Quantitative analysis of land mammal zoogeographical regions in China and adjacent regions

Quantitative analysis of land mammal zoogeographical regions in China and adjacent regions. Zoological Studies 43(1): 142-160. In this paper, our aim was to determine, by means of quantitative analysis, the distribution patterns of the land mammals in China and, adjacent regions using physiographical regions as operative geographical units (OGUs). Based, on the pre-sence or absence of 11 orders, 42 families, 197 genera, and 577 species of land mammals in their zoogeographical regions, which were used as OGUs, we studied the biotic boundary between the Oriental Region (OR) and the Palaearctic Region (PR), as well as subregion boundaries. The boundary's statistical significance was tested by G-test as described by McCoy et al. A significantly strong biotic boundary was found to separate the PR from the OR, and there is a weak biotic boundary in the PR, which divides it into 2 subregions. We concluded that the biotic boundary which separates the PR and OR is a strong boundary. We suggest that the Qinghai-Xizang Plateau should be regarded as a subregion of the PR, which can embody its characteristics of high elevations and a frigid climatic, which is called the Qing-Zang subregion of the PR (QZSP).

Amino acid requirements for maturation of rhesus monkey (Macacca mulatta) oocytes in culture

This study evaluated the effects of different amino acid formulations on supporting meiotic and cytoplasmic maturation of rhesus monkey (Macacca mulatta) oocytes in vitro. Five hundred and forty-six cumulus-oocyte complexes (COCs) aspirated from unstimulated adult monkey follicles (greater than or equal to 1000 mum in diameter) were cultured in either modified Connaught Medical Research Laboratories 1066 medium (mCMRL-1066) or in one of eight chemically defined media (modified basic medium 5 supplemented with 5.5 mmol glucose l(-1), 0.003 mmol pantothenic acid l(-1) and different amino acid formulations) as below: (1) modified basic medium 5 (mBM5) containing no amino acid; (2) mBM5 + 0.2 mmol glutamine l(-1); (3) mBM5 + 11 amino acids from hamster embryo culture medium 6 (HECM-6) (11 AA); (4) mBM5 + Eagle's non-essential amino acids (NEA); (5) mBM5 + NEA + 0.2 mmol glutamine l(-1); (6) mBM5 + Eagle's essential amino acids (EA) without glutamine; (7) mBM5 + EA + 0.2 mmol glutamine l(-1); (8) mBM5 + Eagle's 20 amino acids (20 AA) + 0.2 mmol glutamine l(-1); and (9) mCMRL-1066 (control). All media contained FSH, LH, oestradiol and progesterone. After maturation, mature oocytes were subjected to the same fertilization and embryo culture procedures. COCs matured in treatment 5 had greater potential to progress to metaphase II (66%; P < 0.05) than did those in treatments 1 (37.3%), 2 (48.3%)f 3 (41%), 6 (41%) and 9 (43%). Oocytes matured in treatment 8 had the best morula (53%) and blastocyst (18%) developmental responses (P<0.05). The lowest (P<0.05) morula and blastocyst developmental responses were obtained from COCs matured in treatments 1 (0%) and 6 (8%). The other media supported intermediate embryonic development (range 11-38% of morula and blastocyst). These results indicate that the choice of amino acids affects the competence of oocyte maturation and that Eagle's 20 AA with 0.2 mmol glutamine l(-1) is more efficient than the other amino acid formulations for maturation of rhesus monkey oocytes.

Requirements-based development of an improved engineering change management method

Engineering changes (ECs) are essential in complex product development, and their management is a crucial discipline for engineering industries. Numerous methods have been developed to support EC management (ECM), of which the change prediction method (CPM) is one of the most established. This article contributes a requirements-based benchmarking approach to assess and improve existing methods. The CPM is selected to be improved. First, based on a comprehensive literature survey and insights from industrial case studies, a set of 25 requirements for change management methods are developed. Second, these requirements are used as benchmarking criteria to assess the CPM in comparison to seven other promising methods. Third, the best-in-class solutions for each requirement are investigated to draw improvement suggestions for the CPM. Finally, an enhanced ECM method which implements these improvements is presented. © 2013 © 2013 The Author(s). Published by Taylor & Francis.

Decision tree classification of land cover from remotely sensed data

Decision tree classification algorithms have significant potential for land cover mapping problems and have not been tested in detail by the remote sensing community relative to more conventional pattern recognition techniques such as maximum likelihood classification. In this paper, we present several types of decision tree classification algorithms arid evaluate them on three different remote sensing data sets. The decision tree classification algorithms tested include an univariate decision tree, a multivariate decision tree, and a hybrid decision tree capable of including several different types of classification algorithms within a single decision tree structure. Classification accuracies produced by each of these decision tree algorithms are compared with both maximum likelihood and linear discriminant function classifiers. Results from this analysis show that the decision tree algorithms consistently outperform the maximum likelihood and linear discriminant function classifiers in regard to classf — cation accuracy. In particular, the hybrid tree consistently produced the highest classification accuracies for the data sets tested. More generally, the results from this work show that decision trees have several advantages for remote sensing applications by virtue of their relatively simple, explicit, and intuitive classification structure. Further, decision tree algorithms are strictly nonparametric and, therefore, make no assumptions regarding the distribution of input data, and are flexible and robust with respect to nonlinear and noisy relations among input features and class labels.

A methodology of characterizing status and trend of land changes in oases: A case study of Sangong River watershed, Xinjiang, China

National Natural Science Foundation of China [40471134]; program of Lights of the West China by the Chinese Academy of Science

Spatial patterns and driving forces of land use change in China during the early 21st century

Land use and land cover change as the core of coupled human-environment systems has become a potential field of land change science (LCS) in the study of global environmental change. Based on remotely sensed data of land use change with a spatial resolution of 1 km x 1 km on national scale among every 5 years, this paper designed a new dynamic regionalization according to the comprehensive characteristics of land use change including regional differentiation, physical, economic, and macro-policy factors as well. Spatial pattern of land use change and its driving forces were investigated in China in the early 21st century. To sum up, land use change pattern of this period was characterized by rapid changes in the whole country. Over the agricultural zones, e.g., Huang-Huai-Hai Plain, the southeast coastal areas and Sichuan Basin, a great proportion of fine arable land were engrossed owing to considerable expansion of the built-up and residential areas, resulting in decrease of paddy land area in southern China. The development of oasis agriculture in Northwest China and the reclamation in Northeast China led to a slight increase in arable land area in northern China. Due to the "Grain for Green" policy, forest area was significantly increased in the middle and western developing regions, where the vegetation coverage was substantially enlarged, likewise. This paper argued the main driving forces as the implementation of the strategy on land use and regional development, such as policies of "Western Development", "Revitalization of Northeast", coupled with rapidly economic development during this period.

Assessing the consequence of land use change on agricultural productivity in China

China's cultivated land has been undergoing dramatic changes along with its rapidly growing economy and population. The impacts of land use transformation on food production at the national scale, however, have been poorly understood due to the lack of detailed spatially explicit agricultural productivity information on cropland change and crop productivity. This study evaluates the effect of the cropland transformation on agricultural productivity by combining the land use data of China for the period of 1990-2000 from TM images and a satellite-based NPP (net primary production) model driven with NOAH/AVHRR data. The cropland area of China has a net increase of 2.79 Mha in the study period, which causes a slightly increased agricultural productivity (6.96 Mt C) at the national level. Although the newly cultivated lands compensated for the loss from urban expansion, but the contribution to production is insignificant because of the low productivity. The decrease in crop production resulting from urban expansion is about twice of that from abandonment of arable lands to forests and grasslands. The productivity of arable lands occupied by urban expansion was 80% higher than that of the newly cultivated lands in the regions with unfavorable natural conditions. Significance of cropland transformation impacts is spatially diverse with the differences in land use change intensity and land productivity across China. The increase in arable land area and yet decline in land quality may reduce the production potential and sustainability of China's agro-ecosystems. (C) 2008 Elsevier B.V. All rights reserved.

Study on spatial pattern of land-use change in China during 1995-2000

It is more and more acknowledged that land-use/cover dynamic change has become a key subject urgently to be dealt with in the study of global environmental change. Supported by the Landsat TM digital images, spatial patterns and temporal variation of land-use change during 1995 -2000 are studied in the paper. According to the land-use dynamic degree model, supported by the 1km GRID data of land-use change and the comprehensive characters of physical, economic and social features, a dynamic regionalization of land-use change is designed to disclose the spatial pattern of land-use change processes. Generally speaking, in the traditional agricultural zones, e.g., Huang-Huai-Hai Plains, Yangtze River Delta and Sichuan Basin, the built-up and residential areas occupy a great proportion of arable land, and in the interlock area of farming and pasturing of northern China and the oases agricultural zones, the reclamation I of arable land is conspicuously driven by changes of production conditions, economic benefits and climatic conditions. The implementation of "returning arable land into woodland or grassland" policies has won initial success in some areas, but it is too early to say that the trend of deforestation has been effectively reversed across China. In this paper, the division of dynamic regionalization of land-use change is designed, for the sake of revealing the temporal and spatial features of land-use change and laying the foundation for the study of regional scale land-use changes. Moreover, an integrated study, including studies of spatial pattern and temporal process of land-use change, is carried out in this paper, which is an interesting try on the comparative studies of spatial pattern on change process and the change process of spatial pattern of land-use change.