Gamma rays from dark matter annihilation in the Draco and observability at ARGO

The CACTUS experiment recently observed a gamma ray excess above 50 GeV from the direction of the Draco dwarf spheroidal galaxy. Considering that Draco is dark matter dominated the gamma rays may be generated through dark matter annihilation in the Draco halo. In the framework of the minimal supersymmetric extension of the standard model we explore the parameter space to account for the gamma ray signals at CACTUS. We find that the neutralino mass is constrained to be approximately in the range between 100 GeV ~ 400 GeV and a sharp central cuspy of the dark halo profile in Draco is necessary to explain the CACTUS results. We then discuss further constraints on the supersymmetric parameter space by observations at the ground based ARGO detector. It is found that the parameter space can be strongly constrained by ARGO if no excess from Draco is observed above 100 GeV.Comment: 15 pages, 4 figure

Detecting the dark matter annihilation at the ground EAS detectors

In this paper we study the possibility of detecting gamma rays from dark matter annihilation in the subhalos of the Milky Way by the ground based EAS detectors within the frame of the minimal supersymmetric standard model. Based on the Monte Carlo simulation we also study the properties of two specific EAS detectors, the ARGO and HAWC, and the sensitivities of these detectors on the detection of dark matter annihilation. We find the ground EAS detectors have the possibility to observe such signals. Conversely if no signal observed we give the constraints on the supersymmetric parameter space, which however depends on the subhalos properties.Comment: 23 pages, 9 figures, accepted by NP

Gamma rays from the neutralino dark matter annihilations in the Milky Way substructures

High resolution simulations reveal that in the cold dark matter scenario the structures form hierarchically and a large number of substructures survive in the galactic halos. The substructures can be probed if they emit gamma rays via dark matter annihilation. We calculated the gamma ray fluxes from the dark matter annihilations in the substructures of our Galaxy within the frame of the minimal supersymmetric extension of the standard model. The uncertainties of the prediction from both the low energy supersymmetry and especially from the density profiles of dark matter in the substructures are carefully investigated. The cumulative number of substructures emitting gamma rays above any given flux is calculated. Detectability of the gamma rays from the substructures is discussed. We propose the viability to detect these signals through the ground large field of view detectors.Comment: 34 pages, 10 figures, 1 table; discussion on mSUGRA model is added, references are adde

Impacts of land use and land cover change on surface runoff, discharge and low flows: evidence from East Africa

Region: East Africa. Focus: A review of catchment studies (n=37) conducted in East Africa evaluating the impacts of Land Use and Land Cover Changes (LULCC) on discharge, surface runoff, and low flows. New hydrological insights: Forest cover loss is accompanied by increased stream discharges and surface runoff. No significant difference in stream discharge is observed between bamboo and pine plantation catchments, and between cultivated and tea plantation catchments. Trend analyses show that despite forest cover loss, 63% of the watersheds show non-significant changes in annual discharges while 31% show increasing trends. Half of the watersheds show non-significant trends in wet season flows and low flows while 35% reveal decreasing trends in low flows. Modeling studies estimate that forest cover loss increases annual discharges and surface runoff by 16 ± 5.5% and 45 ± 14%, respectively. Peak flows increased by a mean of 10 ± 2.8% while low flows decreased by a mean of 7 ± 5.3%. Increased forest cover decreases annual discharges and surface runoff by 13 ± 1.9% and 25 ± 5%, respectively. Weak correlations between forest cover and runoff (r=0.42, p < 0.05), mean discharge (r=0.63, p < 0.05) and peak discharge (r=0.67, p < 0.05) indicate that forest cover alone is not an accurate predictor of hydrological fluxes in East African catchments. The variability in these results supports the need for long-term field monitoring to better understand catchment responses and to improve the calibration of currently used simulation models

A Frameshift Mutation in Golden Retriever Dogs with Progressive Retinal Atrophy Endorses SLC4A3 as a Candidate Gene for Human Retinal Degenerations

Progressive retinal atrophy (PRA) in dogs, the canine equivalent of retinitis pigmentosa (RP) in humans, is characterised by vision loss due to degeneration of the photoreceptor cells in the retina, eventually leading to complete blindness. It affects more than 100 dog breeds, and is caused by numerous mutations. RP affects 1 in 4000 people in the Western world and 70% of causal mutations remain unknown. Canine diseases are natural models for the study of human diseases and are becoming increasingly useful for the development of therapies in humans. One variant, prcd-PRA, only accounts for a small proportion of PRA cases in the Golden Retriever (GR) breed. Using genome-wide association with 27 cases and 19 controls we identified a novel PRA locus on CFA37 (praw = 1.94×10−10, pgenome = 1.0×10−5), where a 644 kb region was homozygous within cases. A frameshift mutation was identified in a solute carrier anion exchanger gene (SLC4A3) located within this region. This variant was present in 56% of PRA cases and 87% of obligate carriers, and displayed a recessive mode of inheritance with full penetrance within those lineages in which it segregated. Allele frequencies are approximately 4% in the UK, 6% in Sweden and 2% in France, but the variant has not been found in GRs from the US. A large proportion of cases (approximately 44%) remain unexplained, indicating that PRA in this breed is genetically heterogeneous and caused by at least three mutations. SLC4A3 is important for retinal function and has not previously been associated with spontaneously occurring retinal degenerations in any other species, including humans

Combining literature-based and data-driven fuzzy models to predict brown trout (salmo trutta l.) spawning habitat degradation induced by climate change

[EN] A fuzzy rule-based system combining empirical data on hydraulic preferences and literature information on temperature requirements was used to foresee the brown trout (Salmo trutta L.) spawning habitat degradation induced by climate change. The climatic scenarios for the Cabriel River (Eastern Iberian Peninsula) corresponded to two Representative Concentration Pathways (4.5 and 8.5) for the short (2011¿2040) and mid (2041¿2070) term horizons. The hydraulic and hydrologic modelling were undertaken with process-based numerical models (i.e., River2D© and HBV-light) while the water temperature was modelled by assembling the predictions of three machine learning techniques (M5, Multi-Adaptive Regression Splines and Support Vector Regression). The predicted rise in the water temperature will not be compensated by the more benign lower flows. Consequently, the suitable spawning habitat will be reduced between 15.4¿48.7%. The entire population shall suffer the effects of climate change and will probably be extirpated from the downstream segments of the river.The study has been partially funded by the IMPADAPT project (CGL2013-48424-C2-1-R) with Spanish MINECO (Ministerio de Economía y Competitividad) and FEDER funds and by the Confederación Hidrográfica del Júcar (Spanish Ministry of Agriculture, Food and Environment). The authors thank AEMET and UC for the data provided for this work (dataset Spain02). Finally, we are grateful to the colleagues who worked in the field and in preliminary data analyses; especially Marcello Minervini (funded by the EU programme of Erasmus Traineeships, at the Dept. of Hydraulic Engineering and Environment, Universitat Politècnica de València).Muñoz Mas, R.; Marcos-García, P.; Lopez-Nicolas, A.; Martínez-García, F.; Pulido-Velazquez, M.; Martinez-Capel, F. (2018). Combining literature-based and data-driven fuzzy models to predict brown trout (salmo trutta l.) spawning habitat degradation induced by climate change. Ecological Modelling. 386:98-114. https://doi.org/10.1016/j.ecolmodel.2018.08.012S9811438

The overwintering of Antarctic krill, Euphausia superba, from an ecophysiological perspective

A major aim of this review is to determine which physiological functions are adopted by adults and larvae to survive the winter season with low food supply and their relative importance. A second aim is to clarify the extent to which seasonal variation in larval and adult krill physiology is mediated by environmental factors with a strong seasonality, such as food supply or day light. Experimental studies on adult krill have demonstrated that speciWc physiological adaptations during autumn and winter, such as reduced metabolic rates and feeding activity, are not caused simply by the scarcity of food, as was previously assumed. These adaptations appear to be inXuenced by the local light regime. The physiological functions that larval krill adopt during winter (reduced metabolism, delayed development, lipid utilisation, and variable growth rates) are, in contrast to the adults, under direct control by the available food supply. During winter, the adults often seem to have little association with sea ice (at least until early spring). The larvae, however, feed within sea ice but mainly on the grazers of the ice algal community rather than on the algae themselves. In this respect, a miss-match in timing of the occurrence of the last phytoplankton blooms in autumn and the start of the sea ice formation, as has been increasingly observed in the west Antarctic Peninsula (WAP) region, will impact larval krill development during winter in terms of food supply and consequently the krill stock in this region