Ground beetle dispersal: how to bridge the scales?

Beneficial arthropods that provide biological control of aphids or weed seeds use a variety of habitats in agricultural landscapes. Information on the movement behaviour of these arthropods between these habitats is needed to develop conservation strategies that sustain pest suppression in agricultural landscapes. Models for movement behaviour may help to understand and explore biocontrol functions. As measurements of behaviour at the landscape scale are technically difficult to make, measurements are often made at smaller scales. It is then necessary to upscale to larger scales, using movement models. Here we present a case study on such upscaling. The first results indicate that upscaling from small scales to large scales, using a correlated random movement model, may result in errors. An alternative approach, to be tested in further work, is to fit the movement model directly to the large scale dat

Spatio-temporal analysis of stress diffusion in a mining-induced seismicity system

Abstract. The spatio-temporal correlation of micro-earthquakes occuring in a mining-induced seismic system (Creighton mine, Ontario, Canada) is investigated. It is shown that, when considering only the after-events correlated to a main event, i.e., not accounting for the uncorrelated regime of ‘background ’ activity, the spatial distribution of these afterevents occuring at t after the main event change with t. This change takes the form of an expanding pattern, characterized by a typical scale Lc(t) varying as Lc(t) ∼ t H, H being estimated to 0.18. This diffusion exponent is found to increase when considering only a subset of the most energetic events as mainshocks. We interpret this result as the indication of a stress (sub-)diffusion mechanism, involving propagation on the heterogeneous fractal fault network. 1

Imbricated slip rate processes during slow slip transients imaged by low-frequency earthquakes

Low Frequency Earthquakes (LFEs) often occur in conjunction with transient strain episodes, or Slow Slip Events (SSEs), in subduction zones. Their focal mechanism and location consistent with shear failure on the plate interface argue for a model where LFEs are discrete dynamic ruptures in an otherwise slowly slipping interface. SSEs are mostly observed by surface geodetic instruments with limited resolution and it is likely that only the largest ones are detected. The time synchronization of LFEs and SSEs suggests that we could use the recorded LFEs to constrain the evolution of SSEs, and notably of the geodetically-undetected small ones. However, inferring slow slip rate from the temporal evolution of LFE activity is complicated by the strong temporal clustering of LFEs. Here we apply dedicated statistical tools to retrieve the temporal evolution of SSE slip rates from the time history of LFE occurrences in two subduction zones, Mexico and Cascadia, and in the deep portion of the San Andreas fault at Parkfield. We find temporal characteristics of LFEs that are similar across these three different regions. The longer term episodic slip transients present in these datasets show a slip rate decay with time after the passage of the SSE front possibly as t^(−1/4). They are composed of multiple short term transients with steeper slip rate decay as t^(−α) with α between 1.4 and 2. We also find that the maximum slip rate of SSEs has a continuous distribution. Our results indicate that creeping faults host intermittent deformation at various scales resulting from the imbricated occurrence of numerous slow slip events of various amplitudes

Confluence reduction for Markov automata

Markov automata are a novel formalism for specifying systems exhibiting nondeterminism, probabilistic choices and Markovian rates. Recently, the process algebra MAPA was introduced to efficiently model such systems. As always, the state space explosion threatens the analysability of the models generated by such specifications. We therefore introduce confluence reduction for Markov automata, a powerful reduction technique to keep these models small. We define the notion of confluence directly on Markov automata, and discuss how to syntactically detect confluence on the MAPA language as well. That way, Markov automata generated by MAPA specifications can be reduced on-the-fly while preserving divergence-sensitive branching bisimulation. Three case studies demonstrate the significance of our approach, with reductions in analysis time up to an order of magnitude

Small Solar Panels Can Drastically Reduce the Carbon Footprint of Radio Access Networks

The limited power requirements of new generations of base stations (BSs) make the use of renewable energy sources, solar in particular, extremely attractive for mobile network operators. Exploiting solar energy implies a reduction of the network operation cost as well as of the carbon footprint of radio access networks, but previous research works indicate that the area of the solar panels that are necessary to power a standard macro BS is large, so large to make the solar panel deployment problematic, especially within urban areas. In this paper we use a modeling approach based on Markov reward processes to investigate the possibility of combining small area solar panels with a connection to the power grid to run a macro BS. By so doing, it is possible to increase the amount of renewable energy used to run a radio access network, while also reducing the cost incurred by the network operator to power its base stations. We assume that energy is drawn from the power grid only when needed to keep the BS operational, or during the night, that corresponds to the period with lowest electricity price. This has advantages in terms of both cost and carbon footprint. We show that solar panels of the order of 1-2 kW peak, i.e., with a surface of about 5-10 m2, combined with limited capacity energy storage (of the order of 10-15 kWh, corresponding to about 3-5 car batteries), and a smart energy management policy, can lead to an effective exploitation of renewable energy