareness of how data on the traits of organisms can be collected and managed for reuse by the research community. Trait observations are relevant to a broad interdisciplinary community of field biologists, synthesis ecologists, evolutionary biologists, computer scientists and database managers. We hope these basic guidelines can be useful as a starter for active communication in disseminating such integrative knowledge and in how to make trait data future‐proof. We invite the scientific community to participate in this effort at http://opentraits.org/best‐practices.html.

Abstract Artificial intelligence (AI)‐based diagnostic algorithms have achieved ambitious aims through automated image pattern recognition. For neurological disorders, this includes neurodegeneration and inflammation. Scalable imaging technology for big data in neurology is optical coherence tomography (OCT). We highlight that OCT changes observed in the retina, as a window to the brain, are small, requiring rigorous quality control pipelines. There are existing tools for this purpose. Firstly, there are human‐led validated consensus quality control criteria (OSCAR‐IB) for OCT. Secondly, these criteria are embedded into OCT reporting guidelines (APOSTEL). The use of the described annotation of failed OCT scans advances machine learning. This is illustrated through the present review of the advantages and disadvantages of AI‐based applications to OCT data. The neurological conditions reviewed here for the use of big data include Alzheimer disease, stroke, multiple sclerosis (MS), Parkinson disease, and epilepsy. It is noted that while big data is relevant for AI, ownership is complex. For this reason, we also reached out to involve representatives from patient organizations and the public domain in addition to clinical and research centers. The evidence reviewed can be grouped in a five‐point expansion of the OSCAR‐IB criteria to embrace AI (OSCAR‐AI). The review concludes by specific recommendations on how this can be achieved practically and in compliance with existing guidelines.

Abstract In neurodegenerative diseases, extracellular vesicles (EVs) transfer pathogenic molecules and are consequently involved in disease progression. We have investigated the proteomic profiles of EVs that were isolated from four different human‐induced pluripotent stem cell‐derived neural cell types (excitatory neurons, astrocytes, microglia‐like cells, and oligodendrocyte‐like cells). Novel cell type‐specific EV protein markers were then identified for the excitatory neurons (ATP1A3, NCAM1), astrocytes (LRP1, ITGA6), microglia‐like cells (ITGAM, LCP1), and oligodendrocyte‐like cells (LAMP2, FTH1), as well as 16 pan‐EV marker candidates, including integrins and annexins. To further demonstrate how cell‐type‐specific EVs may be involved in Alzheimer's disease (AD), we performed protein co‐expression network analysis and conducted cell type assessments for the proteomes of brain‐derived EVs from the control, mild cognitive impairment, and AD cases. A protein module enriched in astrocyte‐specific EV markers was most significantly associated with the AD pathology and cognitive impairment, suggesting an important role in AD progression. The hub protein from this module, integrin‐β1 (ITGB1), was found to be significantly elevated in astrocyte‐specific EVs enriched from the total brain‐derived AD EVs and associated with the brain β‐amyloid and tau load in independent cohorts. Thus, our study provides a featured framework and rich resource for the future analyses of EV functions in neurodegenerative diseases in a cell type‐specific manner.

Abstract Functional traits mediate species' responses to, and roles within, their environment and are constrained by evolutionary history. While we have a strong understanding of trait evolution for macro‐taxa such as birds and mammals, our understanding of invertebrates is comparatively limited. Here, we address this gap in North American beetles with a sample of ground beetles (Carabidae), leveraging a large‐scale collection and digitization effort by the National Ecological Observatory Network (NEON). For 154 ground beetle species, we measured seven morphological traits, which we placed into a recently developed effect–response framework that characterizes traits by how they predict species' effects on their ecosystems or responses to environmental stressors. We then used cytochrome oxidase 1 sequences from the same specimens to generate a phylogeny and tested the evolutionary tempo and mode of the traits. We found strong phylogenetic signal in, and correlations among, ground beetle morphological traits. These results indicate that, for these species, beetle body shape trait evolution is constrained, and phylogenetic inertia is a stronger driver of beetle traits than (recent) environmental responses. Strong correlations among effect and response traits suggest that future environmental drivers are likely to affect both ecological composition and functioning in these beetles.

Abstract Land degradation is a leading cause of biodiversity loss, and understanding its consequences on freshwater ecosystems remains a priority for improving the effectiveness of restoration practices and ecosystem assessments. Freshwater monitoring programs use macroinvertebrates to assess the biotic effects of degradation and management actions, often using the ratio of observed to expected taxa at a site—O/E—for this purpose. Despite the power of the O/E approach, large amounts of data are required to generate an expectation and it can be difficult to define a threshold value for degraded sites. An alternative assessment tool is phylogenetic diversity, which is widely used in academic biology but rarely applied in management despite empirical correlations between phylogenetic diversity and management targets such as ecosystem structure and function. Here, we use macroinvertebrate data from 1400 watersheds, collected since 1998, to evaluate the potential for phylogenetic metrics to inform evaluations of management practices. These watersheds were chosen because their low disturbance levels and high habitat heterogeneity have made them problematic to assess with O/E. Phylogenetic diversity detected degradation of assemblages and was sensitive enough to parse impacts to inform management actions. This is particularly notable given the phylogenetic metrics, unlike O/E, did not require additional “baseline” data. Site disturbance and broader environmental drivers strongly predicted site phylogenetic structure, providing management objectives to increase site quality. We call on others to consider using phylogenetic diversity to complement existing O/E schemes, particularly in systems where O/E is insufficient to prioritize management objectives.