Much remains to be learned about how anthropogenic structures affect migration in large mammals. We examined the potential influence of the international railroad in Mongolia on migration in Mongolian gazelles (Procapra gutturosa). We examined gazelle movements and the normalized difference vegetation index (NDVI) on both sides of the railroad. The tracked gazelles never crossed the railroad, despite movements that mainly followed the railroad in winter and higher NDVI values on the opposite side. It is likely that the railroad had a barrier effect on gazelle migration because it split the gazelles' habitat. Our results, although based on an extremely small sample, have utility in indicating approaches that might be useful for examining migration in ungulates.Resumen: Falta mucho por conocer sobre el efecto de estructuras antropogénicas sobre la migración de mamíferos mayores. Examinamos la potencial influencia del ferrocarril internacional en Mongolia sobre la migración de gacelas de Mongolia ( Procapra gutturosa). Examinamos los movimientos de las gacelas y eĺ ındice de vegetación de diferencia normalizada (IVDN) a ambos lados de la vía férrea. Las gacelas rastreadas nunca cruzaron la vía férrea, a pesar de que los movimientos mayormente seguían la vía en invierno y que los valores de IVDN eran mayores del lado contrario. Es probable que la vía férrea produjera un efecto de barrera sobre la migración de las gacelas porque dividió al hábitat de las gacelas. Nuestros resultados, aunque basados en una muestra extremadamente pequeña, sonútiles para señalar estrategias que pueden ser utilizadas provechosamente para examinar la migración de ungulados.
Conservation and management are urgently required for Mongolian gazelles Procapra gutturosa inhabiting the Mongolian steppe. We captured and satellitecollared two adult females in Dornogobi Province and two adult females in Omnogobi Province and examined whether their seasonal migration corresponded to shifts in the normalized difference vegetation index (NDVI) in their habitat. The mean NDVI values of their annual, summer and winter ranges were calculated based on data acquired by the moderate-resolution imaging spectrometer (MODIS) onboard the Terra satellite. Satellite tracking of gazelles proved their ability to move long distances and provided details of their migration routes. In Omnogobi, the NDVI of the summer range was higher than those of annual and winter ranges during summer, but from October to November the NDVI of the summer range was lower than annual or winter ranges. The shift in NDVI values between summer and winter ranges corresponded with seasonal migrations of gazelles. In contrast, NDVI values were higher in the winter ranges than in both the summer and annual ranges throughout the year in Dornogobi. The results showed that the NDVI is a good indicator of gazelle habitat, but the NDVI alone cannot the explain seasonal migration of gazelles. It is important to evaluate the effectiveness and limitations of the NDVI as an indicator of habitat quality.
The longest dust trail among those so detected at optical wavelengths was found along the orbit of 4P/Faye in the 2006 return. It extended as long as 10° in the backward direction. The surface brightness increases monotonically with the distance from the nucleus between $0\rlap{.}^\circ5$ and 3°, but decreases slowly beyond 4°. The observed brightnesses of the dust trail and the tail are reasonably explained by our dust ejection model. The model shows that the dust trail is composed of cm-sized particles ejected during previous returns, and the derived power indices of the size distribution function of dust particles ejected from the nucleus ($-$3.5) and those remaining in the trail ($-$1.9) have a big difference for each other. The averaged mass-loss rate (20 kg s$^{-1}$) derived from the model is comparable to those of known IRAS dust trail comets.
For better risk management, detailed and quantitative measurement of channel and stream‐bed structure is required to understand and predict water and sediment flow in mountain channels. Our previous research demonstrated good performance of green‐wavelength Terrestrial laser scanning (TLS) for measurement of submerged stream‐bed in a steep mountain channel. This paper examines how the acquisition protocol of TLS affects the accuracy of data collected in the mountain channel. First, it was tested whether varying the scanner height, i.e., incident angle affects the data acquisition in terms of point density and accuracy in the pool unit of step‐pool channel. Then, the effect of varying the minimum point spacing on the derived Digital terrain model (DTM) was examined. It was also analyzed whether a combination of multiple TLS data acquired from different directions would improve the accuracy of data compared to data acquired by a single measurement. Furthermore, TLS data were acquired over a cascade unit of the channel and examined whether TLS is capable of capturing reliable underwater data. All the acquired underwater data by TLS were corrected for water refraction and validated using manual surveyed data. The results showed that the accuracy of derived DTM was improved when the scanner height was increased or data was acquired from multiple directions, however, acquiring denser point cloud with a minimum point spacing of 1 mm did not improve the accuracy of the data. Accuracy of TLS measurement in the cascade unit was considerably lower. Special consideration is required for this area.
<p><strong>Abstract.</strong> Herbaceous vegetation on riverdike is important to prevent soil erosion, which may lead to collapse of riverdikes and consequently severe flooding. To keep suitable vegetation condition and secure visibility of riverdike for inspection, managers need to know where thick and tall herbaceous vegetation grows on riverdikes in a cost effective manner. This paper aims to derive vertical structure of herbaceous vegetation on riverdike using UAV LiDAR. UAV LiDAR based indices, V-bottom, V-middle and V-top; presence of vegetation in bottom vegetation (0&ndash;50&thinsp;cm), middle vegetation (50&ndash;100&thinsp;cm) and top vegetation (&gt;100&thinsp;cm) respectively, were calculated and compared to field survey data for validation. The results showed that UAV LiDAR based assessment strongly correlated with field based assessment in middle and top vegetation with R<sup>2</sup>&thinsp;=&thinsp;0.67 and 0.85, respectively. However, it displayed only moderate correlation in bottom vegetation (R<sup>2</sup>&thinsp;=&thinsp;0.36). It was found that bottom vegetation might be underestimated when forb species or falling grass species is abundant in middle vegetation. However, underestimated place can be easily checked using proposed UAV LiDAR based V-bottom and V-middle values. The vertical structure information derived by proposed method would be valuable assets for vegetation management on riverdike.</p>
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