ALBERT

Description: The detection and characterization of signals of interest in the presence of (in)coherent ambient noise is central to the analysis of infrasound array data. Microbaroms have an extended source region and a dynamical character. From the perspective of an infrasound array, these coherent noise sources appear as interfering signals that conventional beamform methods may not correctly resolve. This limits the ability of an infrasound array to dissect the incoming wavefield into individual components. In this paper, this problem will be addressed by proposing a high-resolution beamform technique in combination with the CLEAN algorithm. CLEAN iteratively selects the maximum of the f/k spectrum (i.e. following the Bartlett or the Capon method) and removes a percentage of the corresponding signal from the cross-spectral density matrix. In this procedure, the array response is deconvolved from the f/k spectral density function. The spectral peaks are retained in a ‘clean’ spectrum. A data-driven stopping criterion for CLEAN is proposed, which relies on the framework of Fisher statistics. This allows the construction of an automated algorithm that continuously extracts coherent energy until the point is reached that only incoherent noise is left in the data. CLEAN is tested on a synthetic data set and is applied to data from multiple International Monitoring System infrasound arrays. The results show that the proposed method allows for the identification of multiple microbarom source regions in the Northern Atlantic that would have remained unidentified if conventional methods had been applied.

Description: Wild deer exert strong top–down control on forest composition by browsing on palatable trees, and these effects are exacerbated as red, fallow, and roe deer populations increase in northern temperate forests. However, the relationship between deer abundance and plant recruitment remains poorly documented. Here, we combined camera trap and vegetation plot data to quantify the shape of the relationship between habitat utilization by deer (red, fallow and roe deer) with different components of the forest understory in ten sites distributed across a temperate mixed forest in the Veluwe, the Netherlands. The list of forest attributes included the density, richness and diversity of saplings, the proportion of conifers to broadleaves, the number of browsed broadleaves and conifers, the forest basal area, the understory cover of shrubs, moss and bare soil and the depth of the litter layer. When applying General Linear Mixed Models to those camera trap data, six of the eleven forest variables were related to the utilization level (UL) by deer. With increasing UL by fallow deer, there was a decrease in sapling species richness (β = −0.26). With increasing UL by red deer, there was a decrease in litter depth (β = −0.14) and an increase in browsed broadleaf stems (β = 0.40). With increasing UL by roe deer, there was a decrease in species richness of sapling plants (β = −0.26), Shannon diversity (β = −0.11) and shrub cover (β = −0.36), whereas there was an increase in stem density (β = 0.06). When combining all deer species into one guild, a negative relation was found between UL by deer and sapling richness (β = −0.21), diversity (β = −0.09) and litter depth (β = −0.14) and a positive relation with sampling density (β = 0.04). The relationship between UL by deer and different forest attributes followed a linear log10 shape. When back transforming, the response was curvilinear with large changes at a low UL and small changes when the UL was high. Yet, the exact shape of the curve varied according to (a) biotic factors specific to each study location. The conservation of temperate forests can benefit from limiting the size of deer populations and the time deer spend browsing in forest patches with high biodiversity value.