Degradation of tropical forest in Hainan, China, 1991-2008: Conservation implications for Hainan Gibbon (Nomascus hainanus)

The Hainan gibbon (Nomascus hainanus) is one of the most endangered primates in the world, confined to mature natural forest in Hainan Island, China. We assessed changes in habitat condition on the island between 1991 and 2008, using vegetation maps generated by remote-sensing images. We defined forest suitable for gibbons based on composition, tree size and canopy cover. During the 17-year period, the area of suitable gibbon forest decreased by 540 km(2) (35%) across the whole island, and by 6.3 km(2) (7%) in the locality of the sole remaining gibbon population at Bawangling National Nature Reserve. The forest patches large enough (>1 km(2)) to support a gibbon group decreased from 754 km(2) to 316 km(2) in total area, and from 92 to 64 in number. Suitable natural forest was mainly replaced by plantations below 760 m, or degraded by logging, grazing and planting of pines above 760 m. Meanwhile, forests in former confirmed gibbon areas became more fragmented: mean area of patches decreased by 53%. We mapped the patches of natural forest in good condition which could potentially support gibbons. We recommend a freeze on further expansion of plantations between core patches at Bawangling, Jiaxi-Houmiling and Yinggeling Nature Reserves in accordance with forest protection regulations; establishment of nature reserves in currently unprotected natural forest patches elsewhere in line with the local government's nature reserve expansion policy; and active natural-forest restoration between remaining fragments at Bawangling. (C) 2010 Elsevier Ltd. All rights reserved.

The Critically Endangered black crested gibbon Nomascus concolor on Wuliang Mountain, Yunnan, China: the role of forest types in the species' conservation

The Critically Endangered black crested gibbon Nomascus concolor of China, Laos and Vietnam is threatened by deforestation and habitat destruction but there have been no studies of how it uses its forest habitat, probably because of the typically rugged t

New insights into the karyotypic relationships of Chinese muntjac (Muntiacus reevesi), forest musk deer (Moschus berezovskii) and gayal (Bos frontalis)

To investigate the karyotypic relationships between Chinese muntjac (Muntiacus reevesi), forest musk deer (Moschus berezovskii) and gayal (Bos frontalis), a complete set of Chinese muntjac chromosome-specific painting probes has been assigned to G-banded chromosomes of these three species. Sixteen autosomal probes (i.e. 6-10, 12-22) of the Chinese muntjac each delineated one pair of conserved segments in the forest musk deer and gayal, respectively. The remaining six autosomal probes (1-5, and 11) each delineated two to five pairs of conserved segments. In total, the 22 autosomal painting probes of Chinese muntjac delineated 33 and 34 conserved chromosomal segments in the genomes of forest musk deer and gayal, respectively. The combined analysis of comparative chromosome painting and G-band comparison reveals that most interspecific homologous segments show a high degree of conservation in G-banding patterns. Eleven chromosome fissions and five chromosome fusions differentiate the karyotypes of Chinese muntjac and forest musk deer; twelve chromosome fissions and six fusions are required to convert the Chinese muntjac karyotype to that of gayal; one chromosome fission and one fusion separate the forest musk deer and gayal. The musk deer has retained a highly conserved karyotype that closely resembles the proposed ancestral pecoran karyotype but shares none of the rearrangements characteristic for the Cervidae and Bovidae. Our results substantiate that chromosomes 1-5 and 11 of Chinese muntjac originated through exclusive centromere-to-telomere fusions of ancestral acrocentric chromosomes. Copyright (C) 2005 S. Karger AG, Basel.

Enzyme-free glucose biosensor based on low density CNT forest grown directly on a Si/SiO2 substrate

A highly sensitive nonenzymatic amperometric glucose sensor was fabricated by using Ni nanoparticles homogeneously dispersed within and on the top of a vertically aligned CNT forest (CNT/Ni nanocomposite sensor), which was directly grown on a Si/SiO2 substrate. The surface morphology and elemental analysis were characterized using scanning electron microscopy and energy dispersive spectroscopy, respectively. Cyclic voltammetry and chronoamperometry were used to evaluate the catalytic activities of CNT/Ni electrode. The CNT/Ni nanocomposite sensor exhibited a great enhancement of anodic peak current after adding 5 mM glucose in alkaline solution. The sensor can also be applied to the quantification of glucose content with a linear range covering from 5 μM to 7 mM, a high sensitivity of 1433 μA mM-1 cm-2, and a low detection limit of 2 μM. The CNT/Ni nanocomposite sensor exhibits good reproducibility and long-term stability, moreover, it was also relatively insensitive to commonly interfering species, such as uric acid, ascorbic acid, acetaminophen, sucrose and d-fructose. © 2013 Elsevier B.V.

High contrast holograms using nanotube forest

Nanotube forest behaves as highly absorbent material when they are randomly placed in sub-wavelength scales. Furthermore, it is possible to create diffractive structures when these bulks are patterned in a substrate. Here, we introduce an alternative to fabricate intensity holograms by patterning fringes of nanotube forest on a substrate. The result is an efficient intensity hologram that is not restricted to sub-wavelength patterning. Both the theoretical and experimental analysis was performed with good agreement. The produced holograms show a uniform behaviour throughout the visible spectra. © 2013 AIP Publishing LLC.

Unconstrained monocular 3D human pose estimation by action detection and cross-modality regression forest

This work addresses the challenging problem of unconstrained 3D human pose estimation (HPE) from a novel perspective. Existing approaches struggle to operate in realistic applications, mainly due to their scene-dependent priors, such as background segmentation and multi-camera network, which restrict their use in unconstrained environments. We therfore present a framework which applies action detection and 2D pose estimation techniques to infer 3D poses in an unconstrained video. Action detection offers spatiotemporal priors to 3D human pose estimation by both recognising and localising actions in space-time. Instead of holistic features, e.g. silhouettes, we leverage the flexibility of deformable part model to detect 2D body parts as a feature to estimate 3D poses. A new unconstrained pose dataset has been collected to justify the feasibility of our method, which demonstrated promising results, significantly outperforming the relevant state-of-the-arts. © 2013 IEEE.

The Random Forest Kernel and other kernels for big data from random partitions

We present Random Partition Kernels, a new class of kernels derived by demonstrating a natural connection between random partitions of objects and kernels between those objects. We show how the construction can be used to create kernels from methods that would not normally be viewed as random partitions, such as Random Forest. To demonstrate the potential of this method, we propose two new kernels, the Random Forest Kernel and the Fast Cluster Kernel, and show that these kernels consistently outperform standard kernels on problems involving real-world datasets. Finally, we show how the form of these kernels lend themselves to a natural approximation that is appropriate for certain big data problems, allowing $O(N)$ inference in methods such as Gaussian Processes, Support Vector Machines and Kernel PCA.

Did an extensive forest ever develop on the Chinese Loess Plateau during the past 130 ka?: a test using soil carbon isotopic signatures

IEECAS SKLLQG

Nitrogen-15 signals of leaf-litter-soil continuum as a possible indicator of ecosystem nitrogen saturation by forest succession and N loads

National Key Research and Development Program [2010CB833502]; National Natural Science Foundation of China [30600071, 40601097, 30590381]; Chinese Academy of Sciences [KZCX2-YW-432, O7V70080SZ, LENOM07LS-01]; GUCAS [O85101PM03]

Impact of cloudiness on net ecosystem exchange of carbon dioxide in different types of forest ecosystems in China

Asia 3 Foresight Program [30721140307]; National Key Research and Development Program [2010CB833500]; National Natural Science Foundation of China [30590381, 30900198];