Shaanxi Guanyinshan Nature Reserve

Yuanjiazhuang, China

Shaanxi Guanyinshan Nature Reserve

Yuanjiazhuang, China
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Liu X.,Tsinghua University | Wu P.,China Agricultural University | Wu P.,Shenyang Normal University | Shao X.,China Agricultural University | And 4 more authors.
Environmental Earth Sciences | Year: 2017

During the 1970s and 1990s, Guanyinshan Nature Reserve (GNR), a giant panda (Ailuropoda melanoleuca) distribution area historically, had experienced periodic commercial logging. After officially logging stopping in 1998 and converting to a giant panda nature reserve in 2002, GNR got the chance on forest restoration. It is very necessary to monitor the spatiotemporal change of its forest habitat. It is also widely known that it is difficult to make accurate mapping the mountainous area based on images through traditional classification algorithm. So, this study aims to monitor the spatiotemporal change of mountainous habitat in GNR in order to provide proper suggestions for giant panda conservation. The research applied a multilayer perceptron model, a high learning-sensitive algorithm, to classify the land cover types and monitor habitat change in GNR by using Landsat images acquired in 1978, 1988, 1997 and 2007, respectively. Our results showed that: (1) three types of forests composed the main landscape of the GNR, and an increase of 7.7% forest coverage occurred within 30 years. (2) Due to logging, there were many forest clearing-cutting areas in 1997 and swaths of shrub–grass in 1978 and 1988. However, these two types of landscape were strongly reduced by 2007 due to more attention and protection. (3) A decrease in the number of patches, an increase in the mean patch size, and an over-time decreasing in the mean nearest neighbor distance all revealed a decreasing on habitat fragmentation. Therefore, reduction in detrimental human activities has helped enhance and expand giant panda habitat toward a healthier and more stable ecosystem. © 2017, Springer-Verlag GmbH Germany.

Wang C.,Tsinghua University | Wang C.,Jiamusi University | Liu X.,Tsinghua University | Wu P.,China Agricultural University | And 5 more authors.
Acta Theriologica Sinica | Year: 2015

In July 2009, eighteen infrared cameras were installed in Guanyinshan Nature Reserve in Shaanxi Province, located in the Liangfengya area (middle and high altitude) and the Xigou area (low altitude). We collected a total of 1 195 photos of wild boar during the 45 months from August 2009 to April 2013. We defined 9 types of wild boar behavior: standing, walking, running, feeding, drinking, preening, rutting, rooting and sitting/resting. Each of 1 195 photos was examined carefully and we summarized the percentage of each type of behavior in each season. We introduced two indices as monthly relative abundance index (MRAI) and time-period relative abundance index (TRAI) to discuss annual activity and daily activity of wild boar respectively. A simple model was used to estimate the change of population density of wild boar yearly. The results show that (1) in spring, behaviors with the great majority of wild boar are walking, feeding and standing (36%, 25.6% and 17.4% respectively); in summer, walking, standing, feeding and running are the most common behaviors (35.7%, 23.6%, 17% and 16.5% respectively); in autumn, proportions for feeding, walking and rutting are 50.3%, 19.3% and 17.8% respectively; and in winter, the behaviors of feeding, walking and standing are dominant having proportions of 53.7%, 26.7% and 11.9% respectively. (2) The activities of wild boars are more frequent in August, September and December based on the MRAI values, and wild boars are more active during the daytime according to the TRAI values. Especially, we got peak values at the period of 14:00-16:00, and low values at the period of 22:00-04:00 at the year scale. The activity patterns across the four seasons are different. (3) Finally, the population density of wild boar increased from 2009 to 2012. All of these results can help us to know population dynamics and activity patterns of wild boar, and then we might manage to take effective measures to reduce kinds of damage. ©, 2015, Science Press. All right reserved.

Liu X.,State Key Joint Laboratory of Environment Simulation and Pollution Control | Liu X.,Tsinghua University | Wu P.,China Agricultural University | Songer M.,Smithsonian Conservation Biology Institute | And 4 more authors.
Ecological Indicators | Year: 2013

Ecological indicators or indices have been widely used to simplify and measure complex ecosystems. It is critical to identify suitable indicators or indices to improve monitoring and understanding of complex natural systems. Camera trapping is an objective technique that can provide a large amount of information on wildlife. The purpose of our study is to explore the effective ecological indices for wildlife diversity analysis and monitoring in Guanyinshan Nature Reserve of Shaanxi Province, China. Since July 2009, a total of 18 cameras were installed in the reserve from August 2009 to July 2011, collecting 2115 photo captures during these 24 months. We developed five abundance indices, including relative abundance index (RAI), monthly relative abundance index (MRAI), time-period relative abundance index (TRAI), night-time relative abundance index (NRAI) and species abundance index (N) to integrate the information derived from captures. Results are: (1) 27 species were detected and 6 species had high RAI values of over 79.3%, including takin (Budorcas taxicolor), common goral (Naemorhedus goral), tufted deer (Elaphodus cephalophus), golden pheasant (Chrysolophus pictus), wild boar (Sus scrofa), and mainland serow (Capricornis sumatraensis). (2) MRAI shows a consistent monthly activity pattern of all animals being active in June and July and inactive in February. (3) TRAIs of the most abundant six species show that takin, tufted deer and common goral have the similar daily activity pattern with one peak at dawn and one peak at dusk. The daily activity patterns of golden pheasant and wild boar show that they are most active during the day time, with wild boar being particularly active at noon. NRAIs of mainland serow show the highest nocturnality and of golden pheasant the lowest nocturnality. (4) We estimated abundance of takin, tufted deer and wild boar by using our developed index. The abundance for the three species shows an increasing trend during the 2-year study period, particularly for wild boar. Our results provided an interesting comparison of species diversity and their activity patterns. As trapping continues we will have a consistent source of monitoring data to evaluate changes in species abundance and activities. Therefore, the conclusion is that the methods we used and the indices we developed are capable to estimate species activity patterns and abundance dynamics which are useful for future wildlife management in Guanyinshan Nature Reserve and elsewhere. © 2012 Elsevier Ltd. All rights reserved.

Wu P.,China Agricultural University | Liu X.,Tsinghua University | Cai Q.,Shaanxi Guanyinshan Nature Reserve | He X.,Shaanxi Foping Nature Reserve | And 3 more authors.
Acta Theriologica Sinica | Year: 2012

Since July 2009, the total 18 cameras were installed in the Guanyinshan Nature Reserve (GNR), Shaanxi Province. During our 24 months' monitoring from August 2009 to July 2011, we have collected a total of 1 755 mammal photos. The results show (1) a total of 22 mammal species were photographed. The first 6 species selected for analysis based on a relative abundance index (RAI) were Budorcas taxicolor, Naemorhedus goral, Elaphodus cephalophus, Sus scrofa, Capricornis sumatraensis and Muntiacus reevesi; their total percentage reaches 86.04%. (2) The monthly RAI (MRAI) for the whole year varies among months. The greatest value of MRAI is acquired in July and the lowest in February. (3) Three of the six selected species demonstrated similar daily activity patterns, which has two peaks, one at dawn and one at dusk. The daily pattern of Naemorhedus goral also has two peaks, but they differe from those of the previous three species. The daily activity pattern of Sus scrofa shows a peak at noon and Capricornis sumatraensis was less active at the period of 10:00-16:00. (4) The NRAI gave a clear indication of variation in nocturnality among the 6 species. Capricornis sumatraensis was most active at night and Sus scrofa was opposite.

Li Y.,Tsinghua University | Cai Q.,Shaanxi Guanyinshan Nature Reserve | Liu X.,Tsinghua University | Songer M.,Smithsonian Conservation Biology Institute | And 3 more authors.
Acta Theriologica Sinica | Year: 2016

Giant pandas(Ailuropoda melanoleuca)depend on bamboos for food, making these plants vital for their sustenance and survival. This study was carried out in Foping Nature Reserve, Shaanxi Province, China and analyzed the structure and nutritional value of two bamboo species present in the reserve at different elevations. In this region of the Qinling Mountains, the two staple food bamboos are Bashania fargesii and Fargesia qinlingensis. Our results indicate that: (1)elevation had a significant effect(P<0.05) on both the height and basal diameter of bamboos, thus strongly influencing the mean value and variance(uniformity, evenness, skewness and kurtosis)of these two characteristics in bamboo forests at different elevations. (2)The significant effects on bamboo nutrition by elevation varied with seasons(P=0.02 for crude protein and total sugar in spring; P=0.01 for crude fiber in summer; P=0.04 for crude protein and crude fiber, and P<0.01 for total sugar in autumn). The two bamboo species we studied also differed significantly with respect to how nutritional value is distributed among the leaf, branch, and culm parts of the plant(P<0.05). (3)Because elevation and seasonal conditions both affect bamboo nutrition, pandas adapt their feeding strategies accordingly: in summer, they go to higher elevation areas, and in the other three seasons they prefer lower elevations. Our research sheds light on the relationships among elevation, nutrition, and bamboo structure, along with giant panda migration patterns. In addition, this study provides a theoretical foundation for decision-making with regard to food provision for captive giant pandas. It also provides scientific support for policies to protect wild pandas and the regulation of human activity inside conservation areas. © 2016, Science Press. All right reserved.

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