RESUMO
Time-of-arrival transmitter localization systems, which use measurements from an array of sensors to estimate the location of a radio or acoustic emitter, are now widely used for tracking wildlife. Outlier measurements can severely corrupt estimated locations. This article describes a new suite of location estimation algorithms for such systems. The new algorithms detect and discard outlier time-of-arrival observations, which can be caused by non-line-of-sight propagation, radio interference, clock glitches, or an overestimation of the signal-to-noise ratio. The new algorithms also detect cases in which two locations are equally consistent with measurements and can usually select the correct one. The new algorithms can also infer approximate altitude information from a digital elevation map to improve location estimates close to one of the sensors. Finally, the new algorithms approximate the covariance matrix of location estimates in a simpler and more reliable way than the baseline algorithm. Extensive testing on real-world data involving mobile transmitters attached to wild animals demonstrates the efficacy of the new algorithms. Performance testing also shows that the new algorithms are fast and that they can easily cope with high-throughput real-time loads.
Assuntos
Algoritmos , Animais Selvagens , Animais , Razão Sinal-RuídoRESUMO
Many environmental and ecological studies require line of sight (LOS) and/or viewshed analyses. While tools for performing these analyses from digital elevation models (DEMs) are widespread, they are either too restrictive, inaccessible or pricey and difficult to use. This methodological gap is potentially imperative for scholars using solutions like telemetry tracking systems or spatial ecology landscape mapping. Here we present ViewShedR-a free, open-source and intuitive graphical user-interface application for performing LOS calculations, including cumulative, subtractive (areas covered by towers A + B or by A but not by B, respectively), and elevated-target analyses. ViewShedR is implemented in the widely used R environment, thus facilitating usage and further modification by end-users. We provide two working examples for ViewShedR in the context of permanent animal-tracking systems requiring simultaneous tag-detection by multiple towers (receivers): first, the ATLAS system for terrestrial animals in the Harod Valley, Israel; and second, an acoustic telemetry array for marine animals in the Dry Tortugas, Florida. ViewShedR allowed effective tower deployment and finding partially detected tagged animals in the ATLAS system. Similarly, it allowed us to identify reception shadows cast by islands in the marine array. We hope ViewShedR will facilitate deployment of tower arrays for tracking, communication networks and other ecological applications.
RESUMO
Deserts are characterized by unpredictable precipitation and extreme temperatures. Their fauna and flora are sensitive to anthropogenic environmental changes, and often recover slowly from environmental disasters. The effects of oil spills on the biota of desert regions, however, have scarcely been studied. We predicted that terrestrial invertebrates suffer long-term negative effects from an oil spill, due to their close association with the substrate. Thus, we investigated the effects of two oil spills that occurred in 1975 and 2014 in the hyper-arid 'Arava desert (Israel), on a spider that constructs silk-lined nests in burrows in compact, sandy soil in this extreme desert habitat. The spider, Sahastata aravaensis sp. nov. (Filistatidae), is described herein. We assessed spider burrow abundance in plots located in oil-contaminated and nearby uncontaminated clean soil (control) areas over five consecutive years and measured habitat characteristics in these plots. In the laboratory, we determined the preference of individuals for clean vs. oil-contaminated soil as a resting substrate. Finally, as this species was previously undescribed, we added a new species description. The abundance of Sahastata was significantly lower in oil-contaminated plots, and this was the case in the 40-year-old oil spill (1975) as well as in the recent one (2014). In laboratory tests, spiders showed a significant preference for the clean soil substrate over the oil-contaminated substrate. In the field, soil crust hardness and vegetation density did not differ significantly between oil-contaminated and control plots, but these measures were highly variable. The burrows were significantly clustered, suggesting that the young disperse only short distances. In the laboratory adult spiders did not dig burrows, perhaps indicating that adults remain permanently in their natal burrows and that in the field they may use vacant burrows. We conclude that Sahastata populations were affected negatively by the oil spills and these effects were long-lasting. We propose that by monitoring their spatial distribution, burrow-dwelling spiders such as Sahastata can be used as effective bioindicators of soil pollution in desert habitats.