Disparate Sources Of Information Research Articles

Rare and common variants associated with alcohol consumption identify a conserved molecular network.

Genome-wide association studies (GWAS) have identified hundreds of common variants associated with alcohol consumption. In contrast, genetic studies of alcohol consumption that use rare variants are still in their early stages. No prior studies of alcohol consumption have examined whether common and rare variants implicate the same genes and molecular networks, leaving open the possibility that the two approaches might identify distinct biology. To address this knowledge gap, we used publicly available alcohol consumption GWAS summary statistics (GSCAN, N = 666,978) and whole exome sequencing data (Genebass, N = 393,099) to identify a set of common and rare variants for alcohol consumption. We used gene-based analysis to implicate genes from common and rare variant analyses, which we then propagated onto a shared molecular network using a network colocalization procedure. Gene-based analysis of each dataset implicated 294 (common variants) and 35 (rare variants) genes, including ethanol metabolizing genes ADH1B and ADH1C, which were identified by both analyses, and ANKRD12, GIGYF1, KIF21B, and STK31, which were identified in only the rare variant analysis, but have been associated with other neuropsychiatric traits. Network colocalization revealed significant network overlap between the genes identified via common and rare variants. The shared network identified gene families that function in alcohol metabolism, including ADH, ALDH, CYP, and UGT. Seventy-one of the genes in the shared network were previously implicated in neuropsychiatric or substance use disorders but not alcohol-related behaviors (e.g. EXOC2, EPM2A, and CACNG4). Differential gene expression analysis showed enrichment in the liver and several brain regions. Genes implicated by network colocalization identify shared biology relevant to alcohol consumption, which also underlie neuropsychiatric traits and substance use disorders that are comorbid with alcohol use, providing a more holistic understanding of two disparate sources of genetic information.

Open Science News Informing System for Scientific Libraries

The purpose of the study is to theoretically and practically substantiate the need to introduce an online news information system into library practice as part of the information support of scientific activities (on the example of Open Science). The work theoretically substantiates that improving the news information system in libraries is necessary in connection with the development of technology, open science, library activities and the rapid growth of disparate sources of information. The experience analysis of 130 libraries in presenting various news information products has led to the conclusion that the implementation of news information requires appropriate technology that would allow us to model the sequence of processes and operations for generating news library and information products.As a result the model of a news information system on open science is developed, which allows searching, collecting, processing, and synthesizing news information on open science, as well as creating, posting and distributing information products, their qualitative and quantitative assessment of effectiveness to be made. It has been implemented on the web platform of the State Public Library for Science and Technology of the Siberian Branch of RAS “Library for Open Science” in January 2023 and demonstrates a gradual increase in the number of all web analytical indicators of news information products created on its basis.

An open-source system for efficient clinical trial support: The COMET study experience.

Exercise clinical trials are complex, logistically burdensome, and require a well-coordinated multi-disciplinary approach. Challenges include managing, curating, and reporting on many disparate information sources, while remaining responsive to a variety of stakeholders. The Combined Exercise Trial (COMET, NCT04848038) is a one-year comparison of three exercise modalities delivered in the community. Target enrollment is 280 individuals over 4 years. To support rigorous execution of COMET, the study team has developed a suite of scripts and dashboards to assist study stakeholders in each of their various functions. The result is a highly automated study system that preserves rigor, increases communication, and reduces staff burden. This manuscript describes system considerations and the COMET approach to data management and use, with a goal of encouraging further development and adaptation by other study teams in various fields.

تحسين جودة القصص الإلكترونية المستخدمة في مناهج رياض الأطفال

The scientific change that the current era is witnessing in the field of informatics and informational development and the implications of that progress in all branches of knowledge imposed new variables that affected all aspects of life, and changed many of its patterns and methods to which society must respond. The future requires people with multiple abilities and skills to be able to communicate with others and interact with the changes of the times through advanced modern technical means until it reaches e-learning, which has become an urgent necessity through which the future is predicted. E-learning aims to provide multiple and disparate sources of information that provide opportunities for comparison, discussion, analysis, and evaluation using electronic media in linking and interacting with the educational system while providing the opportunity for learners to interact instantly electronically with each other on one hand, and between them and the teacher on the other hand through modern technological resources/media. The problem with the research is that the institutions that produce the electronic stories for the kindergarten stage do not adhere to the standards necessary to produce these stories for the kindergarten stage. Therefore, the importance of the research stands out in developing a proposed model for the design and production standards of the electronic story for the kindergarten stage.

ОСНОВНЫЕ ПРИНЦИПЫ ЭКОСИСТЕМНОГО УЧЕТА

Due to the growing attention of society to the conservation of natural capital and ecosystem services, ecosystem accounting is becoming a significant tool for achieving sustainable development goals both at the national and international levels. Environmental accounting improves the way natural capital and ecosystem services are identified and valued. The System of Environmental-Economic Accounting is an international standard accounting developed by the United Nations. The ecosystem accounting system generates environmental and economic reports necessary for effective management decisions and external disclosure of environmental information. The possibility of environmental accounting lies in the development of systems that integrate information rather than create disconnected, discrete repositories of information. With the introduction of an ecosystem accounting system, it is possible to jointly review and compare disparate sources of information reflecting the state of natural capital and ecosystem services. The introduction of a system of ecosystem accounting contributes to the achievement of sustainable development goals. The result of the implementation of the eco-system accounting system is a decision support system. The author proposes to consider the system of environmental-ecosystem accounting as a reliable and effective platform for providing more complete information on the availability and sufficiency of certain types of ecosystem services and natural capital.

Mid-Late Quaternary Fluvial Archives near the Margin of the MIS 12 Glaciation in Southern East Anglia, UK: Amalgamation of Multi-Disciplinary and Citizen-Science Data Sources

This paper presents an updated geological reconstruction of the Quaternary evolution of the River Thames at its downstream extremities, close to the North Sea coast, based on new data from multi-disciplinary and citizen-science sources. In this area, the interaction of the Thames with the MIS 12 (Anglian) glaciation is an important part of the Quaternary archive. The Anglian ice sheet, which reached parts of north and east London, was responsible for diverting the Thames southwards into its present course, although the footprint of the maximum ice sheet(s) does not reach the North Sea coast south of Hollesley, Suffolk. Further south, the coastal zone hosts pre-Anglian and early Anglian river-terrace deposits of the pre-diversion Thames system, superimposed upon which are products of later post-Anglian rivers, of both Middle and Late Pleistocene age. On the peninsula between the Stour and Blackwater–Colne estuaries, the lowest and most recent terrace of the pre-diversion Thames includes evidence directly pertaining to the glacial disruption event, for which geochronological data are reported here for the first time. The first post-diversion terrace of the Thames also reaches this peninsula, the river having essentially re-joined its original valley before crossing the alignment of the modern coastline. This terrace passes beneath Clacton-on-Sea, where it includes the type locality of the Clactonian Palaeolithic Industry. The area of interest to this paper, in NE Essex and southern Suffolk, includes a number of interglacial and Palaeolithic sites, the data from which assist in constraining the chronostratigraphy of the sequence. In some cases, there has been uncertainty as to whether these sites represent pre-Anglian environments and hominin occupations, part of the palaeo-Thames sequence, or whether they are the product of later post-Anglian streams, formed after the Thames had migrated southwards. This paper compiles evidence from a wide range of recent sources, including developer-funded archaeological appraisal and citizen-science activities, to explore and update the evidence from sites at Ipswich, Upper Dovercourt and Thorpe-le-Soken, as well as a number of localities associated with the Clacton Channel Deposits (host to the type-Clactonian), amongst others. The resulting new data are placed within the wider context of the Quaternary fluvial archives in southern Britain, with a discussion of how disparate sources of information, including the work of citizen scientists, have contributed.

Integration of Patient-Reported Outcome Measures in the Electronic Health Record: The Veterans Affairs Experience.

There are growing efforts to integrate patient-reported outcome (PRO) data into electronic health records (EHRs) to bring together disparate sources of patient information and improve medical care. PRO measures can be used to assess cancer symptom presence and severity. Integrating PRO tools in EHRs can alert providers to address symptoms, which is an essential component of comprehensive oncology care. We modified a PRO used to measure cancer and end-of-life symptoms, the Edmonton Symptom Assessment System to create the Veteran Symptom Assessment System (VSAS). VSAS was implemented as an integrated PRO as part of the Veterans Administration EHR system and was used at hematology-oncology clinics in Veteran Administration (VA) medical centers in the Southeast. From 2013 to 2014, VSAS was introduced, underwent usability testing and modifications, and was finally implemented in the EHR. Between 2015 and 2019, VSAS was administered 43,883 times in 9,058 patients. Eighty-nine percent of Veterans were male, 11% were female, 52% identified as non-Hispanic White, and 43% identified as African American. Fatigue, shortness of breath with exertion, and pain were most frequently reported initially (68%, 48%, and 45%, respectively) and were most frequently rated as severe (27%, 16%, and 17%, respectively). In patients diagnosed with stage IV cancer, higher symptom burden was significantly associated with shorter overall survival. The majority of Veterans with longitudinal measurements experienced improvement in symptoms, most frequently in severe symptoms. To our knowledge, this is the first large-scale implementation of a PRO system, integrated in the VA EHR, in ambulatory patients with cancer and blood disorders. The integration of VSAS within the VA EHR is a significant demonstration and a necessary requirement for current and future systemic initiatives in cancer symptom management.

Performing Information Extraction and Ontology Development for Mission Engineering Applications

The development and evaluation of Mission Engineering Threads (METs) require an understanding of the operational context for which a system-of-systems (SoS) will be employed as well as an assessment that the performance of a complex SoS is effective and safe. The information describing the design and performance parameters of the systems within the SoS is distributed in many different physical locations, and is represented in a variety of formats, both structured and unstructured. Because of this dynamic on the structuring of the data to include differing ontology frameworks, it is necessary to develop a framework and toolset to handle the automated extraction of information from disparate information sources. In addition, this extracted information needs to be categorized properly into defined data types as represented in the specific MET to correctly capture the appropriate context of the mission scenario. Semantic technique solutions will be researched, analysed, and applied as a means to infer new facts from existing facts and data. These techniques are particularly powerful when the amount of data and/or the relationships and constraints among data are too cumbersome and complex for human understanding and reasoning. Using the characteristics of wine as an example, we present our framework to show how it enables rapid and contextually relevant extraction, and represents complex information in a user-friendly format.

Patient Perspectives Surrounding Intraarticular Injections for Knee Osteoarthritis: A Qualitative Study.

Intraarticular (IA) injections are used frequently for knee osteoarthritis (OA), but little is known about patients' attitudes toward these therapies. We aimed to better understand patients' perceptions of the facilitators of and barriers to IA injections for knee OA. We conducted a qualitative, descriptive, exploratory study and held focus groups and individual interviews with participants with knee OA, including some who had and some who had not received IA injections. We conducted a thematic analysis to identify themes describing the factors that participants found influential when deciding whether to try an IA injection. We held 3 focus groups with 12 participants and conducted 3 individual interviews (15 participants total). We identified the following 4 themes that shaped participants' decisions to receive a specific injection: 1) the impact of OA on participants' lives; 2) participants' attitudes and concerns, including desire to avoid surgery, willingness to accept uncertain outcomes, and concerns about side effects and dependence; 3) the way participants gathered and processed information from physicians, peers, and the internet; and 4) the availability of injectable products. Participants weighed the desire to regain function and delay surgery with concerns about side effects, uncertain efficacy, and costs. Participants were concerned about the effectiveness, toxicity, availability, and cost of injectable products. They balanced disparate sources of information, uncertain outcomes, limited product availability, and other injection-related concerns with a desire to decrease pain. These findings can provide clinicians, investigators, and public health professionals with insights into challenges that patients face when making injection decisions.

Machine learning for perturbational single-cell omics.

Cell biology is fundamentally limited in its ability to collect complete data on cellular phenotypes and the wide range of responses to perturbation. Areas such as computer vision and speech recognition have addressed this problem of characterizing unseen or unlabeled conditions with the combined advances of big data, deep learning, and computing resources in the past 5 years. Similarly, recent advances in machine learning approaches enabled by single-cell data start to address prediction tasks in perturbation response modeling. We first define objectives in learning perturbation response in single-cell omics; survey existing approaches, resources, and datasets (https://github.com/theislab/sc-pert); and discuss how a perturbation atlas can enable deep learning models to construct an informative perturbation latent space. We then examine future avenues toward more powerful and explainable modeling using deep neural networks, which enable the integration of disparate information sources and an understanding of heterogeneous, complex, and unseen systems.

Activity strategy and pattern of the Siberian jerboa (Orientallactaga sibirica) in the Alxa desert region, China.

Rodents exhibit seasonal changes in their activity patterns as an essential survival strategy. We studied the activity patterns and strategies of the Siberian jerboa (Orientallactaga sibirica) in the Alxa desert region to better understand the habitats and behavioural ecology of xeric rodents. We conducted an experiment using three plots to monitor the duration, time, and frequency of the active period of the Siberian jerboa using infrared cameras in the Alxa field workstation, Inner Mongolia, China in 2017. The relationships between the activity time and frequency, biological factors (perceived predation risk, food resources, and species composition), and abiotic factors (temperature, air moisture, wind speed) were analysed using Redundancy Analysis (RDA). Our results showed that: (1) relative humidity mainly affected activities in the springtime; temperature, relative humidity and interspecific competition mainly affected activities in the summertime; relative humidity and perceived predation risk mainly influenced activities in the autumn. (2) The activity pattern of the Siberian jerboa altered depending on the season. The activity of the Siberian jerboa was found to be bimodal in spring and summer, and was trimodal in autumn. The activity time and frequency in autumn were significantly lower than the spring. (3) Animals possess the ability to integrate disparate sources of information about danger to optimize energy gain. The jerboa adapted different responses to predation risks and competition in different seasons according to the demand for food resources.

Complexity of Documentation Needs for Children With Medical Complexity: Implications for Hospital Providers.

Care coordination is a core component of pediatric complex care programs (CCPs) supporting children with medical complexity (CMC) and their families. In this study, we aim to describe the purpose and characteristics of clinical care notes used within a pediatric CCP. We conducted observations of provider-family interactions during CCP clinic visits and 5 focus groups with members of the CCP. Focus groups were recorded and transcribed. Field observation notes and focus group transcripts were subjected to qualitative content analyses. Four major themes help characterize clinical care notes: (1) Diversity of note types and functions: program staff author and use a number of unique note types shared across multiple stakeholders, including clinicians, families, and payers. (2) motivations for care note generation are different and explain how, why, and where they are created. (3) Program staff roles and configuration vary in relation to care note creation and use. (4) Sources of information for creating and updating notes are also diverse. Given the disparate information sources, integrating and maintaining up-to-date information for the child is challenging. To minimize information gaps, program staff devised unique but resource-intensive strategies, such as accompanying families during specialty clinic visits or visiting them inpatient. CMC have complex documentation needs demonstrated by a variety of professional roles, care settings, and stakeholders involved in the generation and use of notes. Multiple opportunities exist to redesign and streamline the existing notes to support the cognitive work of clinicians providing care for CMC.

The role of default mode network in semantic cue integration

Recent accounts of large-scale cortical organisation suggest that the default mode network (DMN) is positioned at the top of a principal gradient, reflecting the separation between heteromodal and unimodal sensory-motor regions in patterns of connectivity and in geodesic distance along the cortical surface (Margulies et al., 2016). This isolation of DMN from external inputs might allow the integration of disparate sources of information that can constrain subsequent cognition. We tested this hypothesis by manipulating the degree to which semantic decisions for ambiguous words (e.g. jam) were constrained by preceding visual cues depicting relevant spatial contexts (e.g. supermarket or road) and/or facial emotions (e.g. happy vs. frustrated). We contrasted (i) the effects of a single preceding cue with a no-cue condition employing scrambled images, and (ii) convergent spatial and emotion cues with single cues. Single cues elicited stronger activation in the multiple demand network relative to no cues, consistent with the requirement to maintain information in working memory. The availability of two convergent cues elicited stronger activation within DMN regions (bilateral angular gyrus, middle temporal gyrus, medial prefrontal cortex, and posterior cingulate), even though behavioural performance was unchanged by cueing – consequently task difficulty is unlikely to account for the observed differences in brain activation. A regions-of-interest analysis along the unimodal-to-heteromodal principal gradient revealed maximal activation for the convergent cue condition at the heteromodal end, corresponding to the DMN. Our findings are consistent with the view that regions of DMN support states of information integration that constrain ongoing cognition and provide a framework for understanding the location of these effects at the heteromodal end of the principal gradient.

E-Dictionaries in a Network of Information Tools in the e-Environment

Traditional dictionaries offer curated data to users. Users should therefore be able to find the correct data to solve their information need. However, users don't necessarily know the exact scope of lexicographic information. Dictionary articles can still demand considerable interpretation by the user to select the appropriate meaning or equivalent. In the e-environment, users can easily navigate between different e-sources. This is especially evident on various e-book platforms, where one can link multiple dictionaries and other sources to a text or search of the internet. Internet content is obviously not curated, and providing access to such data is therefore anathema to the traditional lexicographer. A traditional dictionary is the result of an application of data pushing procedures. The online environment enables the use of data pulling procedures that give users access to both curated and non-curated data. These issues are illustrated by means of a number of examples that show that a large number of different and disparate information sources are easily available to the user to satisfy any specific information need, and that the dictionary is one of a plethora of information sources. The information is therefore available on demand, without risking information overload. It is argued that, when optimising a network of information tools that constitutes a comprehensive search universe, the information retrieval structure should preferably have a circular network as application domain, rather than a linear continuum.

Thinking like a naturalist: Enhancing computer vision of citizen science images by harnessing contextual data

Abstract The accurate identification of species in images submitted by citizen scientists is currently a bottleneck for many data uses. Machine learning tools offer the potential to provide rapid, objective and scalable species identification for the benefit of many aspects of ecological science. Currently, most approaches only make use of image pixel data for classification. However, an experienced naturalist would also use a wide variety of contextual information such as the location and date of recording. Here, we examine the automated identification of ladybird (Coccinellidae) records from the British Isles submitted to the UK Ladybird Survey, a volunteer‐led mass participation recording scheme. Each image is associated with metadata; a date, location and recorder ID, which can be cross‐referenced with other data sources to determine local weather at the time of recording, habitat types and the experience of the observer. We built multi‐input neural network models that synthesize metadata and images to identify records to species level. We show that machine learning models can effectively harness contextual information to improve the interpretation of images. Against an image‐only baseline of 48.2%, we observe a 9.1 percentage‐point improvement in top‐1 accuracy with a multi‐input model compared to only a 3.6% increase when using an ensemble of image and metadata models. This suggests that contextual data are being used to interpret an image, beyond just providing a prior expectation. We show that our neural network models appear to be utilizing similar pieces of evidence as human naturalists to make identifications. Metadata is a key tool for human naturalists. We show it can also be harnessed by computer vision systems. Contextualization offers considerable extra information, particularly for challenging species, even within small and relatively homogeneous areas such as the British Isles. Although complex relationships between disparate sources of information can be profitably interpreted by simple neural network architectures, there is likely considerable room for further progress. Contextualizing images has the potential to lead to a step change in the accuracy of automated identification tools, with considerable benefits for large‐scale verification of submitted records.

The role of historical sources in the restoration of Long Swamp, Discovery Bay, Victoria

Inspired by the success of restoration efforts in the adjacent Piccaninnie Ponds Karst Wetlands Ramsar site, the local community was anxious for progress to address observed changes to the hydrology of Long Swamp, near Nelson, Victoria. Uncertainty about the original character and condition of the wetland system required deep exploration of a vast range of historical reference material. This is a story of how disparate sources of historical information can complement modern scientific methods, help resolve contentious issues and contribute to refining reference ecosystem models to improve restoration outcomes.Long Swamp from Oxbow Lake (A) to Lake Momboeng (B), showing the Glenelg River Mouth (1) and ocean outlet locations at White Sands (2) and Nobles Rocks (3). The hypothesised original main direction of surface flows was from east to west (from B to A). N = north.image

Multifidelity Data Fusion: Application to Blended-Wing-Body Multidisciplinary Analysis Under Uncertainty

This paper presents a methodology to support improved decision making and identification of risks in early stage multidisciplinary design. The approach fuses multifidelity data from disparate information sources available to designers, such as disciplinary simulations, experiments, and operational data from previously deployed systems. The multifidelity data fusion is achieved using a fidelity-weighted combination of Gaussian process surrogate models. This weighting takes into account both the quality of the Gaussian process approximation and the designer’s confidence in the underlying information source being approximated. The resulting multifidelity surrogate provides a rapid analysis capability, which in turn enables the high number of evaluations needed to conduct multidisciplinary trade studies and to propagate uncertainty to the overall system level. The methodology is broadly applicable across engineering design problems where multiple information sources are available to support design decisions. In this paper, the approach is demonstrated on the stability and control analysis of a Blended-Wing-Body aircraft’s center-of-gravity limits, considering the longitudinal criteria of fly-to-stall, stall recovery, nose-wheel steering, and nose-wheel liftoff. The results show that low-fidelity models are enhanced by the presence of higher-fidelity data in key areas of the design space. The presence of even sparse high-fidelity data is key to reducing the variance in the overall analysis, thereby improving the quality of the predictions needed to inform early stage design decisions.

Information gerrymandering and undemocratic decisions.

People must integrate disparate sources of information when making decisions, especially in social contexts. But information does not always flow freely. It can be constrained by social networks1-3 and distorted by zealots and automated bots4. Here we develop a voter game as a model system to study information flow in collective decisions. Players are assigned to competing groups (parties) and placed on an 'influence network' that determines whose voting intentions each player can observe. Players are incentivized to vote according to partisan interest, but also to coordinate their vote with the entire group. Our mathematical analysis uncovers a phenomenon that we call information gerrymandering: the structure of the influence network can sway the vote outcome towards one party, even when both parties have equal sizes and each player has the same influence. A small number of zealots, when strategically placed on the influence network, can also induce information gerrymandering and thereby bias vote outcomes. We confirm the predicted effects of information gerrymandering in social network experiments with n=2,520 human subjects. Furthermore, we identify extensive information gerrymandering in real-world influence networks, including online political discussions leading up to the US federal elections, and in historical patterns of bill co-sponsorship in the US Congress and European legislatures. Our analysis provides an account of the vulnerabilities of collective decision-making to systematic distortion by restricted information flow. Our analysis also highlights a group-level social dilemma: information gerrymandering can enable one party to sway decisions in its favour, but when multiple parties engage in gerrymandering the group loses its ability to reach consensus and remains trapped in deadlock.

We Can('t) Get There From Here: Aligning local to global efforts for realizing a biodiversity data commons

The last 250 years of biodiversity research have produced a wealth of information on the natural world. First locked up in museum drawers or printed publications, in isolated desktop computers or in incompatible digital formats, and in multiple human languages, an increasing proportion is now digitally accessible, thanks to a number of organisational, institutional, and regional digitisation initiatives. These are creating new repositories of open data supporting a wealth of research, much of which has become possible thanks to the digital aggregation of disparate sources of information. Despite this growth of digital content, there is a growing realisation that these initiatives alone are insufficient and inadequate to address global community needs and expectations (Hardisty et al. 2013, Hobern et al. 2019). To move the community forward, we propose a coordinated Commons for Biodiversity. Based on a landscape analysis of relevant infrastructures and more than twenty years of combined experience from two major initiatives (Integrated Digitized Biocollections [iDigBio] in the US and Synthesis of Systematic Resources [SYNTHESYS] in Europe), which suggest that while more data is being mobilized, our activities are creating larger data silos without cross-linkages between different categories of data necessary to fully exploit research opportunities. This highlights the need for more consolidation and alignment, with greater cross-linkage between data types supported by greater standardisation and agreed identifier strategies. Better coordination (e.g., of communication and education, to partition effort) of our communities' activities at various levels (publisher, collection, individual, and in software) would also promote more efficient use of organisational resources. We argue that this is only possible through greater international coordination, and will enable us to deliver on the major scientific opportunities from these data, such as the provision of a complete and accurate data on the world's species or predicting changing patterns and trends in biodiversity. Adopting a shared vision at this level requires coordination mechanisms that we do not currently have and that transcend our normal regional activities. This "Biodiversity Commons" inspired by similar movements, is closely aligned with recent proposals to form a new alliance for biodiversity knowledge, the One-World Collection project, and the European Distributed System of Scientific Collections (DiSSCo). Coalescing these and related efforts, while engaging a broader set of stakeholders, is likely to be the next step toward realising a Common's movement for the biodiversity community. In this presentation, we outline specific challenges and highlight possible solutions to help align our global efforts. These include bottom-up activities such as 1) sharing data visualisation and metrics of use to build a coordinated business case for collections data mobilisation; 2) the sharing of authority file resources to improve data quality and speed of data mobilisation; 3) the need for open fora supporting comment on vision, decisions and actions; as well as more top-down efforts such as 4) increasing international diversity and participation across the global museum community; 5) creating models of participation that include groups, individuals, and institutions varying in size, scope, and resources; 6) capacity enhancement activities such as the development of techniques for more cross-institutional infrastructure development; and 7) policy-level alignment to harmonise our operational activities (e.g. data citation and attribution), which are inclusive of more and varied stakeholders.

Conspecific presence and microhabitat features influence foraging decisions across ontogeny in a facultatively social mammal

Natural selection is expected to favor the evolution of threat-sensitive behaviors that permit individuals to adaptively detect and respond to danger. However, because time allocated to vigilance reduces the amount of time that is available for energy acquisition, foraging in the face of predation can impose an evolutionary trade-off. Optimal foraging theory therefore predicts that risk-taking decisions should vary in response to perceived levels of threat. Our goal here is to disentangle the relative contributions of conspecific presence, ecological factors, and individual traits on two measures of vigilance in free-living California ground squirrels (Otospermophilus beecheyi). This facultatively social and ecologically flexible rodent represents a major source of prey in California grasslands. Over a 5-year period, we collected 386 focal animal surveys on 156 free-living individuals residing at two colony sites. Individuals were most vigilant in conditions for which predation risk was highest, such as when foraging alone and on flat areas with low vegetative cover. In general, juvenile foragers were more gregarious but less vigilant than adult foragers. Although all animals—regardless of age or sex—generally decreased their intensity of vigilance as group size increased, only adults decreased their time allocated to vigilance in response to conspecific presence. Thus, grouping consistently buffered the costs of foraging for risk-averse adults, but the benefits of conspecific presence were less salient for juveniles. Taken together, our findings highlight the importance of context in shaping foraging decisions and offer insights into the suite of factors mediating decision-making in socially and ecologically variable environments. Animals face trade-offs when foraging in the face of predation, but the capacity for individuals to respond appropriately to subtle changes in context-dependent threats remains poorly understood. We studied antipredator vigilance by the California ground squirrel, a flexible species that may forage alone or in small groups of various sizes and in habitats that vary in their protective value from predators and the ease at which prey may detect predators. Although adults are more sensitive to changes in group size, all animals detected context-dependent danger to some extent. Our findings offer insights into the multiple factors that prey respond to when making foraging decisions, suggesting that animals possess the ability to integrate disparate sources of information about danger to optimize energy gain.