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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Courtois, Ève; Bélisle, Marc; Garant, Dany; Pelletier, Fanie;

    Study area The study area included 40 farms distributed along a gradient of agricultural intensification covering approximately 10,200 km2 in southern Québec, Canada. Three land cover types dominated the study system: low-intensity agricultural fields (i.e. hay, alfalfa (Medicago sativa), clover (Trifolium spp.), and pastures, henceforth referred to as “forage crops”), intensive agricultural fields (i.e., annual row crops mainly composed of corn (Zea mays), soybean (Glycine max), and wheat (Triticum spp.)) and forest. Each farm included 10 identical nest boxes mostly arranged in a row along field margins and separated by at least 50 meters to limit intra and interspecific competition (see Ghilain and Bélisle 2008 for further details on the study system). A Thermochron iButton device was fixed on the outside of one nest box on each farm to record hourly ambient temperature (model DS1922L; Embedded Data Systems, Lawrenceburg, Kentucky, USA). A pluviometer collected precipitation data (millimeters of rainfall) on each farm. We used the mean daily temperature and mean daily rainfall between May 1 and May 15 to characterize spring climate. Nest monitoring We monitored nest boxes every other day from 2009 to 2018 starting in the first week of May. We recorded the occurrence of nest materials, the laying date (first egg), and the number of eggs, hatchlings and fledglings. Monitoring ended when all nestlings had fledged on a given farm, which occurred between June 15 and August 5 during the study. Nest boxes were cleared of any nest material and/or dead nestlings every year in October. Preference Preference for each nest box was estimated for each year according to the occurrence of a laying event (at least one egg laid) and settlement date (Julian date at which nesting material was first observed). Because some early settlement dates were left-censored given that some boxes already contained nest material at the first visit (45% of all boxes), settlement dates were classified as either “early” or “late” with respect to the annual median settlement date. The category “early” included boxes with settlement dates preceding or equal to the annual median, which comprised nearly all (91.3%) left-censored dates. Overall, the average difference between the annual mean settlement dates categorized as “early” and “late” was 10.4 ± 2.9 days (mean ± SD). Nest boxes occupied by other species were excluded from analyses (N = 964 boxes between 2009 and 2018). Such exclusions were made possible, even in the absence of a laying event, because the material and shape of nests are very species specific. We are thus confident that the vast majority of nests included in the study were initiated by tree swallows. The ordinal preference variable featured three categories: 1: No laying event 2: Laying event and late settlement 3: Laying event and early settlement Habitat quality We used two proxies of reproductive success: (1) the number of hatchlings produced in a nest box and (2) the proportion of hatchlings that successfully fledged in a nestbox (i.e., fledging success). Landscape context We characterized landscape habitat composition by measuring the relative cover of forest, perennial forage crops, as well as of water bodies and wetlands, within radii of respectively 100 m, 5 km and 10 km. We assessed landscape habitat composition up to the 500-m scale on a yearly basis in the field by visually identifying cultures and marginal habitats and delineating them using orthophotos (1:40,000). Characterization beyond the 500-m scale was based on a mosaic of yearly georeferenced classified optical and radar satellite images taken between 2011 and 2018 (pixel resolution 30 m × 30 m; Agriculture and Agri-Food Canada (AAFC) 2018). Only the year 2018 was used to assess water cover at the above range of scales because it showed better accuracy than the data of previous years (AAFC, 2020), and because the cover of large water bodies, as those covered by the data we used, did not vary significantly across years (e.g., median between-year correlation of yearly water cover between 2011 and 2018 was 0.90 at the 10-km scale). Food availability Two passive insect traps were installed on each farm around the first and second third of the nest box transect. Traps consisted of ~4-L yellow buckets placed 1.5 m above ground. They were filled with ~2 L of salty detergent solution to reduce surface tension and slow the growth of bacteria and fungi. Two transparent plexiglass screens were mounted perpendicularly to one another above each bucket to intercept flying insects (see Bellavance et al. 2018 and Garrett et al. 2021a for details). We collected the content of each trap on every visit to a farm (i.e., every other day) and conserved arthropods in 70% ethanol until processing. We sorted samples by removing arthropods unlikely to be preyed upon by tree swallows (i.e., bumble bees (Bombus spp.: Hymenoptera), June bugs (Phyllophaga spp.: Coleoptera), large spiders (Araneae, > 0.5 cm body width), and caterpillars (Lepidoptera); Bellavance et al. 2018). The rest of the sample was dried at 50ºC for at least 48 hours before being weighed (Adam Equipment, model AAA250L, ± 0.0001 g). The mean daily dry biomass of arthropods collected between May 1 and May 15 was used as a proxy of yearly food availability on a given farm at the time of nest site selection. Heterospecific social information House sparrows (Passer domesticus) are tree swallow’s main nest-site competitors in our system and they initiate breeding before swallows return from their wintering grounds (Robillard, Garant and Bélisle, 2013). We evaluated the use of heterospecific social information through the number of nest boxes occupied by house sparrows on each farm in the current year. Nest boxes and house sparrow nests were visited every other day concurrently to tree swallow monitoring. Occupancy was determined by the presence of at least one egg, and only first clutches observed in each box were included since a nest box is rarely used by another species once house sparrows have built a nest therein. Conspecific social information We defined two sources of social information regarding the future breeding success that an individual could expect to experience on a given farm: the density of tree swallows that bred on a farm during the previous year and the mean number of fledglings obtained by those breeders. Animals are expected to select a breeding habitat using cues that should reflect, directly or not, the fitness outcome of the different habitat options. However, human-induced environmental changes can alter the relationships between habitat characteristics and their fitness consequences, leading to maladaptive habitat choices. The most severe case of such nonideal habitat selection is the ecological trap, which occurs when individuals prefer to settle in poor-quality habitats while better ones are available. Here we studied the adaptiveness of nest box selection in a tree swallow (Tachycineta bicolor) population breeding over a 10-year period in a network of 400 nest boxes distributed along a gradient of agricultural intensification in southern Québec, Canada. We first examined the effects of multiple environmental and social habitat characteristics on nest box preference to identify potential settlement cues. We then assessed the links between those cues and habitat quality as defined by the reproductive performance of individuals that settled early or late in nest boxes. We found that tree swallows preferred nesting in open habitats with high cover of perennial forage crops, high spring insect biomass, and high density of house sparrows (Passer domesticus), their main competitors for nest sites. They also preferred nesting where the density of breeders and their mean number of fledglings during the previous year were high. However, we detected mismatches between preference and habitat quality for several environmental variables. The density of competitors and conspecific social information showed severe mismatches, as their relationships to preference and breeding success went in opposite direction under certain circumstances. Spring food availability and agricultural landscape context, while related to preferences, were not related to breeding success. Overall, our study emphasizes the complexity of habitat selection behavior and provides evidence that multiple mechanisms may potentially lead to an ecological trap in farmlands. 

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    Authors: Deutsch, Andreas;

    Cancer invasion may be viewed as collective phenomenon emerging from the interplay of individual biological cells with their environment. Cell-based mathematical models can be used to decipher the rules of interaction. In these models cells are regarded as separate movable units. Here, we introduce an integrative modelling approach based on mesoscopic biological lattice-gas cellular automata (BIO-LGCA) to analyse collective effects in cancer invasion. This approach is rule- and cell-based, computationally efficient, and integrates statistical and biophysical models for different levels of biological knowledge. In particular, we provide BIO-LGCA models to analyse mechanisms of invasion in glioma and breast cancer cell lines. Ref.: Deutsch, A., Dormann, S.: Cellular automaton modeling of biological pattern formation: characterization, applications, and analysis. Birkhauser, Boston, 2018 Author affiliation: TU Dresden Unreviewed Non UBC Other

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    Lunaris
    Dataset . 2019
    Data sources: Lunaris
    https://doi.org/10.5446/56514...
    Audiovisual . 2019
    Data sources: Datacite
    https://doi.org/10.14288/1.038...
    Audiovisual . 2019
    Data sources: Datacite
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      Lunaris
      Dataset . 2019
      Data sources: Lunaris
      https://doi.org/10.5446/56514...
      Audiovisual . 2019
      Data sources: Datacite
      https://doi.org/10.14288/1.038...
      Audiovisual . 2019
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/

    Ce Sea-Bird Microcat SBE37SMP-ODO 9533 a été déployé le 2023-07-09 au Endeavour South. Cette section sud des évents hydrothermaux Endeavour comprend deux mouillages pour surveiller la circulation régionale. Cet instrument est un Conductivité/Température/Profondeur. Conductivité Température Profondeur (CTD) est un nom abrégé pour un ensemble d'instruments qui contient des capteurs permettant de mesurer la conductivité, la température et la pression de l'eau de mer. La salinité, la vitesse du son, la profondeur et la densité sont des variables qui peuvent être dérivées des mesures par capteurs. Les CTD peuvent transporter d'autres instruments et capteurs, comme des capteurs d'oxygène, des capteurs de turbidité et des fluoromètres. Il a été deployé sur une plateforme fixe. Les données de ce déploiement sont archivées et accessibles sur l'infrastructure numérique Oceans 3.0 du Réseau Canadien des Océans (ONC), avec assurance de la qualité et produits dérivés selon les conventions établies. The Sea-Bird Microcat SBE37SMP-ODO 9533 was deployed on 2023-07-09 at Endeavour South. This south section of the Endeavour Hydrothermal Vents includes two moorings to monitor the regional circulation. This device is a Conductivity Temperature Depth. Conductivity Temperature Depth (CTD) is an instrument package that contains sensors for measuring the conductivity, temperature, and pressure of seawater. Salinity, sound velocity, depth and density are variables that can be derived from sensor measurements. CTDs can carry additional instruments and sensors such as oxygen sensors, turbidity sensors and fluorometers. It was deployed on a fixed platform. Data from this deployment were archived and made available through Ocean Networks Canada's Oceans 3.0 digital infrastructure, with quality assurance and derived data products following established practices.

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    Lunaris
    Dataset . 2023
    Data sources: Lunaris
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    Lunaris
    Dataset . 2023
    Data sources: Lunaris
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    Lunaris
    Dataset . 2023
    Data sources: Lunaris
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    Lunaris
    Dataset . 2023
    Data sources: Lunaris
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    Lunaris
    Dataset . 2023
    Data sources: Lunaris
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    Lunaris
    Dataset . 2023
    Data sources: Lunaris
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      Lunaris
      Dataset . 2023
      Data sources: Lunaris
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      Lunaris
      Dataset . 2023
      Data sources: Lunaris
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      Lunaris
      Dataset . 2023
      Data sources: Lunaris
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      Lunaris
      Dataset . 2023
      Data sources: Lunaris
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      Lunaris
      Dataset . 2023
      Data sources: Lunaris
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      Lunaris
      Dataset . 2023
      Data sources: Lunaris
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    Authors: Garrett, Bernard Mark;

    This dataset arises from a project using a survey to explore the use of risk-associated alternative healthcare (RAAH) in Canada. RAAH uptake was surveyed to explore the characteristics of adult RAAH users and the value of established psychometric instruments previously used in alternative healthcare studies in predicting RAAH behaviours: the Control Beliefs Inventory (CBI), the Reward Responsiveness Behavioural Activation System (RBAS) scale, the Positive Attitudes to Science (PAS) scale, the Satisfaction with Orthodox Medicine (SOM) scale, and the brief version of the Susceptibility to Persuasion-II (StP-II-B) scale. This work draws on research supported by the Social Sciences and Humanities Research Council of Canada Insight Grants program (#435-2019-0190). The authors would like to acknowledge Dr. David Modic of Cambridge University's Computer Laboratory for his assistance and use of the StP-II-B, and Dr. Fuschia Sirois for the use of the CBI.

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    Lunaris
    Dataset . 2023
    Data sources: Lunaris
    Borealis
    Dataset . 2023
    Data sources: Datacite
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      Lunaris
      Dataset . 2023
      Data sources: Lunaris
      Borealis
      Dataset . 2023
      Data sources: Datacite
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    Authors: Hakai Institute;

    This dataset contains the analytical results of freshwater biogeochemical samples collected on Calvert and Hecate Islands on the central coast of British Columbia, Canada, from April 2013 to December 2019. Samples were collected, approximately monthly, year round at the stream outlets of the seven largest watersheds, which are gauged as part of the Kwakshua Watersheds Observatory. The samples were analyzed for dissolved organic carbon (DOC) concentration and stable isotopes, particulate organic carbon and nitrogen (POC and PON) concentration and isotopes, dissolved organic matter (DOM) composition (via metrics of absorbance and fluorescence), total, dissolved, and inorganic nutrients, metals and major ions, water isotopes, and total suspended solids (TSS). Complimenting each water chemistry sample, we measured electrical conductivity, temperature, pH, oxidation reduction potential (ORP), and dissolved oxygen in-situ with a hand-held sensor. From the Calvert Island field station, each stream was accessed by a short boat ride (~10 min). The field team was dropped on land and walked up-stream to the pre-established sampling location, above tidal influence. For most sample types, water was filtered streamside, using a 0.45 µm filter attached to a syringe. POC, PON, and TSS samples, however, were brought back to the laboratory, to be filtered via vaccum filtration, using a grade GF/F 0.7 µm filter. The samples were then preserved, according to the Hakai preservation protocol before being sent to external analytical laboratories for analysis. The absorbance and fluorescence samples as well as TSS samples were analyzed on site by Hakai technicians. The physio-chemical parameters were measured directly at the sampling locations, using the YSI probe (Pro Plus Multiparameter Instrument) The resulting data were reviewed and flagged following our standard quality control (QC) procedures.

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    Lunaris
    Dataset . 2022
    Data sources: Lunaris
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      Lunaris
      Dataset . 2022
      Data sources: Lunaris
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    Authors: Rogers, Paul; Johal, Am; Smith, Paige; Wong, Rachel; +3 Authors

    This is the second edition of our Below the Radar Conversations. In this episode, Am Johal speaks with Paul Rogers on COVID-19 and how it impacts geopolitics and climate change. Paul Rogers is professor emeritus in the department of peace studies at Bradford University in the UK. He is openDemocracy's international security adviser, and has been writing a weekly column on global security since 2001; he also writes a monthly briefing for the Oxford Research Group. You can read more of his work and writing on openDemocracy here: www.opendemocracy.net/en/author/paul-rogers/.

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    Authors: Keyel, Edward; Etterson, Matthew; Niemi, Gerald; Evers, David; +5 Authors

    Study Area All samples were collected between 2009-2012 during fall migration (September through November) from the Hawk Ridge Bird Observatory banding station at Duluth, MN, USA (46.85oN, -92.03oW) located near the westernmost point of Lake Superior. Situated at ~300 m above sea level, Hawk Ridge is positioned on basalt rock that extends along the north shore of the lake. This unique location concentrates large numbers of birds of prey, and on average, the banding station bands over 2,600 raptors each fall (Evans et al. 2012). Limited band recovery data suggest that diurnal raptors migrating past Duluth likely originate from breeding grounds in Western Canada and northern Minnesota (Evans et al. 2012). Raptor Sampling Birds were captured using mist, bow, and dho gaza nets (Evans et al. 2012, Table 1). Captured birds were identified, aged, and sexed using methods described by Pyle (2008). Two to four breast feathers were plucked from each sampled bird, inspected for external debris, and placed into envelopes. Feathers were chosen because they represent a reliable index of Hg exposure during the time of feather growth (Bearhop et al. 2000, Kenow et al. 2007, Condon and Cristol 2009) and because they can be sampled non-invasively and easily preserved at room temperature for long periods. Hg Analysis One feather per individual was analyzed for total Hg concentration by thermal decomposition spectrophotometry (EPA method 7473) using a DMA-80 Direct Mercury Analyzer (Milestone) at the BRI Toxicology Lab at Biodiversity Research Institute in Portland, ME, following methods described by Evers et al. (2005). Feathers were prepared for analysis using a protocol employed by U.S. Fish and Wildlife Service contract laboratories (e.g., Texas A & M University; R. Taylor, pers. comm.). Only feathers with no visual evidence of external debris were analyzed. Feathers were not washed, as this protocol does not recommend washing unless external contamination is of concern. Quality control methods including the use of analytical blanks, sample replicates, and certified reference materials DOLT-4, DORM-3 and DORM-4, were employed to evaluate analytical precision and accuracy. Total Hg concentrations in all feathers were above the method detection limit (0.001 µg g-1). Measured Hg concentrations in Certified Reference Materials (CRMs, National Research Council, Canada and Joint Research Centre, European Union) incorporated into each sample run averaged 100% (DOLT-4), 103.7% (DORM-3) and 97.9% (DORM-4) of published values. Feather Hg concentrations are presented in μg g-1 on a fresh weight (fw) basis. Previous work has shown that Hg concentrations can vary among feathers in different parts of the plumage of individual birds (Furness et al. 1986, Braune and Gaskin 1987, Peterson et al. 2019). Although we did not sample multiple feather tracts, we controlled for variation among feathers within birds and standardized comparisons across birds by limiting our sampling to only breast feathers. We also analyzed limited duplicates (e.g., a separate breast feather from the same individual) to verify consistency in Hg concentrations among breast feathers within the same individuals. For duplicates we calculated percent relative difference and Pearson’s correlation coefficient. Because HY birds were known to have grown all feathers within a recent and well-defined timeframe (i.e., nestling development) we also analyzed duplicates and calculated the same statistics within HY and AHY age class groups. The fw of a feather is nearly equivalent to dry weight (dw; R. Taylor, TERL, Texas A & M University, mean % feather moisture <1%, n = 490, reported in DeSorbo et al. 2018). We therefore considered fw = dw for the purposes of literature comparisons. Stable Isotope Analysis Ratios of carbon (δ13C) and nitrogen (δ15N) stable isotopes in feathers were measured for the two species of raptors with the highest mean Hg concentrations: Merlin and Sharp-shinned Hawk. This was done to evaluate the potential relationship between feather Hg and trophic status (as measured by δ15N), and aquatic versus terrestrial carbon source in the raptor diet (as measured by δ13C). Samples from 20 individuals within each age and sex class were selected for stable isotope analysis, with 10 feathers each from the lowest and highest Hg results for each class. Each feather sample was cleaned with a 2:1 chloroform:methanol solution (Hobson 1999), placed in a pre-combusted scintillation vial, and dried at 50oC for at least 24 hours. After drying, the sample was minced and 0.7 μg analyzed with a Costec 4010 EA and Thermo Delta Plus XP isotope ratio mass spectrometer. Stable isotope ratios are reported in standard δ notation, wherein Vienna Pee Dee Belemnite and air are standards for δ13C and δ15N, respectively. Analytical error, calculated as the mean standard deviation of replicate reference material, was < 0.1‰ for δ13C and δ15N. Statistical Analyses Measured feather Hg concentrations were natural log-transformed, and geometric mean concentrations (± SE) were calculated for all 11 species. For a subset of six species with greater sample sizes (n ≥20), analysis of variance was used to compare ln-transformed Hg concentrations, ln(feather Hg), by sex within species, age within species, and their interaction (cohort = all combinations of age and sex) within species. Additional statistical analyses were performed for Merlin and Sharp-shinned Hawk, our two largest samples. A set of 18 general linear models was developed to compare ln(feather Hg) to the year in which birds were captured, ordinal day on which birds were captured, bird age class, sex, and all bivariate interaction terms (Table 2). Year was modeled as a quantitative covariate to test whether feather Hg concentrations were changing over the course of the four years of study. Date was also modeled as a quantitative covariate to explore seasonal variation in feather Hg. Age and sex were modeled as factors, each with 2 levels. Variable importance was calculated based on Akaike’s Information Criterion, corrected for small sample size (AICc), as the sum of AICc weights for each model in which the variable occurred (Burnham and Anderson 2002). A list of all models considered for Merlin and Sharp-shinned Hawk is provided in Table 2. Correlations between ln(feather Hg) and δ13C, and between ln(feather Hg) and δ15N by sex, age, and cohort within each species were evaluated using Pearson’s correlation coefficient. All analyses were conducted in R (version 2.14.0, R Development Core Team 2013).  Mercury (Hg) is a toxic heavy metal that, when methylated to form methylmercury (MeHg), bioaccumulates in exposed animals and biomagnifies through food webs. The purpose of this study was to assess Hg concentrations in raptors migrating through the upper Midwestern USA. From 2009-2012, 966 raptors of 11 species were captured at Hawk Ridge, Duluth, MN. Breast feathers were sampled to determine the concentration of total Hg. Mean Hg concentrations ranged from 0.11 – 3.46 μg g-1 fresh weight across species and were generally higher in raptors that feed on birds in comparison with those that feed on mammals. To evaluate the effect of dietary sources on Hg biomagnification, carbon and nitrogen stable isotope ratios were measured in feathers of the two species with the highest Hg concentrations, Merlin (Falco columbarius) and Sharp-shinned Hawk (Accipiter striatus). Measured δ13C values were similar in both species and indicated a primarily terrestrial-derived diet, whereas δ15N values suggested that individual Merlin and Sharp-shinned Hawk feeding at higher trophic levels accumulated higher concentrations of Hg. The risk to birds associated with measured levels of feather Hg was evaluated by calculating blood-equivalent values using an established algorithm. Predicted blood values were then compared to heuristic risk categories synthesized across avian orders. This analysis suggested that while some Merlin and Sharp-shinned Hawk were at moderate risk to adverse effects of MeHg, most of the sampled birds were at negligible or low risk. There are three worksheets within the Excel file: Hg, Hg_Dups, and Isotope. Hg contains the methylmercury data and should be self-explanatory except perhaps for the 4-letter alphanumeric species codes, which can be easily looked up, and age codes (HY = Hatch Year, AHY = After Hatch Year, SY = Second Year, ASY = After Second Year). Hg_Dups contains the Hg lab duplicate data. Isotope contains the C and N stable isotope data, which should also be self-explanatory, although there are only two species (SS = Sharp-shinned Hawk and ML = Merlin).

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    DRYAD; ZENODO
    Dataset . 2021
    License: CC 0
    Data sources: ZENODO; Datacite
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      DRYAD; ZENODO
      Dataset . 2021
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    Authors: Chen, Yining; Clark, Oliver; Woolley, Sarah C.;

    The performance of courtship signals provides information about the behavioural state and quality of the signaller, and females can use such information for social decision-making (e.g. mate choice). However, relatively little is known about the degree to which the perception of and preference for differences in motor performance are shaped by developmental experiences. Furthermore, the neural substrates that development could act upon to influence the processing of performance features remains largely unknown. In songbirds, females use song to identify males and select mates. Moreover, female songbirds are often sensitive to variation in male song performance. Consequently, we investigated how developmental exposure to adult male song affected behavioural and neural responses to song in a small, gregarious songbird, the zebra finch. Zebra finch males modulate their song performance when courting females, and previous work has shown that females prefer the high-performance, female-directed courtship song. However, unlike females allowed to hear and interact with an adult male during development, females reared without developmental song exposure did not demonstrate behavioural preferences for high-performance courtship songs. Additionally, auditory responses to courtship and non-courtship song were altered in adult females raised without developmental song exposure. These data highlight the critical role of developmental auditory experience in shaping the perception and processing of song performance. EGR1_dataNumber of EGR1 neurons/mm2 in the NCM, CMM and IC.preference_score_by_maleIDAverage preference scores of all females tested on each male stimulus.preference_scores_all_femalesraw data for call back preference tests for normally-reared and song-naive females tested on stimuli from different malespreference_score_vs_song_measuresPercent difference for measures of song between courtship and non-courtship singing. Measures include the number of introductory notes and motifs, syllable entropy, CV of the fundamental frequency and song tempo (motif duration).

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    DANS-EASY
    Dataset . 2017
    Data sources: B2FIND
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      Dataset . 2017
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    Authors: Bennett, Joseph R.; Maxwell, Sean L.; Martin, Amanda E.; Chadès, Iadine; +2 Authors

    1.The question of when to monitor and when to act is fundamental to applied ecology, and notoriously difficult to answer. Value of information (VOI) theory holds great promise to help answer this question for many management problems. However, VOI theory in applied ecology has only been demonstrated in single-decision problems, and has lacked explicit links between monitoring and management costs. 2.Here, we present an extension of VOI theory for solving multi-unit decisions of whether to monitor before managing, while explicitly accounting for monitoring costs. Our formulation helps to choose the optimal monitoring/management strategy among groups of management units (e.g. species, habitat patches), and can be used to examine the benefits of partial and repeat monitoring. 3.To demonstrate our approach, we use case simulated studies of single-species protection that must choose among potential habitat areas, and classification and management of multiple species threatened with extinction. We provide spreadsheets and code to illustrate the calculations and facilitate application. Our case studies demonstrate the utility of predicting the number of units with a given outcome for problems with probabilities of discrete states, and the efficiency of having a flexible approach to manage according to monitoring outcomes. 4.Synthesis and applications. The decision to act or gather more information can have serious consequences for management. No decision, including the decision to monitor, is risk-free. Our multi-unit expansion of Value of Information (VOI) theory can reduce the risk in monitoring/acting decisions for many applied ecology problems. While our approach cannot account for the potential value of discovering previously unknown threats or ecological processes via monitoring programs, it can provide quantitative guidance on whether to monitor before acting, and which monitoring/management actions are most likely to meet management objectives. Multi-unit VOI functionsCode to simulate and analyze data for multi-unit value of information (VOI) problems in Bennett et al. (J. Appl. Ecol.)voi functions multi unit.txt

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    DANS-EASY
    Dataset . 2018
    Data sources: B2FIND
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      DANS-EASY
      Dataset . 2018
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    Authors: Bitton, Pierre-Paul; Yun Christmann, Sebastian Alejandro; Santon, Matteo; Harant, Ulrike K.; +1 Authors

    Active sensing has been well documented in animals that use echolocation and electrolocation. Active photolocation, or active sensing using light, has received much less attention, and only in bioluminescent nocturnal species. However, evidence has suggested the diurnal triplefin Tripterygion delaisi uses controlled iris radiance, termed ocular sparks, for prey detection. While this form of diurnal active photolocation was behaviourally described, a study exploring the physical process would provide compelling support for this mechanism. In this paper, we investigate the conditions under which diurnal active photolocation could assist T. delaisi in detecting potential prey. In the field, we sampled gammarids (genus Cheirocratus) and characterized the spectral properties of their eyes, which possess strong directional reflectors. In the laboratory, we quantified ocular sparks size and their angle-dependent radiance. Combined with environmental light measurements and known properties of the visual system of T. delaisi, we modeled diurnal active photolocation under various scenarios. Our results corroborate that diurnal active photolocation should help T. delaisi detect gammarids at distances relevant to foraging, 4.5 cm under favourable conditions and up to 2.5 cm under average conditions. To determine the prevalence of diurnal active photolocation for micro-prey, we encourage further theoretical and empirical work. Average gammarid body reflectanceSpectrophotometric data for body reflectance of Cheirocratus gammaridsAverage gammarid body transmissionSpectrophotometric transmission measurements of Cheirocratus gammarid bodyBackground reflectance Haliopteris filicianaSpectrophotometric measurements of Haliopteris filicianaCoaxial reflectance values categoricalReflective properties of Gammarid eyes measured with coaxial light sourceDownwelling and sidewelling illuminant for analysesDownwelling and sidewelling light fieldsEye reflectance conversion values categoricalConversion factors to produce non-coaxial reflectance values from co-axial reflectance values for gammarid eyesOcular media valuesTransmission properties of the ocular media of Tripterigyon delaisiOcular spark conversion on continuous scaleConversion curves for transforming downwelling irradiance into ocular spark radianceSA scores Gammarid as perceived by Td pupilSolid angle of the gammarid eye as perceived from the pupil of T. delaisi based on the interaction distanceSA scores Os as perceived by Gammarid eye MATRIXSolid angles of the Ocular spark from T delaisi as perceived by the gammarid eye based on the interaction distance

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    DRYAD; ZENODO
    Dataset . 2019
    License: CC 0
    Data sources: Datacite; ZENODO
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      DRYAD; ZENODO
      Dataset . 2019
      License: CC 0
      Data sources: Datacite; ZENODO
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Courtois, Ève; Bélisle, Marc; Garant, Dany; Pelletier, Fanie;

    Study area The study area included 40 farms distributed along a gradient of agricultural intensification covering approximately 10,200 km2 in southern Québec, Canada. Three land cover types dominated the study system: low-intensity agricultural fields (i.e. hay, alfalfa (Medicago sativa), clover (Trifolium spp.), and pastures, henceforth referred to as “forage crops”), intensive agricultural fields (i.e., annual row crops mainly composed of corn (Zea mays), soybean (Glycine max), and wheat (Triticum spp.)) and forest. Each farm included 10 identical nest boxes mostly arranged in a row along field margins and separated by at least 50 meters to limit intra and interspecific competition (see Ghilain and Bélisle 2008 for further details on the study system). A Thermochron iButton device was fixed on the outside of one nest box on each farm to record hourly ambient temperature (model DS1922L; Embedded Data Systems, Lawrenceburg, Kentucky, USA). A pluviometer collected precipitation data (millimeters of rainfall) on each farm. We used the mean daily temperature and mean daily rainfall between May 1 and May 15 to characterize spring climate. Nest monitoring We monitored nest boxes every other day from 2009 to 2018 starting in the first week of May. We recorded the occurrence of nest materials, the laying date (first egg), and the number of eggs, hatchlings and fledglings. Monitoring ended when all nestlings had fledged on a given farm, which occurred between June 15 and August 5 during the study. Nest boxes were cleared of any nest material and/or dead nestlings every year in October. Preference Preference for each nest box was estimated for each year according to the occurrence of a laying event (at least one egg laid) and settlement date (Julian date at which nesting material was first observed). Because some early settlement dates were left-censored given that some boxes already contained nest material at the first visit (45% of all boxes), settlement dates were classified as either “early” or “late” with respect to the annual median settlement date. The category “early” included boxes with settlement dates preceding or equal to the annual median, which comprised nearly all (91.3%) left-censored dates. Overall, the average difference between the annual mean settlement dates categorized as “early” and “late” was 10.4 ± 2.9 days (mean ± SD). Nest boxes occupied by other species were excluded from analyses (N = 964 boxes between 2009 and 2018). Such exclusions were made possible, even in the absence of a laying event, because the material and shape of nests are very species specific. We are thus confident that the vast majority of nests included in the study were initiated by tree swallows. The ordinal preference variable featured three categories: 1: No laying event 2: Laying event and late settlement 3: Laying event and early settlement Habitat quality We used two proxies of reproductive success: (1) the number of hatchlings produced in a nest box and (2) the proportion of hatchlings that successfully fledged in a nestbox (i.e., fledging success). Landscape context We characterized landscape habitat composition by measuring the relative cover of forest, perennial forage crops, as well as of water bodies and wetlands, within radii of respectively 100 m, 5 km and 10 km. We assessed landscape habitat composition up to the 500-m scale on a yearly basis in the field by visually identifying cultures and marginal habitats and delineating them using orthophotos (1:40,000). Characterization beyond the 500-m scale was based on a mosaic of yearly georeferenced classified optical and radar satellite images taken between 2011 and 2018 (pixel resolution 30 m × 30 m; Agriculture and Agri-Food Canada (AAFC) 2018). Only the year 2018 was used to assess water cover at the above range of scales because it showed better accuracy than the data of previous years (AAFC, 2020), and because the cover of large water bodies, as those covered by the data we used, did not vary significantly across years (e.g., median between-year correlation of yearly water cover between 2011 and 2018 was 0.90 at the 10-km scale). Food availability Two passive insect traps were installed on each farm around the first and second third of the nest box transect. Traps consisted of ~4-L yellow buckets placed 1.5 m above ground. They were filled with ~2 L of salty detergent solution to reduce surface tension and slow the growth of bacteria and fungi. Two transparent plexiglass screens were mounted perpendicularly to one another above each bucket to intercept flying insects (see Bellavance et al. 2018 and Garrett et al. 2021a for details). We collected the content of each trap on every visit to a farm (i.e., every other day) and conserved arthropods in 70% ethanol until processing. We sorted samples by removing arthropods unlikely to be preyed upon by tree swallows (i.e., bumble bees (Bombus spp.: Hymenoptera), June bugs (Phyllophaga spp.: Coleoptera), large spiders (Araneae, > 0.5 cm body width), and caterpillars (Lepidoptera); Bellavance et al. 2018). The rest of the sample was dried at 50ºC for at least 48 hours before being weighed (Adam Equipment, model AAA250L, ± 0.0001 g). The mean daily dry biomass of arthropods collected between May 1 and May 15 was used as a proxy of yearly food availability on a given farm at the time of nest site selection. Heterospecific social information House sparrows (Passer domesticus) are tree swallow’s main nest-site competitors in our system and they initiate breeding before swallows return from their wintering grounds (Robillard, Garant and Bélisle, 2013). We evaluated the use of heterospecific social information through the number of nest boxes occupied by house sparrows on each farm in the current year. Nest boxes and house sparrow nests were visited every other day concurrently to tree swallow monitoring. Occupancy was determined by the presence of at least one egg, and only first clutches observed in each box were included since a nest box is rarely used by another species once house sparrows have built a nest therein. Conspecific social information We defined two sources of social information regarding the future breeding success that an individual could expect to experience on a given farm: the density of tree swallows that bred on a farm during the previous year and the mean number of fledglings obtained by those breeders. Animals are expected to select a breeding habitat using cues that should reflect, directly or not, the fitness outcome of the different habitat options. However, human-induced environmental changes can alter the relationships between habitat characteristics and their fitness consequences, leading to maladaptive habitat choices. The most severe case of such nonideal habitat selection is the ecological trap, which occurs when individuals prefer to settle in poor-quality habitats while better ones are available. Here we studied the adaptiveness of nest box selection in a tree swallow (Tachycineta bicolor) population breeding over a 10-year period in a network of 400 nest boxes distributed along a gradient of agricultural intensification in southern Québec, Canada. We first examined the effects of multiple environmental and social habitat characteristics on nest box preference to identify potential settlement cues. We then assessed the links between those cues and habitat quality as defined by the reproductive performance of individuals that settled early or late in nest boxes. We found that tree swallows preferred nesting in open habitats with high cover of perennial forage crops, high spring insect biomass, and high density of house sparrows (Passer domesticus), their main competitors for nest sites. They also preferred nesting where the density of breeders and their mean number of fledglings during the previous year were high. However, we detected mismatches between preference and habitat quality for several environmental variables. The density of competitors and conspecific social information showed severe mismatches, as their relationships to preference and breeding success went in opposite direction under certain circumstances. Spring food availability and agricultural landscape context, while related to preferences, were not related to breeding success. Overall, our study emphasizes the complexity of habitat selection behavior and provides evidence that multiple mechanisms may potentially lead to an ecological trap in farmlands. 

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    Authors: Deutsch, Andreas;

    Cancer invasion may be viewed as collective phenomenon emerging from the interplay of individual biological cells with their environment. Cell-based mathematical models can be used to decipher the rules of interaction. In these models cells are regarded as separate movable units. Here, we introduce an integrative modelling approach based on mesoscopic biological lattice-gas cellular automata (BIO-LGCA) to analyse collective effects in cancer invasion. This approach is rule- and cell-based, computationally efficient, and integrates statistical and biophysical models for different levels of biological knowledge. In particular, we provide BIO-LGCA models to analyse mechanisms of invasion in glioma and breast cancer cell lines. Ref.: Deutsch, A., Dormann, S.: Cellular automaton modeling of biological pattern formation: characterization, applications, and analysis. Birkhauser, Boston, 2018 Author affiliation: TU Dresden Unreviewed Non UBC Other

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    Lunaris
    Dataset . 2019
    Data sources: Lunaris
    https://doi.org/10.5446/56514...
    Audiovisual . 2019
    Data sources: Datacite
    https://doi.org/10.14288/1.038...
    Audiovisual . 2019
    Data sources: Datacite
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      Lunaris
      Dataset . 2019
      Data sources: Lunaris
      https://doi.org/10.5446/56514...
      Audiovisual . 2019
      Data sources: Datacite
      https://doi.org/10.14288/1.038...
      Audiovisual . 2019
      Data sources: Datacite
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    Ce Sea-Bird Microcat SBE37SMP-ODO 9533 a été déployé le 2023-07-09 au Endeavour South. Cette section sud des évents hydrothermaux Endeavour comprend deux mouillages pour surveiller la circulation régionale. Cet instrument est un Conductivité/Température/Profondeur. Conductivité Température Profondeur (CTD) est un nom abrégé pour un ensemble d'instruments qui contient des capteurs permettant de mesurer la conductivité, la température et la pression de l'eau de mer. La salinité, la vitesse du son, la profondeur et la densité sont des variables qui peuvent être dérivées des mesures par capteurs. Les CTD peuvent transporter d'autres instruments et capteurs, comme des capteurs d'oxygène, des capteurs de turbidité et des fluoromètres. Il a été deployé sur une plateforme fixe. Les données de ce déploiement sont archivées et accessibles sur l'infrastructure numérique Oceans 3.0 du Réseau Canadien des Océans (ONC), avec assurance de la qualité et produits dérivés selon les conventions établies. The Sea-Bird Microcat SBE37SMP-ODO 9533 was deployed on 2023-07-09 at Endeavour South. This south section of the Endeavour Hydrothermal Vents includes two moorings to monitor the regional circulation. This device is a Conductivity Temperature Depth. Conductivity Temperature Depth (CTD) is an instrument package that contains sensors for measuring the conductivity, temperature, and pressure of seawater. Salinity, sound velocity, depth and density are variables that can be derived from sensor measurements. CTDs can carry additional instruments and sensors such as oxygen sensors, turbidity sensors and fluorometers. It was deployed on a fixed platform. Data from this deployment were archived and made available through Ocean Networks Canada's Oceans 3.0 digital infrastructure, with quality assurance and derived data products following established practices.

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    Lunaris
    Dataset . 2023
    Data sources: Lunaris
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Lunaris
    Dataset . 2023
    Data sources: Lunaris
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    Lunaris
    Dataset . 2023
    Data sources: Lunaris
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Lunaris
    Dataset . 2023
    Data sources: Lunaris
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    Lunaris
    Dataset . 2023
    Data sources: Lunaris
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    Lunaris
    Dataset . 2023
    Data sources: Lunaris
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      Lunaris
      Dataset . 2023
      Data sources: Lunaris