45 research outputs found
Open Source evaluation of kilometric indexes of abundance.
Kilometric Abundance Index (KAI) is a common measure used in wildlife studies because it allows a
straightforward comparison of species abundance in different sites or at different times. KAI expresses the
ratio of the total number of individuals (or of signs of presence) observed along a transect by the total transect
length covered at each site. v.transect.kia is a new tool for GRASS GIS, developed for automating the evaluation
of KAI, reducing the risk of manual errors especially when handling large datasets. It can also split the
transects according to one environmental variable (typically habitat type) and evaluate true 3D transect
length. It calculates KAI using a point map of sightings and saves the results in the attribute table, the output
can be displayed in any GIS or used for further statistical analysis. The tool has been tested on field data from
Northern Italy for mountain hare (Lepus timidus), allowing a first wide-area estimate
Home range dynamics of mountain hares (Lepus timidus) in the Swiss Alps.
Little is known on the ecology and behaviour of the alpine mountain hare
(Lepus timidus). Between 1996 and 1997, we analysed by radiotracking the pattern of space
use of 8 mountain hares from the Swiss Alps. We estimated home range size using both the
kernel density estimator and the minimum convex polygon. We found smaller ranges (38
ha) compared to those reported for the species in boreal or arctic habitats, but similar to
ranges in Scotland. Hares did not use a centre of major activity (core area) and showed high
home range overlap, confirming their non-territorial behaviour. Smaller ranges were used
during winter compared to the other seasons, whilst no difference in size was found
between sexes
Can water management reduce NH3 emissions from urea application in rice paddies?
Ammonia (NH3) is one of the main reactive components of the troposphere and its deposition is a major environmental treat. Rice fields are particular sensitive environment in which NH3 volatilisation can be mitigated according to water management, increasing the effectiveness of the fertiliser and reducing environmental issues. Urea is the most common N-fertiliser used for rice production and the determination of NH3 emissions from different water managements is still far from clear.
A two year experiment was designed to quantify NH3 releases from two urea applications, at tillering and at
panicle initiation, and with three different treatment of water managements: (i) \u201cDRY\u201d, with fertilisations on dry
soil; (ii) \u201cFLD-D\u201d - water seeding continuous flooding - with fertilisations on temporally dried soil surface; (iii)
\u201cFLD-W\u201d - water seeding continuous flooding - with fertilisation into standing water. Measurements were carried
out on three contiguous plots, one treatment each, of 2650m2 (5053m) in Castello D\u2019Agogna (Italy) during
2015 and 2016; fertilisations provided 70+50 kg N/ha for DRY and 60+40 kg N/ha for FDL-D and FLD-W. NH3
emissions were quantified by means of concentration-based inverse dispersion modelling, applied to a multi-plot
design. This low-cost method allows measuring gas concentrations above the soil surface by using integrationtime
passive samplers, placed in each plot at 1 m height above soil surface (or crop canopy) and replaced each 6h
during the more turbulent daylight hours and kept for 12h during calm night-time. Two additional measurement
points assessed background concentration near the plots. Surface to atmosphere exchanges were quantified with the Eulerian short-range dispersion model FIDES-3D (INRA, France) in a multi-plot configuration, in order to tackle
with the mutual advection from the three nearby and different sources. Flux were corrected for low turbulence and
near-neutrality conditions (u <0.05m/s), jLj < 2m); 15%of the data.
Water management played a key-role to control NH3 emissions both at tillering and panicle initiation. When fertilisations occurred directly on soil surface, residual surface humidity was determinant, in fact with soil water contents lower than the field capacity (DRY), the emissions were the lowest, start to emitting when the paddy was re-wetted, and following the circadian trend of air temperatures. Conversely, when the soil surface was not completely dried (i.e. drying time too short; FLD-D) and the soil water content resulting above the field capacity, an unique, intense and rapid NH3 emission peak was produced in the first 24h from the fertiliser distribution. This effect was probably due to the rapid hydrolysis combined to the urease activity on soil surface. When the fertilisation occurred
directly into the water (FLD-W), emissions were prolonged over time and assumed intermediate intensities with
no main peaks. Water management after the fertilisation spreading affected secondarily the emissions, outlining
discrete emission phenomena only when the paddies were dried out. NH3 emissions at tillering and at panicle
differentiation were, respectively DRY: 3.2 +/- 0:6% - 5:9%; FLD-D : 17:8 +/- 4:1% - 21:0 +/- 4:2%; FLD-W :
14:5 +/- 4:9% - 17:5 +/- 8:3%
Internet of Things in Agricultural Innovation and Security
The agricultural Internet of Things (Ag-IoT) paradigm has tremendous potential in transparent integration of underground soil sensing, farm machinery, and sensor-guided irrigation systems with the complex social network of growers, agronomists, crop consultants, and advisors. The aim of the IoT in agricultural innovation and security chapter is to present agricultural IoT research and paradigm to promote sustainable production of safe, healthy, and profitable crop and animal agricultural products. This chapter covers the IoT platform to test optimized management strategies, engage farmer and industry groups, and investigate new and traditional technology drivers that will enhance resilience of the farmers to the socio-environmental changes. A review of state-of-the-art communication architectures and underlying sensing technologies and communication mechanisms is presented with coverage of recent advances in the theory and applications of wireless underground communications. Major challenges in Ag-IoT design and implementation are also discussed
A fluorescent probe for ecstasy
A nanostructure formed by the insertion in silica nanoparticles of a pyrene-derivatized cavitand, which is able to specifically recognize ecstasy in water, is presented. The absence of effects from interferents and an efficient electron transfer process occurring after complexation of ecstasy, makes this system an efficient fluorescent probe for this popular drug
Monitoraggio degli ungulati nel Parco Regionale Campo dei Fiori (VA): metodologie a confronto.
Abstrac
Desde el este hacia Argentina. Historia, identidades y perspectivas de abordaje
Resumen: En esta publicación, los autores abordan distintos aspectos que hacen a los diseños de las investigaciones sobre procesos migratorios, desde las teorías, los métodos y datos necesarios, hasta los niveles de análisis en que se plantean los estudios.\nLos procesos migratorios hacia Argentina, desde países de Europa Central y del Este, así como de algunos de Asia, tienen largo tiempo. Y estudiarlos siempre ha resultado atractivo para los investigadores interesados en la movilidad humana, sus causas y consecuencias. Dependiendo del país de procedencia de los migrantes, los flujos han llegado en distintos períodos desde comienzos fines del siglo XIX. Por causas que varían según el contexto internacional y el momento histórico. Generalmente vinculadas a crisis económicas y/o sociales, guerras u otros sucesos de violencia como persecuciones por motivos étnicos, etc. que han afectado a los países en distintos períodos. En algunos casos, los flujos migratorios de la misma procedencia ocurridos en distintos períodos se han apoyado en un marco legal que lo hacia posible sumado a la existencia de redes migratorias que han cumplido un rol fundamental, al decidir la salida del país de origen y durante los primeros tiempos en el país receptor.\nFil: Masseroni, Susana. Universidad de Buenos Aires. Facultad de Ciencias Sociales. Instituto de Investigaciones Gino Germani; Argentina.Fil: Fraga, Cecilia. Universidad de Buenos Aires. Facultad de Ciencias Sociales. Instituto de Investigaciones Gino Germani; Argentina.Fil: Rutyna, Nancy E. Universidad de Buenos Aires. Instituto de Ciencias Antropológicas; Argentina.Fil: Boulgourdjian, Nélida E. Universidad de Buenos Aires. Facultad de Filosofía y Letras; Argentina