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The surface flooding of Antarctic sea ice in summer covers 50% or more of the sea-ice area in the major summer ice packs, the western Weddell and the Bellingshausen-Amundsen Seas. Two CRREL ice mass-balance buoys were deployed on the Amundsen Sea pack in late December 2010 from the icebreaker Oden, bridging the summer period (January–February 2011). Temperature records from thermistors embedded vertically in the snow and ice showed progressive increases in the depth of the flooded layer (up to 0.3–0.35 m) on the ice cover during January and February. While the snow depth was relatively unchanged from accumulation (<10 cm), ice thickness decreased by up to a meter from bottom melting during this period. Contemporaneous with the high bottom melting, under-ice water temperatures up to 1°C above the freezing point were found. The high temperature arises from solar heating of the upper mixed layer which can occur when ice concentration in the local area falls and lower albedo ocean water is exposed to radiative heating. The higher proportion of snow ice found in the Amundsen Sea pack ice therefore results from both winter snowfall and summer ice bottom melt found here that can lead to extensive surface flooding.

The potential of remotely sensed time series of biophysical states of landscape to characterize soil moisture condition antecedent to radar estimates of precipitation is assessed in a statistical prediction model of streamflow in a 1,420 km2 watershed in south-central Texas, Moderate Resolution Imaging Spectroradiometer (MODIS) time series biophysical products offer significant opportunities to characterize and quantify hydrologic state variables such as land surface temperature (LST) and vegetation state and status. Together with Next Generation Weather Radar (NEXRAD) precipitation estimates for the period 2002 through 2005, 16 raw and deseasoned time series of LST (day and night), vegetation indices, infrared reflectances, and water stress indices were linearly regressed against observed watershed streamflow on an eight-day aggregated time period. Time offsets of 0 (synchronous with streamflow event), 8, and 16 days (leading streamflow event) were assessed for each of the 16 parameters to evaluate antecedent effects. The model results indicated a reasonable correlation (r2 = 0.67) when precipitation, daytime LST advanced 16 days, and a deseasoned moisture stress index were regressed against log-transformed streamflow. The estimation model was applied to a validation period from January 2006 through March 2007, a period of 12 months of regional drought and base-flow conditions followed by three months of above normal rainfall and a flood event. The model resulted in a Nash-Sutcliffe estimation efficiency (E) of 0.45 for flow series (in log-space) for the full 15-month period, -0.03 for the 2006 drought condition period, and 0.87 for the 2007 wet condition period. The overall model had a relative volume error of -32%. The contribution of parameter uncertainties to model discrepancy was evaluated.

:  The potential of remotely sensed time series of biophysical states of landscape to characterize soil moisture condition antecedent to radar estimates of precipitation is assessed in a statistical prediction model of streamflow in a 1,420 km2 watershed in south‐central Texas, Moderate Resolution Imaging Spectroradiometer (MODIS) time series biophysical products offer significant opportunities to characterize and quantify hydrologic state variables such as land surface temperature (LST) and vegetation state and status. Together with Next Generation Weather Radar (NEXRAD) precipitation estimates for the period 2002 through 2005, 16 raw and deseasoned time series of LST (day and night), vegetation indices, infrared reflectances, and water stress indices were linearly regressed against observed watershed streamflow on an eight‐day aggregated time period. Time offsets of 0 (synchronous with streamflow event), 8, and 16 days (leading streamflow event) were assessed for each of the 16 parameters to evaluate antecedent effects. The model results indicated a reasonable correlation (r2 = 0.67) when precipitation, daytime LST advanced 16 days, and a deseasoned moisture stress index were regressed against log‐transformed streamflow. The estimation model was applied to a validation period from January 2006 through March 2007, a period of 12 months of regional drought and base‐flow conditions followed by three months of above normal rainfall and a flood event. The model resulted in a Nash‐Sutcliffe estimation efficiency (E) of 0.45 for flow series (in log‐space) for the full 15‐month period, −0.03 for the 2006 drought condition period, and 0.87 for the 2007 wet condition period. The overall model had a relative volume error of −32%. The contribution of parameter uncertainties to model discrepancy was evaluated.

Satellites have documented variability in sea ice areal extent for decades, but there are significant challenges in obtaining analogous measurements for sea ice thickness data in the Antarctic, primarily due to difficulties in estimating snow cover on sea ice. Sea ice thickness (SIT) can be estimated from snow freeboard measurements, such as those from airborne/satellite lidar, by assuming some snow depth distribution or empirically fitting with limited data from drilled transects from various field studies. Current estimates for large-scale Antarctic SIT have errors as high as ∼50 %, and simple statistical models of small-scale mean thickness have similarly high errors. Averaging measurements over hundreds of meters can improve the model fits to existing data, though these results do not necessarily generalize to other floes. At present, we do not have algorithms that accurately estimate SIT at high resolutions. We use a convolutional neural network with laser altimetry profiles of sea ice surfaces at 0.2 m resolution to show that it is possible to estimate SIT at 20 m resolution with better accuracy and generalization than current methods (mean relative errors ∼15 %). Moreover, the neural network does not require specification of snow depth or density, which increases its potential applications to other lidar datasets. The learned features appear to correspond to basic morphological features, and these features appear to be common to other floes with the same climatology. This suggests that there is a relationship between the surface morphology and the ice thickness. The model has a mean relative error of 20 % when applied to a new floe from the region and season. This method may be extended to lower-resolution, larger-footprint data such as such as Operation IceBridge, and it suggests a possible avenue to reduce errors in satellite estimates of Antarctic SIT from ICESat-2 over current methods, especially at smaller scales.

Most of the world’s mountain glaciers have been retreating for more than a century in response to climate change. Glacier retreat is evident on all continents, and the rate of retreat has accelerated during recent decades. Accurate, spatially explicit information on the position of glacier margins over time is useful for analyzing patterns of glacier retreat and measuring reductions in glacier surface area. This information is also essential for evaluating how mountain ecosystems are evolving due to climate warming and the attendant glacier retreat. Here, we present a non-comprehensive spatially explicit dataset showing multiple positions of glacier fronts since the Little Ice Age (LIA) maxima, including many data from the pre-satellite era. The dataset is based on multiple historical archival records including topographical maps; repeated photographs, paintings, and aerial or satellite images with a supplement of geochronology; and own field data. We provide ESRI shapefiles showing 728 past positions of 94 glacier fronts from all continents, except Antarctica, covering the period between the Little Ice Age maxima and the present. On average, the time series span the past 190 years. From 2 to 46 past positions per glacier are depicted (on average: 7.8).

Adults of Derbidae (Hemiptera: Auchenorrhyncha) are common on foliage of Palmae in many tropical localities; their larvae are believed to develop in decaying debris. The larval stage of Cedusa inflata (Ball), a derbid common on palms in Florida and the Caribbean Region, was observed and is figured for the first time, and its habitat, decaying organic debris, was documented. In plantings of coconut palm, a mean of 56.1 larvae of C. inflata solitary or in aggregations of up to 13 individuals were found in each of 10 piles of organic debris from the palms. The larvae were in moist places in the interior of debris piles usually near fungal mycelia, their presumed food resource. Sparse numbers (x = 6.06) of C. inflata adults were observed on foliage of each of 10 palms adjacent to piles of organic debris, but were virtually absent from 10 palms >15 m from debris piles. These observations have implications for decaying debris as the assumed larval habitat of derbid species found as adults on palms in many tropical countries. /// Adultos de Derbidae (Hemiptera: Auchenorrhyncha) son comunes sobre el follaje de Palmae en muchas localidades tropicales; se suponen que sus larvas se desarrollan sobre detrito orgánico podrido. La larva de Cedusa inflata (Ball), un dérbido común sobre las palmeras en Florida y la Región Caribeña, fue observada e ilustrada por primera vez, y su hábitat, detrito orgánico podrido, fue documentado. En plantíos de palma de coco un promedio de 56.1 larvas de C. inflata, o solitario o en agregaciones de hasta 13 individuos, fueron encontrados en cada uno de 10 montones de detrito orgánico de las palmas. Las larvas estaban en lugares húmidos en el interior de los montones y usualmente estaban cerca de micelios de hongos, su recurso alimenticioso presumido. Números esparcidos (x = 6.06) de los adultos de C. inflata fueron observados sobre follaje de cada una de 10 palmeras adyacentes a montones de detrito orgánico, pero fueron virtualmente ausentes de 10 palmeras >15 m de distancia de montones de detritos. Estas observaciones tienen implicaciones para el detrito podrido como el habitat presumido de las larvas de especies de dérbidos que se encuentran sobre las palmeras in muchos países tropicales.

We documented the decline of a 2-hectare Canary Island date palm (Phoenix canariensis) nursery caused by the palmetto weevil (Rhynchophorus cruentatus) in Dade County, FL. External palm symptoms were defined, divided into nine categories, and representative palms were destructively harvested to assess internal weevil associations. Apparently healthy palms declined and died in a mean of 49 days. At the beginning of the study, 42% of 950 palms appeared healthy but within seven months only 3% were alive. Economic losses were estimated at $285,000-$380,000 for the nursery studied. Palm decline was patchily distributed in the field. The mean palm weevil counts ranged from 0.3 to 223.3 weevils per palm, for healthy to collapsing palms, respectively. Twenty-four weevil grubs were sufficient to kill one mature palm. External symptoms did not allow preventative diagnosis and treatment of internal R. cruentatus infestations. By the time that external symptoms were unambiguous, the mean total weevil counts per palm were over 100 with more than 65% as larvae and more than one quarter of these were >2.5 cm in length. Palms in these categories were dying because of irreparable damage to their apical meristems and attempts to save them would have been ineffectual. Thus, phytosanitation (palm removal and destruction) for management of R. cruentatus in Canary Island date palms should be implemented as soon as host leaves droop and weevil frass is observed. Growers and buyers of P. canariensis in regions where R. cruentatus exists should be aware of the potential lethal risk that it poses for this non-native palm. The costs of aggressive phytosanitation at the first symptoms of R. cruentatus infestation and prophylactic pesticide treatment at times of pruning, stress, or transplanting should be factored into the predicted cost of production and maintenance of Canary Island date palms in Florida. /// Documentamos el deterioro de un vivero de 2-hectáreas de palmas datileras Isla Canaria (Phoenix canariensis) causado por el gorgojo \"palmetto\" (Rhynchophorus cruentatus) en el condado de Miami-Dade, FL. Síntomas externos de la palma fueron definidos, divididos en nueve categorías, y palmas representativas fueron cosechadas destructivamente para evaluar asociaciones internas de los gorgojos. Palmas aparentemente saludables se deterioraron y murieron en un promedio de 49 días. Al comienzo del estudio, 42% de 950 palmas parecían saludables pero dentro de siete meses solo el 3% estaban vivas. Pérdidas económicas fueron estimadas entre $285.000-$380.000 para el vivero del estudio. El deterioro de las palmas en el campo fue distribuido irregularmente. Cuentas de promedios de gorgojos variaron entre 0,3 y 223,3 gorgojos por palma, de palmas saludables a enfermas, respectivamente. Veinticuatro orugas de gorgojo fueron suficiente para matar una palma madura. Síntomas externos no permitieron diagnosis preventivo y tratamientos de infestaciones internas de R. cruentatus. Para el momento en que los síntomas externos eran inequívocos, la cuenta promedio total de gorgojos por palma era sobre 100 con mas de 65% en forma de larva y mas de un cuarto de estos tenían un largo de > 2,5 cm. Palmas en estas categorías morían por daño irreparable a su meristemo apical e intentos para salvarlos hubieran resultado inútiles. Por lo tanto, fito-saneamiento (la practica de remover y destruir las palmas) para administración de R. cruentatus en palmas datileras Isla Canaria debería ser implementado en cuanto las hojas del huésped se inclinen y se observen residuos de daño de gorgojo. Vendedores y compradores de P. canariensis en regiones donde R. cruentatus existe deben estar al tanto de este riesgo potencialmente letal para esta palma no-nativa. El costo de fito-saneamiento agresivo en los primeros síntomas de infestación de R. cruentatus y tratamiento de pesticida profiláctico en momentos de podar, estrés, o transplante deben de ser facturados en los costos predichos de producción y mantenimiento de palmas datileras Isla Canaria en la Florida.

Metamasius hemipterus sericeus (Olivier) is a widely distributed weevil in Central and South America, as well as the West Indies. It was introduced into Florida, Miami-Dade County, in 1984. This insect generally is regarded as a secondary pest of sugarcane, bananas, palms and several other tropical plants grown as ornamentals. Larvae bore into stems and petioles, thus weakening the plant and providing a pathway for penetration by fungi or other pests. In addition to investigating the biology, this study was conducted to gather basic information to help optimize culturing efforts for large numbers of M. h. sericeus to be used for mass rearing of potential biological control organisms. After pairing males and females, it took an average of 27.0 days for females to begin oviposition. The oviposition period lasted 56.8 days. Females lived 142.3 days and laid an average of 51.6 eggs. Mean generation time was 63 days. Mean egg production during the oviposition period was 1.1 eggs/day. Egg eclosion averaged 81.3% during the oviposition period.

We provide the first experimental cross section of the \\(^{73}\\text{As}(p,\\gamma)^{74}\\text{Se}\\) reaction to constrain one of the main destruction mechanisms of the p nucleus \\(^{74}\\text{Se}\\) in explosive stellar environments. The measurement was done using a radioactive \\(^{73}\\text{As}\\) beam at effective center-of-mass energies of 2.9 and 2.3 MeV/nucleon. Along with the total cross-section measurement, statistical properties of the \\(^{74}\\text{Se}\\) compound nucleus were extracted, constraining the reaction cross section in the upper Gamow window of the \\(\\gamma\\) process. The impact of the experimentally constrained reaction rate on \\(^{74}\\text{Se}\\) production in Type II supernovae was investigated through Monte Carlo one-zone network simulations. The results indicate that the overproduction of \\(^{74}\\)Se by Type II supernova models cannot be resolved by nuclear physics alone and point toward the need for a more detailed understanding of the astrophysical conditions of relevance for the \\(\\gamma\\) process.

The Giant Radio Array for Neutrino Detection (GRAND) is a proposed multi-messenger observatory of Ultra-High-Energy (UHE) particles of cosmic origin. Its main goal is to find the long-sought origin of UHE cosmic rays by detecting large numbers of them and the secondary particles created by their interactions like gamma rays and neutrinos. The GRAND Collaboration plans to achieve this using large arrays of radio antennas that look for the radio signals emitted by the air showers initiated by the interactions of the UHE particles in the atmosphere. Since 2023, three small-scale prototype GRAND arrays have been in operation: GRAND@Nançay in France, GRAND@Auger in Argentina, and GRANDProto300 in China. Together, their goal is to validate the detection principle of GRAND under prolonged field conditions, achieving efficient, autonomous radio-detection of air showers. We describe the hardware, software, layout, and operation of the GRAND prototypes. Using their data, we show a first characterization of the local electromagnetic environment of each site and a measurement of the Galactic synchrotron emission. Despite challenges, the successful operation of the prototypes confirms that the GRAND instrumentation is apt to address the goals of the experiment and lays the groundwork for its ensuing stages.