4 research outputs found

    A globally relevant change taxonomy and evidence-based change framework for land monitoring

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    A globally relevant and standardized taxonomy and framework for consistently describing land cover change based on evidence is presented, which makes use of structured land cover taxonomies and is underpinned by the Driver-Pressure-State-Impact-Response (DPSIR) framework. The Global Change Taxonomy currently lists 246 classes based on the notation 'impact (pressure)', with this encompassing the consequence of observed change and associated reason(s), and uses scale-independent terms that factor in time. Evidence for different impacts is gathered through temporal comparison (e.g., days, decades apart) of land cover classes constructed and described from Environmental Descriptors (EDs; state indicators) with pre-defined measurement units (e.g., m, %) or categories (e.g., species type). Evidence for pressures, whether abiotic, biotic or human-influenced, is similarly accumulated, but EDs often differ from those used to determine impacts. Each impact and pressure term is defined separately, allowing flexible combination into 'impact (pressure)' categories, and all are listed in an openly accessible glossary to ensure consistent use and common understanding. The taxonomy and framework are globally relevant and can reference EDs quantified on the ground, retrieved/classified remotely (from ground-based, airborne or spaceborne sensors) or predicted through modelling. By providing capacity to more consistently describe change processes-including land degradation, desertification and ecosystem restoration-the overall framework addresses a wide and diverse range of local to international needs including those relevant to policy, socioeconomics and land management. Actions in response to impacts and pressures and monitoring towards targets are also supported to assist future planning, including impact mitigation actions

    A globally relevant change taxonomy and evidence-based change framework for land monitoring

    Get PDF
    A globally relevant and standardized taxonomy and framework for consistently describing land cover change based on evidence is presented, which makes use of structured land cover taxonomies and is underpinned by the Driver-Pressure-State�Impact-Response (DPSIR) framework. The Global Change Taxonomy currently lists 246 classes based on the notation ‘impact (pressure)’, with this encompassing the consequence of observed change and associated reason(s), and uses scale-independent terms that factor in time. Evidence for different impacts is gathered through temporal comparison (e.g., days, decades apart) of land cover classes constructed and described from Environmental Descriptors (EDs; state indicators) with pre-defined measurement units (e.g., m, %) or categories (e.g., species type). Evidence for pressures, whether abiotic, biotic or human-influenced, is similarly accumulated, but EDs often differ from those used to determine impacts. Each impact and pressure term is defined separately, allowing flexible combination into ‘impact (pressure)’ categories, and all are listed in an openly accessible glossary to ensure consistent use and common understanding. The taxonomy and framework are globally relevant and can reference EDs quantified on the ground, retrieved/classified remotely (from groundbased, airborne or spaceborne sensors) or predicted through modelling. By providing capacity to more consistently describe change processes—including land degradation, desertification and ecosystem restoration—the overall framework addresses a wide and diverse range of local to international needs including those relevant to policy, socioeconomics and land management. Actions in response to impacts and pressures and monitoring towards targets are also supported to assist future planning, including impact mitigation actions

    Galaxy And Mass Assembly (GAMA): The mechanisms for quiescent galaxy formation at z < 1

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    One key problem in astrophysics is understanding how and why galaxies switch off their star formation, building the quiescent population that we observe in the local Universe. From the Galaxy And Mass Assembly and VIsible MultiObject Spectrograph Public Extragalactic Redshift surveys, we use spectroscopic indices to select quiescent and candidate transition galaxies.We identify potentially rapidly transitioning post-starburst (PSB) galaxies and slower transitioning green-valley galaxies. Over the last 8Gyr, the quiescent population has grown more slowly in number density at high masses (M* > 1011M⊙) than at intermediate masses (M* > 1010.6M⊙). There is evolution in both the PSB and green-valley stellar mass functions, consistent with higher mass galaxies quenching at earlier cosmic times.At intermediatemasses (M* > 1010.6M⊙), we find a green-valley transition time-scale of 2.6 Gyr. Alternatively, at z ~ 0.7, the entire growth rate could be explained by fast-quenching PSB galaxies, with a visibility time-scale of 0.5 Gyr. At lower redshift, the number density of PSBs is so low that an unphysically short visibility window would be required for them to contribute significantly to the quiescent population growth. The importance of the fast-quenching route may rapidly diminish at z 1011M⊙), there is tension between the large number of candidate transition galaxies compared to the slow growth of the quiescent population. This could be resolved if not all high-mass PSB and green-valley galaxies are transitioning from star forming to quiescent, for example if they rejuvenate out of the quiescent population following the accretion of gas and triggering of star formation, or if they fail to completely quench their star formationVW and KR acknowledge support from the European Research Council Starting Grant SEDmorph (PI: VW). GAMA is a joint EuropeanAustralasian project based around a spectroscopic campaign using the Anglo-Australian Telescope. The GAMA input catalogue is based on data taken from the SDSS and the UKIRT Infrared Deep Sky Survey. Complementary imaging of the GAMA regions is being obtained by a number of independent survey programs including GALEX MIS, VST KIDS, VISTA VIKING, WISE, Herschel-ATLAS, GMRT and ASKAP providing UV to radio coverage. GAMA is funded by the STFC (UK), the ARC (Australia), the AAO and the participating institutions. The GAMA website is http://www.gama-survey.org/. Based on observations made with ESO Telescopes at the La Silla Paranal Observatory under programme ID 179.A-2004. This paper uses data from the VIMOS Public Extragalactic Redshift Survey (VIPERS). VIPERS has been performed using the ESO Very Large Telescope, under the ‘Large Programme’ 182.A-0886. The participating institutions and funding agencies are listed at http://vipers.inaf.it This research has made use of NASA’s Astrophysics Data System Bibliographic Services
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