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Abstract. We propose an original approach to develop rainfall thresholds to be used in civil protection warning systems for the occurrence of landslides at regional scale (i.e. tens of thousands of kilometres), and we apply it to Tuscany, Italy (23 000 km2). Purpose-developed software is used to define statistical intensity–duration rainfall thresholds by means of an automated and standardized analysis of rainfall data. The automation and standardization of the analysis brings several advantages that in turn have a positive impact on the applicability of the thresholds to operational warning systems. Moreover, the possibility of defining a threshold in very short times compared to traditional analyses allowed us to subdivide the study area into several alert zones to be analysed independently, with the aim of setting up a specific threshold for each of them. As a consequence, a mosaic of several local rainfall thresholds is set up in place of a single regional threshold. Even if pertaining to the same region, the local thresholds vary substantially and can have very different equations. We subsequently analysed how the physical features of the test area influence the parameters and the equations of the local thresholds, and found that some threshold parameters can be put in relation with the prevailing lithology. In addition, we investigated the possible relations between effectiveness of the threshold and number of landslides used for the calibration. A validation procedure and a quantitative comparison with some literature thresholds showed that the performance of a threshold can be increased if the areal extent of its test area is reduced, as long as a statistically significant landslide sample is present. In particular, we demonstrated that the effectiveness of a warning system can be significantly enhanced if a mosaic of site-specific thresholds is used instead of a single regional threshold.

The increased demand of food produced through sustainable agriculture has resulted in localised amelioration of intensive management imposed by agroecosystems. However, these newly available niches are often isolated and plant species may not be able to recolonise fragmented agroecosystems from where they have been extirpated. Plant reintroduction can overcome dispersal limitation in agroecosystems but may also generate conflicts that jeopardise conservation efforts. Conflicts arise when reintroductions are perceived to place constraints on the management and productivity of agroecosystems: the translocated plants may require space sharing with crops, may have negative effects on crop yields, and come with the expectation that farmers must modify their farming practices and accommodate legal obligations deriving from protected species status. Benefits include economic incentives that pay farmers through CAP, the conservation of nature, ecosystem services, an effective marketing strategy and increased aesthetic value that might generate ecotourism. We discuss the practical implications of the abovementioned issues by reference to two cases of European species in which different approaches to reintroduction resulted in opposite outcomes (i.e., consensus vs. opposition). Coexistence of threatened plants and crops is possible if farmers and local stakeholders are involved in a conservation project from an early stage and if farmers conservation efforts turn into benefits for their income. Based on these considerations, we propose a strategic framework to promote reintroduction of threatened plants in agroecosystems (land sharing) and policy advancement aimed at recognising the role of farmers in maintaining biodiversity on their lands.

Abstract. HIRESSS (HIgh REsolution Slope Stability Simulator) is a physically based distributed slope stability simulator for analyzing shallow landslide triggering conditions in real time and on large areas using parallel computational techniques. The physical model proposed is composed of two parts: hydrological and geotechnical. The hydrological model receives the rainfall data as dynamical input and provides the pressure head as perturbation to the geotechnical stability model that computes the factor of safety (FS) in probabilistic terms. The hydrological model is based on an analytical solution of an approximated form of the Richards equation under the wet condition hypothesis and it is introduced as a modeled form of hydraulic diffusivity to improve the hydrological response. The geotechnical stability model is based on an infinite slope model that takes into account the unsaturated soil condition. During the slope stability analysis the proposed model takes into account the increase in strength and cohesion due to matric suction in unsaturated soil, where the pressure head is negative. Moreover, the soil mass variation on partially saturated soil caused by water infiltration is modeled. The model is then inserted into a Monte Carlo simulation, to manage the typical uncertainty in the values of the input geotechnical and hydrological parameters, which is a common weak point of deterministic models. The Monte Carlo simulation manages a probability distribution of input parameters providing results in terms of slope failure probability. The developed software uses the computational power offered by multicore and multiprocessor hardware, from modern workstations to supercomputing facilities (HPC), to achieve the simulation in reasonable runtimes, compatible with civil protection real time monitoring. A first test of HIRESSS in three different areas is presented to evaluate the reliability of the results and the runtime performance on large areas.

Predation is a major cause of mortality in non-human primates, and considered a selective force in the evolution of primate societies. Although larger body size is considered as protection against predation, evidence for predation on great apes by carnivores comes from chimpanzees (Pan troglodytes), gorillas (Gorilla gorilla), and orangutans (Pongo spp.). Here, we describe the first encounter between wild bonobos (Pan paniscus) and a leopard (Panthera pardus). A single leopard was confronted by a group of habituated bonobos for three hours. Two adult males and one adolescent female bonobo actively harassed the leopard, which remained still for most of the encounter and reacted only to close approaches by bonobos. While no predation was observed, their behaviours confirm that bonobos perceive leopards as potential predators. Our report adds novel information to descriptions from other African ape species, and sheds light on the behavioural repertoire of bonobos' anti-predation strategies. For future investigations, we suggest tagging leopards to remotely monitor their movements and allow assessment of encounter rates as one of several factors influencing predation pressure.

Abstract. This work proposes a methodology to compare the forecasting effectiveness of different rainfall threshold models for landslide forecasting. We tested our methodology with two state-of-the-art models, one using intensity–duration thresholds and the other based on cumulative rainfall thresholds. The first model identifies rainfall intensity–duration thresholds by means of a software program called MaCumBA (MAssive CUMulative Brisk Analyzer) (Segoni et al., 2014a) that analyzes rain gauge records, extracts intensity (I) and duration (D) of the rainstorms associated with the initiation of landslides, plots these values on a diagram and identifies the thresholds that define the lower bounds of the I–D values. A back analysis using data from past events is used to identify the threshold conditions associated with the least number of false alarms. The second model (SIGMA) (Sistema Integrato Gestione Monitoraggio Allerta) (Martelloni et al., 2012) is based on the hypothesis that anomalous or extreme values of accumulated rainfall are responsible for landslide triggering: the statistical distribution of the rainfall series is analyzed, and multiples of the standard deviation (σ) are used as thresholds to discriminate between ordinary and extraordinary rainfall events. The name of the model, SIGMA, reflects the central role of the standard deviations. To perform a quantitative and objective comparison, these two models were applied in two different areas, each time performing a site-specific calibration against available rainfall and landslide data. For each application, a validation procedure was carried out on an independent data set and a confusion matrix was built. The results of the confusion matrixes were combined to define a series of indexes commonly used to evaluate model performances in natural hazard assessment. The comparison of these indexes allowed to identify the most effective model in each case study and, consequently, which threshold should be used in the local early warning system in order to obtain the best possible risk management. In our application, none of the two models prevailed absolutely over the other, since each model performed better in a test site and worse in the other one, depending on the characteristics of the area. We conclude that, even if state-of-the-art threshold models can be exported from a test site to another, their employment in local early warning systems should be carefully evaluated: the effectiveness of a threshold model depends on the test site characteristics (including the quality and quantity of the input data), and a validation procedure and a comparison with alternative models should be performed before its implementation in operational early warning systems.

Abstract. We set up an early warning system for rainfall-induced landslides in Tuscany (23 000 km2). The system is based on a set of state-of-the-art intensity–duration rainfall thresholds (Segoni et al., 2014b) and makes use of LAMI (Limited Area Model Italy) rainfall forecasts and real-time rainfall data provided by an automated network of more than 300 rain gauges. The system was implemented in a WebGIS to ease the operational use in civil protection procedures: it is simple and intuitive to consult, and it provides different outputs. When switching among different views, the system is able to focus both on monitoring of real-time data and on forecasting at different lead times up to 48 h. Moreover, the system can switch between a basic data view where a synoptic scenario of the hazard can be shown all over the region and a more in-depth view were the rainfall path of rain gauges can be displayed and constantly compared with rainfall thresholds. To better account for the variability of the geomorphological and meteorological settings encountered in Tuscany, the region is subdivided into 25 alert zones, each provided with a specific threshold. The warning system reflects this subdivision: using a network of more than 300 rain gauges, it allows for the monitoring of each alert zone separately so that warnings can be issued independently. An important feature of the warning system is that the visualization of the thresholds in the WebGIS interface may vary in time depending on when the starting time of the rainfall event is set. The starting time of the rainfall event is considered as a variable by the early warning system: whenever new rainfall data are available, a recursive algorithm identifies the starting time for which the rainfall path is closest to or overcomes the threshold. This is considered the most hazardous condition, and it is displayed by the WebGIS interface. The early warning system is used to forecast and monitor the landslide hazard in the whole region, providing specific alert levels for 25 distinct alert zones. In addition, the system can be used to gather, analyze, display, explore, interpret and store rainfall data, thus representing a potential support to both decision makers and scientists.

Abstract. Although shallow landslides are a very widespread phenomenon, large area (e.g. thousands of square kilometres) early warning systems are commonly based on statistical rainfall thresholds, while physically based models are more commonly applied to smaller areas. This work provides a contribution towards the filling of this gap: a forecasting chain is designed assembling a numerical weather prediction model, a statistical rainfall downscaling tool and a geotechnical model for the distributed calculation of the factor of safety on a pixel-by-pixel basis. The forecasting chain can be used to forecast the triggering of shallow landslides with a 48 h lead time and was tested on a 3200 km2 wide area.

9 páginas, 2 figuras, 2 tablas. ; In order to characterize the complete range of lesions, especially minimal, affecting mammary gland and viral antigen distribution and target cells using immunohistochemistry in naturally Visna/maedi (VM) 84 infected sheep were studied, forty-four from flocks with clinical cases (A) and 35 randomly sampled from two abattoirs (B) together with five negative controls (C). An immunocytochemistry technique was developed and further milk samples (n = 39) were used to study viral excretion, carrier cells and the role of milk and colostrum in the transmission of the disease. ; This work was supported by LE361A12–1 project of Castilla y León Government and FPU13/01081 grant of the Spanish Government. LE361A12– 1 project financed the materials necessary for collection, analysis and interpretation of data. FPU13/01081 grant financed the pre-doctoral contract of the main performer of experiments and manuscript writer EG.

Italy has a rich natural heritage, which is dangerously under pressure. In recent years, there is an increased awareness of the crucial role of plants in ecosystem functioning and in providing ecosystem services. Consequently, an updated Red List of the Italian vascular flora was compiled in this work, at the request of the Ministry for Environment, Land and Sea Protection, with the scientific support of the Italian Botanical Society. The IUCN Red List criteria were applied to 2,430 Italian native vascular plant taxa to assess their current extinction risk and to highlight the major threats affecting the Italian flora. Our results revealed that 54 taxa (2.2% of the assessed taxa) are extinct or possibly extinct at regional level, while 590 taxa (24.3%) were assigned to a risk category. Moreover, 404 taxa (16.6%) were categorized as Data Deficient. The Italian vascular flora is primarily threatened by habitat modifications due to anthropic disturbance and, especially, to agriculture, tourism and residential development. Coastal areas and lowlands, where anthropogenic impacts and ecosystem destruction are more pronounced, host the greatest number of extinct or declining taxa. Our results represent an important baseline to establish conservation priorities, legislative choices and intervention strategies on a national scale.

Open Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. ; Context. From 1988 to 2016, several stellar occultations have been observed to characterise Pluto's atmosphere and its evolution. From each stellar occultation, an accurate astrometric position of Pluto at the observation epoch is derived. These positions mainly depend on the position of the occulted star and the precision of the timing. Aims. We present 19 Pluto's astrometric positions derived from occultations from 1988 to 2016. Using Gaia DR2 for the positions of the occulted stars, the accuracy of these positions is estimated at 2-10 mas, depending on the observation circumstances. From these astrometric positions, we derive an updated ephemeris of Pluto's system barycentre using the NIMA code. Methods. The astrometric positions were derived by fitting the light curves of the occultation by a model of Pluto's atmosphere. The fits provide the observed position of the centre for a reference star position. In most cases other publications provided the circumstances of the occultation such as the coordinates of the stations, timing, and impact parameter, i.e. the closest distance between the station and centre of the shadow. From these parameters, we used a procedure based on the Bessel method to derive an astrometric position. Results. We derive accurate Pluto's astrometric positions from 1988 to 2016. These positions are used to refine the orbit of Pluto'system barycentre providing an ephemeris, accurate to the milliarcsecond level, over the period 2000-2020, allowing for better predictions for future stellar occultations.© J. Desmars et al. 2019. ; Part of the research leading to these results has received funding from the European Research Council under the European Community's H2020 (2014 2020/ERC Grant Agreement No. 669416 >LUCKY STAR>). This work has made use of data from the European Space Agency (ESA) mission Gaia (https://www.cosmos.esa.int/gaia), processedby the Gaia Data Processing and Analysis Consortium (DPAC, https://www.cosmos.esa.int/web/gaia/dpac/consortium).Funding for the DPAC has been provided by national institutions, in particular the institutions participating in the Gaia Multilateral Agreement. J.I.B.C. acknowledges CNPq grant 308150/2016-3. M.A. thanks CNPq (Grants 427700/2018-3, 310683/2017-3 and 473002/2013-2) and FAPERJ (Grant E-26/111.488/2013). G.B.R. is thankful for the support of the CAPES (203.173/2016) and FAPERJ/PAPDRJ (E26/200.464/2015-227833) grants. This study was financed in part by the Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior -Brasil (CAPES) -Finance Code 001. F.B.R. acknowledges CNPq grant 309578/2017-5. A.R.G-J thanks FAPESP proc. 2018/11239-8. R.V-M thanks grants: CNPq-304544/2017-5, 401903/2016-8, Faperj: PAPDRJ-45/2013 and E-26/203.026/2015 P.S.-S. acknowledges financial support by the European Union's Horizon 2020 Research and Innovation Programme, under Grant Agreement no 687378, as part of the project > Small Bodies Near and Far> (SBNAF). ; Peer Reviewed