Measurement of Diurnal Variation in Needle PRI and Shoot Photosynthesis in a Boreal Forest

This article has an erratum: Remote Sens. 2018. 10, 2030. DOI 10.3390/rs10122030. WOS: 000455637600172Peer reviewe

Detecting Inter-Annual Variations in the Phenology of Evergreen Conifers Using Long-Term MODIS Vegetation Index Time Series

Long-term observations of vegetation phenology can be used to monitor the response of terrestrial ecosystems to climate change. Satellite remote sensing provides the most efficient means to observe phenological events through time series analysis of vegetation indices such as the Normalized Difference Vegetation Index (NDVI). This study investigates the potential of a Photochemical Reflectance Index (PRI), which has been linked to vegetation light use efficiency, to improve the accuracy of MODIS-based estimates of phenology in an evergreen conifer forest. Timings of the start and end of the growing season (SGS and EGS) were derived from a 13-year-long time series of PRI and NDVI based on a MAIAC (multi-angle implementation of atmospheric correction) processed MODIS dataset and standard MODIS NDVI product data. The derived dates were validated with phenology estimates from ground-based flux tower measurements of ecosystem productivity. Significant correlations were found between the MAIAC time series and ground-estimated SGS (R-2 = 0.36-0.8), which is remarkable since previous studies have found it difficult to observe inter-annual phenological variations in evergreen vegetation from satellite data. The considerably noisier NDVI product could not accurately predict SGS, and EGS could not be derived successfully from any of the time series. While the strongest relationship overall was found between SGS derived from the ground data and PRI, MAIAC NDVI exhibited high correlations with SGS more consistently (R-2 > 0.6 in all cases). The results suggest that PRI can serve as an effective indicator of spring seasonal transitions, however, additional work is necessary to confirm the relationships observed and to further explore the usefulness of MODIS PRI for detecting phenology.Peer reviewe

Diurnal and Seasonal Solar Induced Chlorophyll Fluorescence and Photosynthesis in a Boreal Scots Pine Canopy

Solar induced chlorophyll fluorescence has been shown to be increasingly an useful proxy for the estimation of gross primary productivity (GPP), at a range of spatial scales. Here, we explore the seasonality in a continuous time series of canopy solar induced fluorescence (hereafter SiF) and its relation to canopy gross primary production (GPP), canopy light use efficiency (LUE), and direct estimates of leaf level photochemical efficiency in an evergreen canopy. SiF was calculated using infilling in two bands from the incoming and reflected radiance using a pair of Ocean Optics USB2000+ spectrometers operated in a dual field of view mode, sampling at a 30 min time step using custom written automated software, from early spring through until autumn in 2011. The optical system was mounted on a tower of 18 m height adjacent to an eddy covariance system, to observe a boreal forest ecosystem dominated by Scots pine. (Pinus sylvestris) A Walz MONITORING-PAM, multi fluorimeter system, was simultaneously mounted within the canopy adjacent to the footprint sampled by the optical system. Following correction of the SiF data for O2 and structural effects, SiF, SiF yield, LUE, the photochemicsl reflectance index (PRI), and the normalized difference vegetation index (NDVI) exhibited a seasonal pattern that followed GPP sampled by the eddy covariance system. Due to the complexities of solar azimuth and zenith angle (SZA) over the season on the SiF signal, correlations between SiF, SiF yield, GPP, and LUE were assessed on SZ

Quantifying the impact of avian influenza on the northern gannet colony of Bass Rock using ultra-high-resolution drone imagery and deep learning

Drones are an increasingly popular choice for wildlife surveys due to their versatility, quick response capabilities, and ability to access remote areas while covering large regions. A novel application presented here is to combine drone imagery with neural networks to assess mortality within a bird colony. Since 2021, Highly Pathogenic Avian Influenza (HPAI) has caused significant bird mortality in the UK, mainly affecting aquatic bird species. The world’s largest northern gannet colony on Scotland’s Bass Rock experienced substantial losses in 2022 due to the outbreak. To assess the impact, RGB imagery of Bass Rock was acquired in both 2022 and 2023 by deploying a drone over the island for the first time. A deep learning neural network was subsequently applied to the data to automatically detect and count live and dead gannets, providing population estimates for both years. The model was trained on the 2022 dataset and achieved a mean average precision (mAP) of 37%. Application of the model predicted 18,220 live and 3761 dead gannets for 2022, consistent with NatureScot’s manual count of 21,277 live and 5035 dead gannets. For 2023, the model predicted 48,455 live and 43 dead gannets, and the manual count carried out by the Scottish Seabird Centre and UK Centre for Ecology and Hydrology (UKCEH) of the same area gave 51,428 live and 23 dead gannets. This marks a promising start to the colony’s recovery with a population increase of 166% determined by the model. The results presented here are the first known application of deep learning to detect dead birds from drone imagery, showcasing the methodology’s swift and adaptable nature to not only provide ongoing monitoring of seabird colonies and other wildlife species but also to conduct mortality assessments. As such, it could prove to be a valuable tool for conservation purposes

The XMM Cluster Survey: evolution of the velocity dispersion–temperature relation over half a Hubble time

We measure the evolution of the velocity dispersion–temperature (σv–TX) relation up to z = 1 using a sample of 38 galaxy clusters drawn from the XMM Cluster Survey. This work improves upon previous studies by the use of a homogeneous cluster sample and in terms of the number of high-redshift clusters included. We present here new redshift and velocity dispersion measurements for 12 z > 0.5 clusters observed with the Gemini Multi Object Spectographs instruments on the Gemini telescopes. Using an orthogonal regression method,we find that the slope of the relation is steeper than that expected if clusters were self-similar, and that the evolution of the normalization is slightly negative, but not significantly different from zero (σv ∝T0.86±0.14E(z)−0.37±0.33). We verify our results by applying our methods to cosmological hydrodynamical simulations. The lack of evolution seen in our data is consistent with simulations that include both feedback and radiative cooling

Executive summary: heart disease and stroke statistics--2014 update: a report from the American Heart Association.

Each year, the American Heart Association (AHA), in conjunction with the Centers for Disease Control and Prevention, the National Institutes of Health, and other government agencies, brings together the most up-to-date statistics on heart disease, stroke, other vascular diseases, and their risk factors and presents them in its Heart Disease and Stroke Statistical Update. The Statistical Update is a critical resource for researchers, clinicians, healthcare policy makers, media professionals, the lay public, and many others who seek the best available national data on heart disease, stroke, and other cardiovascular disease-related morbidity and mortality and the risks, quality of care, use of medical procedures and operations, and costs associated with the management of these diseases in a single document. Indeed, since 1999, the Statistical Update has been cited >10 500 times in the literature, based on citations of all annual versions. In 2012 alone, the various Statistical Updates were cited ≈3500 times (data from Google Scholar). In recent years, the Statistical Update has undergone some major changes with the addition of new chapters and major updates across multiple areas, as well as increasing the number of ways to access and use the information assembled. For this year's edition, the Statistics Committee, which produces the document for the AHA, updated all of the current chapters with the most recent nationally representative data and inclusion of relevant articles from the literature over the past year. This year's edition includes a new chapter on peripheral artery disease, as well as new data on the monitoring and benefits of cardiovascular health in the population, with additional new focus on evidence-based approaches to changing behaviors, implementation strategies, and implications of the AHA's 2020 Impact Goals. Below are a few highlights from this year's Update. © 2013 American Heart Association, Inc

Executive summary: heart disease and stroke statistics--2013 update: a report from the American Heart Association.

Each year, the American Heart Association (AHA), in conjunction with the Centers for Disease Control and Prevention, the National Institutes of Health, and other government agencies, brings together the most up-to-date statistics on heart disease, stroke, other vascular diseases, and their risk factors and presents them in its Heart Disease and Stroke Statistical Update*The Statistical Update is a valuable resource for researchers, clinicians, healthcare policy makers, media professionals, the lay public, and many others who seek the best national data available on heart disease, stroke, and other cardiovascular disease-related morbidity and mortality and the risks, quality of care, medical procedures and operations, and costs associated with the management of these diseases in a single document*Indeed, since 1999, the Statistical Update has been cited \u3e10 500 times in the literature, based on citations of all annual versions*In 2011 alone, the various Statistical Updates were cited ≈1500 times (data from ISI Web of Science)*In recent years, the Statistical Update has undergone some major changes with the addition of new chapters and major updates across multiple areas, as well as increasing the number of ways to access and use the information assembled*For this year\u27s edition, the Statistics Committee, which produces the document for the AHA, updated all of the current chapters with the most recent nationally representative data and inclusion of relevant articles from the literature over the past year*This year\u27s edition also implements a new chapter organization to reflect the spectrum of cardiovascular health behaviors and health factors and risks, as well as subsequent complicating conditions, disease states, and outcomes*Also, the 2013 Statistical Update contains new data on the monitoring and benefits of cardiovascular health in the population, with additional new focus on evidence-based approaches to changing behaviors, implementation strategies, and implications of the AHA\u27s 2020 Impact Goals*Below are a few highlights from this year\u27s Update . © 2013 American Heart Association, Inc

Estimation of Light-use Efficiency of Terrestrial Ecosystem from Space: A Status Report

A critical variable in the estimation of gross primary production of terrestrial ecosystems is light-use efficiency (LUE), a value that represents the actual efficiency of a plant's use of absorbed radiation energy to produce biomass. Light-use efficiency is driven by the most limiting of a number of environmental stress factors that reduce plants' photosynthetic capacity; these include short-term stressors, such as photoinhibition, as well as longer-term stressors, such as soil water and temperature. Modeling LUE from remote sensing is governed largely by the biochemical composition of plant foliage, with the past decade seeing important theoretical and modeling advances for understanding the role of these stresses on LUE. In this article we provide a summary of the tower-, aircraft-, and satellite-based research undertaken to date, and discuss the broader scalability of these methods, concluding with recommendations for ongoing research possibilities

The Eleventh and Twelfth Data Releases of the Sloan Digital Sky Survey: Final Data from SDSS-III

The third generation of the Sloan Digital Sky Survey (SDSS-III) took data from 2008 to 2014 using the original SDSS wide-field imager, the original and an upgraded multi-object fiber-fed optical spectrograph, a new near-infrared high-resolution spectrograph, and a novel optical interferometer. All of the data from SDSS-III are now made public. In particular, this paper describes Data Release 11 (DR11) including all data acquired through 2013 July, and Data Release 12 (DR12) adding data acquired through 2014 July (including all data included in previous data releases), marking the end of SDSS-III observing. Relative to our previous public release (DR10), DR12 adds one million new spectra of galaxies and quasars from the Baryon Oscillation Spectroscopic Survey (BOSS) over an additional 3000 deg2 of sky, more than triples the number of H-band spectra of stars as part of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE), and includes repeated accurate radial velocity measurements of 5500 stars from the Multi-object APO Radial Velocity Exoplanet Large-area Survey (MARVELS). The APOGEE outputs now include the measured abundances of 15 different elements for each star. In total, SDSS-III added 5200 deg2 of ugriz imaging; 155,520 spectra of 138,099 stars as part of the Sloan Exploration of Galactic Understanding and Evolution 2 (SEGUE-2) survey; 2,497,484 BOSS spectra of 1,372,737 galaxies, 294,512 quasars, and 247,216 stars over 9376 deg2; 618,080 APOGEE spectra of 156,593 stars; and 197,040 MARVELS spectra of 5513 stars. Since its first light in 1998, SDSS has imaged over 1/3 of the Celestial sphere in five bands and obtained over five million astronomical spectra. \ua9 2015. The American Astronomical Society