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20Droughts are among the most important natural disasters, particularly in the arid and 21 semiarid regions of the world. Proper management of droughts requires knowledge of the 22 expected frequency of specific low magnitude precipitation totals for a variety of durations. 23Probabilistic approaches have often been used to estimate the average recurrence period of 24 a given drought event. However, probabilistic model fitting by conventional methods, such 25 as product moment or maximum likelihood in areas with low availability of long records 26 often produces highly unreliable estimates. Recognizing the need for adequate estimates of 27 return periods of severe droughts in the arid and semiarid region of Chile, a regional 28 frequency analysis method based on L-moments (RFA-LM) was used for estimating and 29 mapping drought frequency. Some adaptations to the existing procedures for forming 30 homogeneous regions were found necessary. In addition, a new 3-parameter distribution, 31 the Gaucho, which is a special case of the 4-parameter Kappa distribution, was introduced, 32 and the analysis procedure was improved by the developments of two new software tools 33 named L-RAP, to perform the RFA-LM analysis, and L-MAP, to map the resulting drought 34 maps. Eight homogeneous sub-regions were delineated using the Gaucho distribution and 35 used to construct return period maps for drought events with 80% and 40% precipitation of 36 the normal. The study confirms the importance of a sub-regional homogeneity test, and the 37 usefulness of the Gaucho distribution. The RFA-LM showed that droughts with a 40% 38 precipitation of the normal have return periods that range from four years at the northern 39 arid boundary of the study area to 22 years at the southern sub-humid boundary. The results 40 demonstrate the need for different thresholds for declaring a drought than those currently in 41 use for drought characterization in north-central Chile. 42 43

A description of thermal radiometric field measurements carried out in the framework of the European project SENtinel-2 and Fluorescence Experiment (SEN2FLEX) is presented. The field campaign was developed in the region of Barrax (Spain) during June and July 2005. The purpose of the thermal measurements was to retrieve biogeophysical parameters such as land surface emissivity (LSE) and temperature (LST) to validate airborne-based methodologies and to characterize different surfaces. Thermal measurements were carried out using two multiband field radiometers and several broadband field radiometers, pointing at different targets. High-resolution images acquired with the Airborne Hyperspectral Scanner (AHS) sensor were used to retrieve LST and LSE, applying the Temperature and Emissivity Separation (TES) algorithm as well as single-channel (SC) and two-channel (TC) methods. To this purpose, 10 AHS thermal infrared (TIR) bands (8–13 mm) were considered. LST and LSE estimations derived from AHS data were used to obtain heat fluxes and evapotranspiration (ET) as an application of thermal remote sensing in the context of agriculture and water management. To this end, an energy balance equation was solved using the evaporative fraction concept involved in the Simplified Surface Energy Balance Index (S-SEBI) model. The test of the different algorithms and methods against ground-based measurements showed root mean square errors (RMSE) lower than 1.8K for temperature and lower than 1.1 mm/day for daily ET

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parts of Antarctica were amongst the most rapidly changing regions of the planet during the second half of the Twentieth Century. Even so, today, most of Antarctica remains in the grip of continental ice sheets, with only about 0.2% of its overall area being ice-free. The continent's terrestrial fauna consists only of invertebrates, with just two native species of insects, the chironomid midges Parochlus steinenii and Belgica antarctica. We integrate ecophysiological information with the development of new highresolution climatic layers for Antarctica, to better understand how the distribution of P. steinenii may respond to change over the next century under different IPCC climate change scenarios. We conclude that the species has the potential to expand its distribution to include parts of the west and east coasts of the Antarctic Peninsula and even coastal ice-free areas in parts of continental Antarctica. We propose P. steinenii as an effective native sentinel and indicator species of climate change in the Antarctic. Antarctica and the sub-Antarctic islands are some of the last wilderness areas remaining on the planet. These remote areas remain, to a great extent, free from direct anthropogenic impacts such as overpopulation and overexploitation of native ecosystems 1 , although they are not immune to wider global anthropogenic processes such as climate change and long-range pollution 2,3. The high latitude regions of the Antarctic Peninsula, Scotia Arc, and the Magellanic Sub-Antarctic have been amongst the most rapidly warming areas in the world in the second half of the Twentieth Century, showing significant glacier retreat and reduction of snow and ice cover in terrestrial and freshwater ecosystems 3. While these strong regional warming trends have currently paused, they are predicted to resume through the remainder of the Twenty-first Century 4. These regions are highly sensitive to environmental change and thus are considered natural laboratories in which to study its effects, at all scales, on their ecosystems and biota 3,5. Today, Antarctica remains in the grip of continental ice sheets, with only about 0.2% of its overall area being ice-free 6 , this proportion is somewhat higher in the Antarctic Peninsula region (~3%; British Antarctic Survey unpublished data, Lee et al.. 2017). Terrestrial and freshwater ecosystems are generally small and isolated, populated by small invertebrates, lower plants, and microbes 7. The terrestrial fauna consists only of invertebrates, with just two native species of insects, both chironomid midges (the winged Parochlus steinenii Gerke and the brachypterous Belgica antarctica Jacobs), and two established invasive species with currently restricted ranges, Eretmoptera murphyi (Diptera: Chironomidae) and Trichocera maculipennis (Diptera: Trichoceridae) 8. Climatic gradients have changed over geological time at different spatio-temporal scales in these high latitude southern regions, shaping the composition and distribution of modern landscapes and their biota 3,9. The Eocen...

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This study compares the effect of lime additions on the spatial variability of Fe, Mn and Zn extracted by Mehlich-1 during three different growth stages from an acid paddy soil, a Typic Plintacualf, in Corrientes, Argentina. Field trials were set up involving three treatments: control, without lime addition, plus two different dolomite doses of 625 and 1250 kg ha -1 . Soil was sampled first before sowing in aerobic conditions and then two more times in anaerobic conditions, i.e. by bunch formation and flowering. Ninety-six samples per plot were taken per lime treatment and sampling period, using a nested sampling strategy. Liming significantly increased extractable Fe and Mn, but decreased extractable Zn. The spatial variability of the studied soil properties was assessed using semivariogram analysis and examination of kriging maps. Models were fitted to experimental semivariograms for 27 data sets, i.e. three different soil properties, each of them sampled in three treatments and during three dates. Soil extractable and Fe, Mn and Zn exhibited a rather strong spatial dependence, as nugget variance was either null or a small proportion of the total variance, and this all over the three different study periods and for the three lime treatments. Geostatistical analysis provided insight into possible processes responsible of the observed spatial variability patterns within the rice soil. Kriging was useful in mapping soil micronutrient variability allowing identifying microrregions with high or low Fe, Mn and Zn concentrations, which showed the presence of small scale variability. These findings indicate the potential for applying the principles of precision agriculture to control spatiotemporal variability in rice fields.