Jizhou Ren

A grassland classification system and its application in China

China possesses vast grassland resources that include alpine meadow, tundra, steppe and desert. It is, therefore, desirable to establish a grassland classification system that involves the formative factors contributing to this diversity. This paper reports a grassland classification system called the Integrated Orderly Classification System of Grassland (IOCSG), which was formulated through grouping or clustering units with similar properties. The IOCSG involves a hierarchy of three classification levels. At the first level, grasslands are grouped into classes according to an index of moisture and temperature. At the second level, grasslands are differentiated as subclasses by the edaphic conditions. At the third level, grassland types within a subclass are distinguished by vegetation types. Under the IOCSG, seven thermal zones and six humidity zones have been identified and used to differentiate grassland classes. The IOCSG recognises 42 grassland Classes, of which 41 are present in China.

Integrated crop-livestock production systems in China

The integrated crop-livestock production system provides most of the food needed by the people of China. Five types of integrated production systems are recognised; rangeland, grain crops, crop/pasture, agro-silvopastoral and ponds. Development of more sustainable and integrated crop-pasture-rangeland-livestock production systems has been recently achieved. Demonstrations of the integrated systems at household, village and regional levels are occurring for rain-fed agriculture on the Loess Plateau, the Hexi Corridor, north-western China and the Karst region of Guizhou Province, south-western China. These indicate that integration of crop, livestock and forage are effective means of improving agricultural productivity, environmental sustainability and farmers’ incomes. Widespread adoption of integrated farming systems should also reduce rangeland degradation.

Modelling global-scale potential grassland changes in spatio-temporal patterns to global climate change

Grassland is one of the most widespread vegetation types worldwide and plays a significant role in global carbon cycling. Understanding the sensitivity of grassland to climate change and the effect of climate changes on the grassland ecosystems is a key issue in global carbon cycling. One of the goals of this study was to evaluate the three net primary productivity (NPP)–climate models, i.e. the Miami model, the Schuur model and the classification indices-based model. Results indicated that the classification indices-based model was the most effective model at estimating large-scale grassland NPP. In this research, changes in the spatial pattern of global potential grassland from recent past (1950–2000) to future (2001–2050) A2a scenario were analysed with the integrated orderly classification system of grassland (IOCSG) approach in a Geographic Information System (GIS) environment. NPP was evaluated with the classification indices-based model. Results indicate that under recent past climatic conditions, the main parts of global grassland are the savanna and tundra and alpine grassland and will be converted into the savanna, steppe and semi-desert grassland in A2a scenario. As a whole, areas of grassland will increase by 31.76 million hectares. The classification indices-based model estimated a 12.40% increase of total NPP in grassland from recent past to A2a scenario. It will impose a new issue for future grassland researches to support sustainable development and to provide action relevant knowledge to meet the challenge of climate change.

Outburst Flooding of the Moraine-Dammed Zhuonai Lake on Tibetan Plateau: Causes and Impacts

The Kekexili region of the Tibetan Plateau has become warmer and wetter since the 1960s, resulting in a significant expansion of Zhuonai Lake (+0.46 km2/year, p <; 0.05) before an outburst flood event occurred on September 15, 2011, and mapped by the Chinese Huanjing (HJ)-A/B satellites with a two-day revisit ability and a 360-km orbit swath. The direct cause of the outburst was due to relatively heavy precipitation from May to September 2011, specifically the continuous rainfall from later August to middle September. Two nearby earthquakes that occurred two months before the outburst might have impacted the natural structure of the lakebed and moraine dam to accelerate the outburst. The outburst event of Zhuonai Lake caused large environmental impacts on the region: 1) the desertification of the exposed lakebed of Zhuonai Lake; 2) the significant expansion of the three downstream lakes Kusai, Haidingnuoer, and Salt Lakes that not only caused the grassland reduction and deteriorations but also the potential threat to the operations of the Qing-Tibet Railway and Highway; and 3) the calving relocation of Tibetan antelopes to the shore area of Kusai Lake due to the deep cutting riverbanks caused by the overflow of Zhuonai Lake. This study provides some scientific clues or alerts for local or central governments to pay some attention on this very issue so that possible future devastative disasters and environmental damages would be avoided or mitigated.

Herders’ opinions about desirable stocking rates and overstocking in the rangelands of northern China

Herders’ desirable stocking rates and their opinions of overstocking were studied using survey and multi-regression methods in the meadow steppe, typical steppe and desert steppe regions of northern China. It was found that individual herders had their own perception of their particular ‘desirable stocking rate’, which referred to the number of livestock that the herders thought they could keep or maintain on an area of rangeland over a specified period of time. These perceptions were not in line with the ‘balancing animals and grass’ policy of the Chinese government, and herders used them as a guide to adjust stock-breeding practices. Most herders admitted that they bred more livestock now than 10 years ago, but insisted that there was no overstocking and many even thought that their rangelands could still carry more livestock. They also held the view that they took into account the carrying capacity of rangelands when making decisions about livestock-breeding practices. Individual herders thought that the reasonable stocking rate range should be 0.75–1.50 sheep units ha–1 (meadow steppe), 0.60–1.50 sheep units ha–1 (typical steppe), and 0.50–0.75 sheep units ha–1 (desert steppe), respectively. The herders from the desert steppe regions were most concerned about the overstocking of rangelands, and the concern of herders was in the order desert steppe > typical steppe > meadow steppe. The herders with more formal education and those who worked in a village council and had smaller areas of rangelands, were more concerned about the overstocking of rangelands. It is argued that such herders should be given more access to policy and market information, including extensive grazing and modern stall-feeding technologies, and encouraged to reduce their desirable stocking rates, leading to more sustainable rangeland management in northern China.

Spatio-temporal dynamics on the distribution, extent, and net primary productivity of potential grassland in response to climate changes in China

Net primary productivity (NPP) of grassland is one of the key components in measuring the carrying capacity of livestock. Not only are grassland researchers concerned with the performance of NPP simulation models under current climate conditions, they also need to understand the behaviour of NPP–climate models under projected climatic changes. One of the goals of this study was to evaluate the three NPP–climate models: the Miami Model, the Schuur Model, and the Classification Indices-based Model. Results indicated that the Classification Indices-based Model was the most effective model at estimating large-scale grassland NPP. Both the Integrated Orderly Classification System of Grassland and the Classification Indices-based Model were then applied to analyse the succession of grassland biomes and to measure the change in total NPP (TNPP) of grassland biomes from the recent past (1950–2000) to a future scenario (2001–2050) in a geographic information system environment. Results of the simulations indicate that, under recent-past climatic conditions, the major biomes of China’s grassland are the tundra and alpine steppe, and steppe, and these would be converted into steppe and semi-desert grassland in the future scenario; the potential grassland TNPP in China was projected to be 0.72 PgC under recent-past climatic conditions, and would be 0.83 Pg C under the future climatic scenario. The ‘safe’ carrying capacity of livestock that best integrates a wide range of factors, such as grassland classes, climatic variability, and animal nutrition, is discussed as unresolved. Further research and development is needed to identify the regional trends for the ‘safe’ carrying capacity of livestock to maintain sustainable resource condition and reduce the risk of resource degradation. This important task remains a challenge for all grassland scientists and practitioners.