2,404 research outputs found

    A conceptual model for the integration of social and ecological information to understand human-wildlife interactions

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    There is growing recognition that interdisciplinary approaches that account for both ecological and social processes are necessary to successfully address human-wildlife interactions. However, such approaches are hindered by challenges in aligning data types, communicating across disciplines, and applying social science information to conservation actions. To meet these challenges, we propose a conceptual model that adopts a social-ecological systems approach and integrates social and ecological theory to identify the multiple, nested levels of influence on both human and animal behavior. By accounting for a diverse array of influences and feedback mechanisms between social and ecological systems, this model fulfills a need for approaches that treat social and ecological processes with equal depth and facilitates a comprehensive understanding of the drivers of human and animal behaviors that perpetuate human-wildlife interactions. We apply this conceptual model to our work on human-black bear conflicts in Colorado, USA to demonstrate its utility. Using this example, we identify key lessons and offer guidance to researchers and conservation practitioners for applying integrated approaches to other human-wildlife systems

    The Gray Needle: Large Grains in the HD 15115 Debris Disk from LBT/PISCES/Ks and LBTI/LMIRcam/L' Adaptive Optics Imaging

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    We present diffraction-limited \ks band and \lprime adaptive optics images of the edge-on debris disk around the nearby F2 star HD 15115, obtained with a single 8.4 m primary mirror at the Large Binocular Telescope. At \ks band the disk is detected at signal-to-noise per resolution element (SNRE) \about 3-8 from \about 1-2\fasec 5 (45-113 AU) on the western side, and from \about 1.2-2\fasec 1 (63-90 AU) on the east. At \lprime the disk is detected at SNRE \about 2.5 from \about 1-1\fasec 45 (45-90 AU) on both sides, implying more symmetric disk structure at 3.8 \microns . At both wavelengths the disk has a bow-like shape and is offset from the star to the north by a few AU. A surface brightness asymmetry exists between the two sides of the disk at \ks band, but not at \lprime . The surface brightness at \ks band declines inside 1\asec (\about 45 AU), which may be indicative of a gap in the disk near 1\asec. The \ks - \lprime disk color, after removal of the stellar color, is mostly grey for both sides of the disk. This suggests that scattered light is coming from large dust grains, with 3-10 \microns -sized grains on the east side and 1-10 \microns dust grains on the west. This may suggest that the west side is composed of smaller dust grains than the east side, which would support the interpretation that the disk is being dynamically affected by interactions with the local interstellar medium.Comment: Apj-accepted March 27 2012; minor correction

    First Light LBT AO Images of HR 8799 bcde at 1.65 and 3.3 Microns: New Discrepancies between Young Planets and Old Brown Dwarfs

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    As the only directly imaged multiple planet system, HR 8799 provides a unique opportunity to study the physical properties of several planets in parallel. In this paper, we image all four of the HR 8799 planets at H-band and 3.3 microns with the new LBT adaptive optics system, PISCES, and LBTI/LMIRCam. Our images offer an unprecedented view of the system, allowing us to obtain H and 3.3$ micron photometry of the innermost planet (for the first time) and put strong upper-limits on the presence of a hypothetical fifth companion. We find that all four planets are unexpectedly bright at 3.3 microns compared to the equilibrium chemistry models used for field brown dwarfs, which predict that planets should be faint at 3.3 microns due to CH4 opacity. We attempt to model the planets with thick-cloudy, non-equilibrium chemistry atmospheres, but find that removing CH4 to fit the 3.3 micron photometry increases the predicted L' (3.8 microns) flux enough that it is inconsistent with observations. In an effort to fit the SED of the HR 8799 planets, we construct mixtures of cloudy atmospheres, which are intended to represent planets covered by clouds of varying opacity. In this scenario, regions with low opacity look hot and bright, while regions with high opacity look faint, similar to the patchy cloud structures on Jupiter and L/T transition brown-dwarfs. Our mixed cloud models reproduce all of the available data, but self-consistent models are still necessary to demonstrate their viability.Comment: Accepted to Ap

    Genome-Wide Association Study of Susceptibility to Idiopathic Pulmonary Fibrosis

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    Rationale: Idiopathic pulmonary fibrosis (IPF) is a complex lung disease characterised by scarring of the lung that is believed to result from an atypical response to injury of the epithelium. Genome-wide association studies have reported signals of association implicating multiple pathways including host defence, telomere maintenance, signalling and cell-cell adhesion. Objectives: To improve our understanding of factors that increase IPF susceptibility by identifying previously unreported genetic associations. Methods and measurements: We conducted genome-wide analyses across three independent studies and meta-analysed these results to generate the largest genome-wide association study of IPF to date (2,668 IPF cases and 8,591 controls). We performed replication in two independent studies (1,456 IPF cases and 11,874 controls) and functional analyses (including statistical fine-mapping, investigations into gene expression and testing for enrichment of IPF susceptibility signals in regulatory regions) to determine putatively causal genes. Polygenic risk scores were used to assess the collective effect of variants not reported as associated with IPF. Main results: We identified and replicated three new genome-wide significant (P<5×10−8) signals of association with IPF susceptibility (associated with altered gene expression of KIF15, MAD1L1 and DEPTOR) and confirmed associations at 11 previously reported loci. Polygenic risk score analyses showed that the combined effect of many thousands of as-yet unreported IPF susceptibility variants contribute to IPF susceptibility. Conclusions: The observation that decreased DEPTOR expression associates with increased susceptibility to IPF, supports recent studies demonstrating the importance of mTOR signalling in lung fibrosis. New signals of association implicating KIF15 and MAD1L1 suggest a possible role of mitotic spindle-assembly genes in IPF susceptibility

    The CHEOPS mission

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    The CHaracterising ExOPlanet Satellite (CHEOPS) was selected in 2012, as the first small mission in the ESA Science Programme and successfully launched in December 2019. CHEOPS is a partnership between ESA and Switzerland with important contributions by ten additional ESA Member States. CHEOPS is the first mission dedicated to search for transits of exoplanets using ultrahigh precision photometry on bright stars already known to host planets. As a follow-up mission, CHEOPS is mainly dedicated to improving, whenever possible, existing radii measurements or provide first accurate measurements for a subset of those planets for which the mass has already been estimated from ground-based spectroscopic surveys and to following phase curves. CHEOPS will provide prime targets for future spectroscopic atmospheric characterisation. Requirements on the photometric precision and stability have been derived for stars with magnitudes ranging from 6 to 12 in the V band. In particular, CHEOPS shall be able to detect Earth-size planets transiting G5 dwarf stars in the magnitude range between 6 and 9 by achieving a photometric precision of 20 ppm in 6 hours of integration. For K stars in the magnitude range between 9 and 12, CHEOPS shall be able to detect transiting Neptune-size planets achieving a photometric precision of 85 ppm in 3 hours of integration. This is achieved by using a single, frame-transfer, back-illuminated CCD detector at the focal plane assembly of a 33.5 cm diameter telescope. The 280 kg spacecraft has a pointing accuracy of about 1 arcsec rms and orbits on a sun-synchronous dusk-dawn orbit at 700 km altitude. The nominal mission lifetime is 3.5 years. During this period, 20% of the observing time is available to the community through a yearly call and a discretionary time programme managed by ESA.Comment: Submitted to Experimental Astronom

    Slow Solar Wind Connection Science during Solar Orbiter’s First Close Perihelion Passage

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    The Slow Solar Wind Connection Solar Orbiter Observing Plan (Slow Wind SOOP) was developed to utilize the extensive suite of remote-sensing and in situ instruments on board the ESA/NASA Solar Orbiter mission to answer significant outstanding questions regarding the origin and formation of the slow solar wind. The Slow Wind SOOP was designed to link remote-sensing and in situ measurements of slow wind originating at open–closed magnetic field boundaries. The SOOP ran just prior to Solar Orbiter’s first close perihelion passage during two remote-sensing windows (RSW1 and RSW2) between 2022 March 3–6 and 2022 March 17–22, while Solar Orbiter was at respective heliocentric distances of 0.55–0.51 and 0.38–0.34 au from the Sun. Coordinated observation campaigns were also conducted by Hinode and IRIS. The magnetic connectivity tool was used, along with low-latency in situ data and full-disk remote-sensing observations, to guide the target pointing of Solar Orbiter. Solar Orbiter targeted an active region complex during RSW1, the boundary of a coronal hole, and the periphery of a decayed active region during RSW2. Postobservation analysis using the magnetic connectivity tool, along with in situ measurements from MAG and SWA/PAS, showed that slow solar wind originating from two out of three of the target regions arrived at the spacecraft with velocities between ∼210 and 600 km s−1. The Slow Wind SOOP, despite presenting many challenges, was very successful, providing a blueprint for planning future observation campaigns that rely on the magnetic connectivity of Solar Orbiter

    Expert range maps of global mammal distributions harmonised to three taxonomic authorities

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    Aim: Comprehensive, global information on species' occurrences is an essential biodiversity variable and central to a range of applications in ecology, evolution, biogeography and conservation. Expert range maps often represent a species' only available distributional information and play an increasing role in conservation assessments and macroecology. We provide global range maps for the native ranges of all extant mammal species harmonised to the taxonomy of the Mammal Diversity Database (MDD) mobilised from two sources, the Handbook of the Mammals of the World (HMW) and the Illustrated Checklist of the Mammals of the World (CMW). Location: Global. Taxon: All extant mammal species. Methods: Range maps were digitally interpreted, georeferenced, error-checked and subsequently taxonomically aligned between the HMW (6253 species), the CMW (6431 species) and the MDD taxonomies (6362 species). Results: Range maps can be evaluated and visualised in an online map browser at Map of Life (mol.org) and accessed for individual or batch download for non-commercial use. Main conclusion: Expert maps of species' global distributions are limited in their spatial detail and temporal specificity, but form a useful basis for broad-scale characterizations and model-based integration with other data. We provide georeferenced range maps for the native ranges of all extant mammal species as shapefiles, with species-level metadata and source information packaged together in geodatabase format. Across the three taxonomic sources our maps entail, there are 1784 taxonomic name differences compared to the maps currently available on the IUCN Red List website. The expert maps provided here are harmonised to the MDD taxonomic authority and linked to a community of online tools that will enable transparent future updates and version control.Fil: Marsh, Charles J.. Yale University; Estados UnidosFil: Sica, Yanina. Yale University; Estados UnidosFil: Burguin, Connor. University of New Mexico; Estados UnidosFil: Dorman, Wendy A.. University of Yale; Estados UnidosFil: Anderson, Robert C.. University of Yale; Estados UnidosFil: del Toro Mijares, Isabel. University of Yale; Estados UnidosFil: Vigneron, Jessica G.. University of Yale; Estados UnidosFil: Barve, Vijay. University Of Florida. Florida Museum Of History; Estados UnidosFil: Dombrowik, Victoria L.. University of Yale; Estados UnidosFil: Duong, Michelle. University of Yale; Estados UnidosFil: Guralnick, Robert. University Of Florida. Florida Museum Of History; Estados UnidosFil: Hart, Julie A.. University of Yale; Estados UnidosFil: Maypole, J. Krish. University of Yale; Estados UnidosFil: McCall, Kira. University of Yale; Estados UnidosFil: Ranipeta, Ajay. University of Yale; Estados UnidosFil: Schuerkmann, Anna. University of Yale; Estados UnidosFil: Torselli, Michael A.. University of Yale; Estados UnidosFil: Lacher, Thomas. Texas A&M University; Estados UnidosFil: Wilson, Don E.. National Museum of Natural History; Estados UnidosFil: Abba, Agustin Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Estudios Parasitológicos y de Vectores. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. Centro de Estudios Parasitológicos y de Vectores; ArgentinaFil: Aguirre, Luis F.. Universidad Mayor de San Simón; BoliviaFil: Arroyo Cabrales, Joaquín. Instituto Nacional de Antropología E Historia, Mexico; MéxicoFil: Astúa, Diego. Universidade Federal de Pernambuco; BrasilFil: Baker, Andrew M.. Queensland University of Technology; Australia. Queensland Museum; AustraliaFil: Braulik, Gill. University of St. Andrews; Reino UnidoFil: Braun, Janet K.. Oklahoma State University; Estados UnidosFil: Brito, Jorge. Instituto Nacional de Biodiversidad; EcuadorFil: Busher, Peter E.. Boston University; Estados UnidosFil: Burneo, Santiago F.. Pontificia Universidad Católica del Ecuador; EcuadorFil: Camacho, M. Alejandra. Pontificia Universidad Católica del Ecuador; EcuadorFil: de Almeida Chiquito, Elisandra. Universidade Federal do Espírito Santo; BrasilFil: Cook, Joseph A.. University of New Mexico; Estados UnidosFil: Cuéllar Soto, Erika. Sultan Qaboos University; OmánFil: Davenport, Tim R. B.. Wildlife Conservation Society; TanzaniaFil: Denys, Christiane. Muséum National d'Histoire Naturelle; FranciaFil: Dickman, Christopher R.. The University Of Sydney; AustraliaFil: Eldridge, Mark D. B.. Australian Museum; AustraliaFil: Fernandez Duque, Eduardo. University of Yale; Estados UnidosFil: Francis, Charles M.. Environment And Climate Change Canada; CanadáFil: Frankham, Greta. Australian Museum; AustraliaFil: Freitas, Thales. Universidade Federal do Rio Grande do Sul; BrasilFil: Friend, J. Anthony. Conservation And Attractions; AustraliaFil: Giannini, Norberto Pedro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico - Tucumán. Unidad Ejecutora Lillo; ArgentinaFil: Gursky-Doyen, Sharon. Texas A&M University; Estados UnidosFil: Hackländer, Klaus. Universitat Fur Bodenkultur Wien; AustriaFil: Hawkins, Melissa. National Museum of Natural History; Estados UnidosFil: Helgen, Kristofer M.. Australian Museum; AustraliaFil: Heritage, Steven. University of Duke; Estados UnidosFil: Hinckley, Arlo. Consejo Superior de Investigaciones Científicas. Estación Biológica de Doñana; EspañaFil: Holden, Mary. American Museum of Natural History; Estados UnidosFil: Holekamp, Kay E.. Michigan State University; Estados UnidosFil: Humle, Tatyana. University Of Kent; Reino UnidoFil: Ibáñez Ulargui, Carlos. Consejo Superior de Investigaciones Científicas. Estación Biológica de Doñana; EspañaFil: Jackson, Stephen M.. Australian Museum; AustraliaFil: Janecka, Mary. University of Pittsburgh at Johnstown; Estados Unidos. University of Pittsburgh; Estados UnidosFil: Jenkins, Paula. Natural History Museum; Reino UnidoFil: Juste, Javier. Consejo Superior de Investigaciones Científicas. Estación Biológica de Doñana; EspañaFil: Leite, Yuri L. R.. Universidade Federal do Espírito Santo; BrasilFil: Novaes, Roberto Leonan M.. Universidade Federal do Rio de Janeiro; BrasilFil: Lim, Burton K.. Royal Ontario Museum; CanadáFil: Maisels, Fiona G.. Wildlife Conservation Society; Estados UnidosFil: Mares, Michael A.. Oklahoma State University; Estados UnidosFil: Marsh, Helene. James Cook University; AustraliaFil: Mattioli, Stefano. Università degli Studi di Siena; ItaliaFil: Morton, F. Blake. University of Hull; Reino UnidoFil: Ojeda, Agustina Alejandra. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto Argentino de Investigaciones de las Zonas Áridas. Provincia de Mendoza. Instituto Argentino de Investigaciones de las Zonas Áridas. Universidad Nacional de Cuyo. Instituto Argentino de Investigaciones de las Zonas Áridas; ArgentinaFil: Ordóñez Garza, Nicté. Instituto Nacional de Biodiversidad; EcuadorFil: Pardiñas, Ulises Francisco J.. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Instituto de Diversidad y Evolución Austral; ArgentinaFil: Pavan, Mariana. Universidade de Sao Paulo; BrasilFil: Riley, Erin P.. San Diego State University; Estados UnidosFil: Rubenstein, Daniel I.. University of Princeton; Estados UnidosFil: Ruelas, Dennisse. Museo de Historia Natural, Lima; PerúFil: Schai-Braun, Stéphanie. Universitat Fur Bodenkultur Wien; AustriaFil: Schank, Cody J.. University of Texas at Austin; Estados UnidosFil: Shenbrot, Georgy. Ben Gurion University of the Negev; IsraelFil: Solari, Sergio. Universidad de Antioquia; ColombiaFil: Superina, Mariella. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Medicina y Biología Experimental de Cuyo; ArgentinaFil: Tsang, Susan. American Museum of Natural History; Estados UnidosFil: Van Cakenberghe, Victor. Universiteit Antwerp; BélgicaFil: Veron, Geraldine. Université Pierre et Marie Curie; FranciaFil: Wallis, Janette. Kasokwa-kityedo Forest Project; UgandaFil: Whittaker, Danielle. Michigan State University; Estados UnidosFil: Wells, Rod. Flinders University.; AustraliaFil: Wittemyer, George. State University of Colorado - Fort Collins; Estados UnidosFil: Woinarski, John. Charles Darwin University; AustraliaFil: Upham, Nathan S.. University of Yale; Estados UnidosFil: Jetz, Walter. University of Yale; Estados Unido

    Expert range maps of global mammal distributions harmonised to three taxonomic authorities

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    AimComprehensive, global information on species' occurrences is an essential biodiversity variable and central to a range of applications in ecology, evolution, biogeography and conservation. Expert range maps often represent a species' only available distributional information and play an increasing role in conservation assessments and macroecology. We provide global range maps for the native ranges of all extant mammal species harmonised to the taxonomy of the Mammal Diversity Database (MDD) mobilised from two sources, the Handbook of the Mammals of the World (HMW) and the Illustrated Checklist of the Mammals of the World (CMW).LocationGlobal.TaxonAll extant mammal species.MethodsRange maps were digitally interpreted, georeferenced, error-checked and subsequently taxonomically aligned between the HMW (6253 species), the CMW (6431 species) and the MDD taxonomies (6362 species).ResultsRange maps can be evaluated and visualised in an online map browser at Map of Life (mol.org) and accessed for individual or batch download for non-commercial use.Main conclusionExpert maps of species' global distributions are limited in their spatial detail and temporal specificity, but form a useful basis for broad-scale characterizations and model-based integration with other data. We provide georeferenced range maps for the native ranges of all extant mammal species as shapefiles, with species-level metadata and source information packaged together in geodatabase format. Across the three taxonomic sources our maps entail, there are 1784 taxonomic name differences compared to the maps currently available on the IUCN Red List website. The expert maps provided here are harmonised to the MDD taxonomic authority and linked to a community of online tools that will enable transparent future updates and version control
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