Horizontal and vertical species turnover in tropical birds in habitats with differing land use.

Large tracts of tropical rainforests are being converted into intensive agricultural lands. Such anthropogenic disturbances are known to reduce species turnover across horizontal distances. But it is not known if they can also reduce species turnover across vertical distances (elevation), which have steeper climatic differences. We measured turnover in birds across horizontal and vertical sampling transects in three land-use types of Sri Lanka: protected forest, reserve buffer and intensive-agriculture, from 90 to 2100 m a.s.l. Bird turnover rates across horizontal distances were similar across all habitats, and much less than vertical turnover rates. Vertical turnover rates were not similar across habitats. Forest had higher turnover rates than the other two habitats for all bird species. Buffer and intensive-agriculture had similar turnover rates, even though buffer habitats were situated at the forest edge. Therefore, our results demonstrate the crucial importance of conserving primary forest across the full elevational range available.

Multimode optical fiber specklegram smart bed sensor array.

SIGNIFICANCE: Monitoring the movement and vital signs of patients in hospitals and other healthcare environments is a significant burden on healthcare staff. Early warning systems using smart bed sensors hold promise to relieve this burden and improve patient outcomes. We propose a scalable and cost-effective optical fiber sensor array that can be embedded into a mattress to detect movement, both sensitively and spatially. AIM: Proof-of-concept demonstration that a multimode optical fiber (MMF) specklegram sensor array can be used to detect and image movement on a bed. APPROACH: Seven MMFs are attached to the upper surface of a mattress such that they cross in a 3 × 4 array. The specklegram output is monitored using a single laser and single camera and movement on the fibers is monitored by calculating a rolling zero-normalized cross-correlation. A 3 × 4 image is formed by comparing the signal at each crossing point between two fibers. RESULTS: The MMF sensor array can detect and image movement on a bed, including getting on and off the bed, rolling on the bed, and breathing. CONCLUSIONS: The sensor array shows a high sensitivity to movement, which can be used for monitoring physiological parameters and patient movement for potential applications in healthcare settings.

Rangeland Condition Monitoring: A New Approach Using Cross-Fence Comparisons of Remotely Sensed Vegetation.

A need exists in arid rangelands for effective monitoring of the impacts of grazing management on vegetation cover. Monitoring methods which utilize remotely-sensed imagery may have comprehensive spatial and temporal sampling, but do not necessarily control for spatial variation of natural variables, such as landsystem, vegetation type, soil type and rainfall. We use the inverse of the red band from Landsat TM satellite imagery to determine levels of vegetation cover in a 22,672 km(2) area of arid rangeland in central South Australia. We interpret this wealth of data using a cross-fence comparison methodology, allowing us to rank paddocks (fields) in the study region according to effectiveness of grazing management. The cross-fence comparison methodology generates and solves simultaneous equations of the relationship between each paddock and all other paddocks, derived from pairs of cross-fence sample points. We compare this ranking from two image dates separated by six years, during which management changes are known to have taken place. Changes in paddock rank resulting from the cross-fence comparison method show strong correspondence to those predicted by grazing management in this region, with a significant difference between the two common management types; a change from full stocking rate to light 20% stocking regime (Major Stocking Reduction) and maintenance of full 100% stocking regime (Full Stocking Maintained) (P = 0.00000132). While no paddocks had a known increase in stocking rate during the study period, many had a reduction or complete removal in stock numbers, and many also experienced removals of pest species, such as rabbits, and other ecosystem restoration activities. These paddocks generally showed an improvement in rank compared to paddocks where the stocking regime remained relatively unchanged. For the first time, this method allows us to rank non-adjacent paddocks in a rangeland region relative to each other, while controlling for natural spatio-temporal variables such as rainfall, soil type, and vegetation community distributions, due to the nature of the cross-fence experimental design, and the spatially comprehensive data available in satellite imagery. This method provides a potential tool to aid land managers in decision making processes, particularly with regard to stocking rates.