Identification and evaluation of desertification reversal in China: indicators and methods review

Ning Liu , LiHua Zhou , Yong Chen , Shan Huang

1. Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou,Gansu 730000, China

2. China Development Bank Qinghai Branch, Xining, Qinghai 810001, China

1 Introduction

Desertification, the process of land degradation in arid, semi-arid and dry sub humid areas resulting from various factors, is a worldwide phenomenon affecting about one-fifth of the world population, 10%–20% of all dry lands and 8% of the total land area of the world(Millennium Ecosystem Assessment, 2005; Helldén,2008). In China, the annual expansion rate of sandy desertified lands for the past five decades was 1,560 km2from the late 1950s to 1975, 2,100 km2between 1975 and 1987 and 3,600 km2from 1987 to 2000(Wanget al., 2004a). Commonly accepted causation of desertification is interaction of a set of natural(bio-physical) and anthropogenic factors with different temporal and spatial variability (Rubio and Bochet,1998; Zhouet al., 2013). As a serious environmental problem, desertification has already reduced land productivity and overburdened the ecological system,thus jeopardizing economic growth and inducing poverty (Abdelgalil and Cohen, 2007; Chenet al.,2012). A more troubling trend is the accelerating rate of global environmental problems associated with desertification, with political and socio-economic ramifications, particularly in developing nations(Daily, 1995; Abuduwailiet al., 2010).

Rehabilitation is the desired outcome in combating desertification. This requires converting degraded land into productive land, especially in the agro-pastoral zone, which depends on identification of degraded areas and assessment of desertification severity (Guoet al., 1989; Chenet al., 1996; Zha and Gao, 1997; Millennium Ecosystem Assessment, 2005).There have been numerous attempts to rehabilitate degraded land globally, which is highly significant for the food supply, biodiversity conservation, energy balance, resource distribution and economic development in desertified regions. Desertification can be curbed or even reversed by adopting prevention and control measures with ecologically sound land-use practices in China (Wanget al., 2008; Mohammad,2012). In some desertified regions, rehabilitation has occurred (Daily, 1995), particularly in China (Wanget al., 2004b). The annual rehabilitation rate of desertified land in northern China was 3,600 km2in recent years (Wang, 2008). However, several problems are still hindering the process. First, endeavors and impact of large scale rehabilitation projects are few and difficult to validate (Daily, 1995). Second, the time consumed in rehabilitation varies in different regions of specific conditions but are generally quite long(Daily, 1995). Third, most degraded areas with known histories have not yet recovered and degradation in some areas is irreversible. And fourth, the potential for accelerating recovery, rehabilitation identification,and rehabilitation assessment are difficult to implement. Also, degradation and rehabilitation are also diversified in cause, performance and intervention,which make intervention identification and assessment and its outcome even more complicated or worse.

The effect of natural factors is complicated and uncontrollable in desertification rehabilitation in regards to a short time span, thus the focus is on anthropogenic activity (Maet al., 2006; Liet al., 2008;Xuet al., 2008; Jiaet al., 2009; Zhanget al., 2009).Thus, the means by which to evaluate anthropogenic activity through sustainability, cost and benefits analysis, public interest and individual behavior with an ecologic/economic concern is thereby a necessity.Consequentially, an inevitable prerequisite for evaluation is an overall method for rehabilitation identification (including indicator selection) (Figure 1).

Although there is little consensus for the identification and evaluation of desertification rehabilitation,such a consensus is in urgent demand. Indictors and system identifications are scattered and evaluation models or experiences specific to desertification rehabilitation, to our knowledge, is rare. Here, we provide a systematic argument for the identification and evaluation of desertification rehabilitation based on previous literature. During this process we incorporated sustainability, cost and benefits analysis, public interest and individual behavior.

Figure 1 The outline and relationship between identification and evaluation of desertification rehabilitation

2 How to identify desertification rehabilitation

To evaluate desertification rehabilitation, irrelevant of ecological or mainstream economics, its identification is essential and of primary importance. At present, the definition and method to assess and monitor desertification (Mabbutt, 1986) is under debate,thus there is no consensus on this matter. Also, available literature on desertification rehabilitation is limited, especially on desertification identification (see table 1). As defined by Millennium Ecosystem Assessment (2005), rehabilitation is a reversal process of desertification. Thus, it is plausible to use the reversal process as an indirect method to account for desertification identification and rehabilitation. Thereby, two methods can be used, direct identification which nominally confronts rehabilitation as the results, and indirect identification which involves the reversal process of desertification.

2.1 Direct identification

Most available data on desertification rehabilitation are from China. In respect to rehabilitation achievement, direct indicators outlined by Zha and Gao (1997) and Gaoet al. (2001) include increase oasis area (plantation of shrub and grass) and size decrease of desertification areas. Xuet al. (2010)adopted potential and actual net primary production(NPP) to access relative roles of climate change and anthropogenic activity in desertification, especially in rehabilitation and expansion processes. Huanget al.(2013) concluded that changes of the water environment play an important role in the process of long-term desertification. Suet al. (2007) identified vegetation cover, soil development and sand transportation rate during sandstorm events in the restoration area and the untreated control area as assessment of long-term effects of the ecological restoration of desertification on an oasis environment.

Table 1 List of desertification identification and rehabilitation

However, the most comprehensive framework for direct identification of desertification rehabilitation was proposed by Zhaoet al. (2008), which can be stage summary of theory though limited in empirical estimation. By clarifying concept disparity, geographic diversity and categories of desertification, the authors listed three core subsystems which affect each other and are made up of multiple second-level variables (see table 2). They also explored availability and feasibility of the framework and argued that component variables should be specifically selected depending on natural and economic conditions of the research region.

Additionally, change in water infiltration and its positive feedback relation with vegetation cover and the possible relation with livestock removal mediated by soil compaction (Castellano and Valone, 2007) are the focus of theoretical explanations for desertification rehabilitation, which was empirically supported by evidence of livestock closure (Fuhlendorfet al.,2001; Rasmussenet al., 2001; Valoneet al., 2002).Land use also has an impact on land desertification,and there are significant correlations between different land covers and key factors such as water bodies and annual precipitation, river beach and runoff, areas of shifting dunes and annual precipitation, as well as cropland and underground water table (Zhaoet al.,2010).

Table 2 Direct measuring framework of positive and negative processes of land desertification (from Zhao et al., 2008)

2.2 Indirect identification

An alternative to direct identification of desertification rehabilitation is the indirect method. Although desertification identification is divergent to some extent, on the basis of an accepted indicator system of desertification selected from a theoretical framework affected by local characters, a positive variation of these indicators can reliably explain desertification rehabilitation. Hereinafter, a review of indicators system of desertification will be given separately from global and Chinese experience.

Before the introduction of desertification indicators, it is necessary to indentify causes of desertification and determinants of indicators system. Many studies suggested that anthropogenic activity is the major contributor to desertification in arid and semiarid regions; Wang XMet al.(2008) presented several lines of evidence to demonstrate that this activity,guided by policy shifts, is the major force driving aeolian desertification via changes in land-use patterns and intensity. Some European studies strongly emphasize the nature-human coupled impact (Rasmussenet al., 2001; Salvatiet al., 2008; Ladisaet al., 2011).Wang Tet al. (2008) argued that descriptive evidence from Chinese studies cannot explain why the three proxies for human impact, human population, livestock, and areas devoted to agriculture, have increased continuously since the 1950s, yet rehabilitation has occurred since the 1990s. Another fact is that land rehabilitation has occurred in many parts of arid and semiarid areas of China before the launch of land rehabilitation techniques to combat desertification(Wang Tet al., 2008). Some studies also assert that two climatic variables, drift potential and frequency of sand-driving winds, had a much stronger effect than has been appreciated in previous research, and the impact of anthropogenic activity on environmental change may thus have been overestimated (Wanget al.,2006). However, Wang Tet al. (2008) insisted that anthropogenic activity is not the primary cause of desertification or rehabilitation, and that public opinion and governmental decisions towards desertification are at odds with each other (Zhuet al., 1980, 1981; Zhu and Liu, 1982; Zhu and Chen, 1994; Wanget al., 2003,2004a, 2006; Yanget al., 2005; Liu, 2006).

Numerous methods exist to evaluate desertification such as direct observation and identification,mathematical models and parametric equations, in the perspective of scale of monitoring and types of variables (Berry and Ford, 1977; Reining, 1978; Rubio and Bochet, 1998), which are debated based on choice and application of indicators (Mabbutt, 1986). Commonly,these restrictions are from lack of perception, information about the environment before degradation and information about the contribution of each process involved in global desertification. These restrictions are also from multiple definitions of the desertification concept, overlap of mechanisms and factors acting with different intensities and times, and biological and social interactions (Rubio and Bochet, 1998).Similarly, problems in Chinese desertification research include uncertainty of baseline assessments and indictor systems, and the misuse of remotely sensed data sources (Yanget al., 2005).

To assess desertification risk in Europe, Rubio and Bochet (1998) proposed indicators including soil(water and wind erosion, and physical, chemical, and biological degradation), climate, vegetation, topography and social-economics. As an adjustment of the Environmental Sensitive Areas model, Ladisaet al.(2011) also selected soil, climate, vegetation, land use management and human pressure index covering complicated sub-indicators. Sepehret al. (2007), in a quantitative assessment of desertification using the MEDALUS method with limited variation, adopted indicators such as soil, climate, erosion, plant cover,groundwater and management.

It is obvious that these indicators represent natural and social influences but trend toward natural impact,and soil, climate and vegetation are common selections. However, Salvatiet al. (2008) included population (human density, population growth, urban sprawl and soil consumption), tourism (human pressure, unsustainable water management and increasing density),agriculture (land abandonment, aging landholders and unsustainable irrigation) and industrialization (soil pollution, water pollution and soil consumption) in the social system. This system is based on experience from the Mediterranean, in which the interference between human and nature has produced a new socio-ecological system, contributing more to human than natural welfare although desertification does not occur without anthropogenic activity.

Chinese scholars have put forward several indicator sets. Sunet al. (2006) developed a community level land desertification Risk Index (RI) with 20 selected social-economic factors. Sunet al. (2006) explored spatial and temporal variability of desertification risk in the study area and found that temporal variation is a contributor to desertification, and that average number of sheep per-household and changes in ridge crop planting area are also important indicators of change in desertification risk. Wanget al.(2008), nevertheless, excluded the adaptation of annual rainfall in temporal trend explanation of desertification because total annual precipitation did not show a significant decrease or increase in arid and semiarid areas of China. They argue that spring precipitation, regional wind regimes and trends in potential sand transport were closely related to desertification or rehabilitation.

3 How to evaluate desertification rehabilitation

Valuation is the process by which to estimate the contribution of goods or services towards a goal(Costanzaet al., 1998), and has been gradually recognized by private and public sectors as biophysical and ecological bases of value (Straton, 2006). Numerous literature and models have been devoted to the evaluation of ecological systems or products, but are limited in desertification rehabilitation.

Considering that desertification is a type of land degradation, the applicability of evaluation models for ecological products is plausible in desertification and rehabilitation. The following sophisticated formulation models exhibit two apparent trends. The first model is usually proposed by ecologist to model ecological service or product in an ecological economic analysis framework. The second model is usually proposed by economist to value an ecological service or product in the perspective of economics.

3.1 Economic evaluation

Ecological service or product plays a crucial role in sustainability for current and future production of the economic system (Common and Perrings, 1992;Costanzaet al., 1997; De Grootet al., 2002). However, modern neoclassical conceptualization of value incorporates a convergence of supply and demand.This produces equilibrium but market-clearing price apparently fails to explain non-market value of ecological service (Georgescu-Roegen, 1975). Thus, numerous early attempts and models have contributed to conceptualization of ecosystem service, products,their economic value and benefits to human society(e.g., Helliwell, 1969; Hueting, 1970; Binghamet al.,1995; Costanzaet al., 1997; Dailyet al., 2000). In recent years, Costanzaet al. (1997) and De Grootet al.(2002) argued for a new classification of the ecosystem into 17 categories in 16 biomes, and Farberet al.(2002) and Straton (2006) provided a dedicated conceptual analysis framework.

The approaches to estimating a non-market ecosystem argued by Sinden (1994) are a conceptually-correct manner and a partial values estimation method, while two principles of Straton (2006) are demand-side valuation and supply-side valuation.Arguments of Sinden and Griffith (2007) are willingness to pay, opportunity cost and market price which seem to be specific methods involved in the framework of Sinden (1994) and Straton (2006). Irrelevant of conceptualization structure, specific methods covered by these opinions are not much different and are mainly contingent valuation, defensive expenditure,replacement (restoration or relocation) cost, travel cost, productivity cost, hedonic pricing, and market value (Sinden and Griffith, 2007) (Table 3).

Table 3 List of economic method to value

The contingent valuation, under willingness to pay of Sinden and Griffith (2007) and under demand-side value estimation of Straton (2006) is the most popular real time application method (e.g., Xuet al. (2003)adopted Contingent Valuation Method in rural China to estimate the willingness to pay for restoring a local ecosystem service). However, both demand-side and supply-side value estimation can explain the aforementioned methods (Straton, 2006), but has a range of limitations. These limitations include neglecting objective biophysical properties of demand side ecological resource, and failing to provide true welfare identification and valuing the outcome of certain policies rather than the ecosystem product or service itself(Heal, 2000; Patterson, 2002; Straton, 2006). Although the aforementioned methods have their limitations, the new framework of Farberet al.(2002) and Straton (2006) are conceptual and difficult to apply to current situations.

3.2 Ecological evaluation

The ecologist’s perspective of value comes from contribution of products or services to the achievement of some system goal. This perspective usually ignores social processes and human preferences that guide resource use, while economists also ignore the biophysical and ecological processes that sustain ecosystem goods and services (Straton, 2006). Thus,Straton (2006) adopted a complex systems approach including ecological value based on theories of ecology and human value (called subjective value) based on theories of psychology, institutions and decision-making. Actually, ecologists indeed involve an economic segment into their preference, but the ecological segment is still the focus.

Potential Direct Instrumental Value (PDIV) is the choice of Daily (1995) to estimate restoring value of degraded land including desertification area from a purely biophysical (as opposed to socioeconomic)perspective. PDIV estimates direct benefits from which land can provide to society, but does not involve indirect, option, or nonuse values and is thus a conservative identification of value (Daily, 1995). Net Primary Productivity (NPP) is the choice of Xuet al.(2009) to estimate the desertification process, which combines climate change impact and anthropogenic activity to NPP variation. As a similar but inverse concept of NPP to some extent, PDIV also could be an indicator for desertification identification.

Based on the thermodynamic concept of energy as a unified identification for environmental resources and economic products, Chenet al. (2009) developed a framework of ecological economics to assess Chinese agriculture. Jogo and Hassan (2010) developed an ecological model by system dynamics framework.They took into consideration the feedback effects between ecological and economic systems as well as trade-offs in the supply of individual constituents of the bundle of multiple services provided by wetlands.Their aim was to analyze the impact of various management and policy regimes on functioning wetlands and economic well-being.

Additionally, a spatial decision support system originating from the integration of ecological and socio-economic assessment methods, scale-specific and GIS-based data and knowledge modeling and visualization techniques was used to improve water quantity and quality at a micro-, meso- and macro-scale (Volket al., 2008). Contingent valuation method was used to evaluate the eco-economic benefit values of desertification reversion in Yanchi County of Ningxia,China (Zhanget al., 2013). A regional Vulnerability Evaluation Model (VEM), able to assess land vulnerability over time by way of a composite index integrating ecological and economic indicators of land degradation vulnerability, was used in a multi-way data analysis (Salvati and Zitti, 2009). More other models there are such as Krameret al.(1997).

The aforementioned studies placed an emphasis on social-economics, but it is easy to find a preference for an ecological foundation.

3.3 Other evaluations

Even significant studies focus on the value of natural products, some methods are still of new significance. To answer and solve the Public Tragedy from Hardin (1968), Ostrom (2009) proposed a general framework for analyzing sustainability of social-ecological systems which addressed cost and benefits analysis for individual behavior in natural resource conservation in short and long term. Liet al.(2006a) established an indicators system for sustainable development of desertification and processed a validation research (Liet al., 2006b). Dong (1997)and Liu (2006) separately calculated a reference value for desertification economic loss in China. Their method may also estimate desertification rehabilitation with decrease trend of economic value if applicable. Similarly, UNEP estimated the direct, on-site cost of failure to prevent desertification, and they estimated the direct annual cost of prevention and rehabilitation (Daily, 1995).

4 Discussions

At present, there is no universally accepted method for identification and assessment of desertification rehabilitation, irrelevant of economics or ecology.Thus, a need for a theoretical framework under which the details can be modified is imperative, particularly with empirical evidence from successful cases and areas, given the diversity of desertification in causes,performance and intervention.

傳統(tǒng)必不可少，但并不代表其完美，新舊傳統(tǒng)的不斷調(diào)整和適應(yīng)造成了傳統(tǒng)的變遷。這些因素可分為內(nèi)部調(diào)適和外部調(diào)適。

4.1 Indicators to identify desertification rehabilitation

Though direct desertification identification is sometimes unavailable, it is still the primary choice.Considering the diversity of desertification in many aspects, indirect identification is applicable if necessitated data are unavailable and direct identification is impractical. Thus, the selection of desertification identification strategy is dependent on natural and economic conditions.

Comparatively, the method of Zhaoet al.(2008)is a comprehensive direct system. It covers three core subsystems, natural factors, human factors, soil and vegetation. Other studies can also be categorized to this framework (e.g., Castellano and Valone, 2007; Suet al., 2007). However, we argue that area decrease of desertification is an obvious indicator although it may not be convincingly conspicuous in some areas (see table 2). Net primary production (NPP) and PDIV could also be complementary evidence but not determinants if estimation is available. Finally, admitting the dominance of core problems and diversity of real conditions, the framework of Zhaoet al. (2008) plus area decrease of desertification is first valuable and useful in direct identification, but also should be modified or shaped up properly.

When direct identification is impractical, indirect identification is a qualified substitute, although selection of indicators of course will be more ambiguous(see table 1). Zhaoet al. (2008) mentioned indirect desertification identification, and also proposed a system to identify desertification, called the positive process of desertification, but this system is not complete. Actually, the challenge for indirect identification is nearly the same for direct identification, which is the choice and application of indicators (Mabbutt,1986).

Estimation from the perspective of natural and social factors is applicable and practical even if this estimate is not precise due to variability of these factors.Soil quality, climate, vegetation, water including groundwater and precipitation, and topography are commonly used in the selection of natural factors (e.g.,Rubio and Bochet, 1998; Sepehret al., 2007; Ladisaet al., 2011). Selecting suitable indicators is a matter of choice and more experiments and quantitative analysis will be a necessary to refine those choices which will be a huge challenge.

Although most estimates involve social factors,which are not as organized as natural factors, their preference is natural causes (e.g., Rubio and Bochet,1998; Sepehret al., 2007; Ladisaet al., 2011). Some studies only explored the social factors but the indicators they adopted are always disparate. Generally,commonly used indicators are population growth,tourism, agriculture and industrialization. Here, we argue that social indicators are influenced by economic growth, economic models and governmental policies (especially land and water management),thereby these factors and variation of land productivi-ty should be included. Other methods like RI, and NNP (we insist that PDIV is a natural rather than a social indicator) are only for identification where anthropogenic impact has been documented as the primary cause, but only complementary validated.

For serious identification, prudent selection of indicators (and/or weight between natural and social indirect identification) cannot be overemphasized,which will determine the efficiency and accuracy of identification. Irrelevant of deliberate indicator framework, static analysis cannot tell the whole story because of desertification dynamics which confine both direct and indirect identifications. Present studies,however, are usually weak in answering the question properly and comprehensively. Comparative static analysis is a way to cope with, but needs more support data and analysis skills, which is often dependent on availability and usability of experiments and data collection. However, dynamic analysis is a powerful tool and should be processed as much as possible.

4.2 Mode selection of evaluation

Only if evidence from identification is documented, can desertification rehabilitation evaluation be accomplished, which is significant and applicable for initiating and accelerating the process, particularly under the framework of sustainable development and,cost and benefits analysis. Though some natural rehabilitations have been reported (Wanget al., 2008),most attempts are initiated and driven by anthropogenic interest at a regional policy level.

As Daily (1995) noted, studies of succession have shown that rehabilitation of degraded land where desertification is included usually have experienced volcanic eruption, shifting cultivation, continuous agricultural production followed by abandonment, or reclamation. Experiences in China are quite similar but trend to government dominated modes where transition of economic modes, land abandonment and conservation (e.g., grazing prohibition and return of cultivated land to forests), artificial increase of vegetation cover, water management and scientific intervention are the main factors.

Given this ambiguity, it is not only an ecological problem, but rather an ecological economic problem incorporating political implications. Society needs to balance (1) tradeoff between the present and next generations, (2) economic growth and environment,and (3) public and individual interests. Essential to reply and address these problems is not other but just the rational evaluation of the phenomenon.

As previously discussed, neither a pure economic nor ecological evaluation is desired, but current models of ecological economic evaluation are not sufficient and lack rational synthesis and consistency(Straton, 2006). Literature and specific models on ecological economic evaluation of desertification rehabilitation are limited, Daily (1995) is a case, most are focused on land degradation rather than only desertification. Certainly, massive models on ecological products or services are available.

Actually, most value models on ecological products or services are theoretical deduction with empirical cases which can be modified for all ecological issues or processes. Another valuable possibility is that comparable ecological issues to desertification rehabilitation can enlarge the scope of literature.

Although failing in the non-market value of ecological service (Georgescu-Roegen, 1975) and having inevitable deficiencies for both supply and demand based approaches (Georgescu-Roegen, 1975; Straton,2006), models derived from modern neoclassical economics can have effective reference estimation.

Daily (1995) is a pioneer but his method is not comprehensive, while other attempts like WTA/WTP,or the loss value approach only supplementary but surely, not determinable ones. Comparatively, the defensive expenditure approach is a plausible option.This approach was used by Sinden and Griffith (2007)to value environmental gains in the control of 35 weeds in Australian is just a selection to identify gain of mitigating a natural disaster. Desertification rehabilitation can be the result of desertification mitigation,even if the causes are mainly ascribed to climate, and thereby a comprehensive analysis incorporated with local realities in defensive expenditure approach is applicable. However, it is not much different from other models listed in table 3.

Here, we will accentuate the general framework for analyzing sustainability of social-ecological systems of Ostrom (2009). This framework rationally divides the social-ecological system, and outlines strategies to process sustainable analysis, cost and benefit analysis, public interest and individual behavior analysis for natural resources in the short and long term (see figure 2). It also elegantly settles the ambiguity of ecological and economic approaches questioned by Straton (2006), to some extent. We argue that desertification rehabilitation faces issues proposed by Ostrom (2009), and should be a practicable case to be explained and to validate the theoretic framework.

Similarly, limitation of static analysis is also a vital drawback of desertification rehabilitation evaluation. Desertification is a dynamic process; and is the same for rehabilitation and its identification and evaluation. Comparative static analysis is an attempt to process. Thus, the point we argue in the whole process is that the selection of detail approaches has to be variable and depend on available data and natural and economic conditions.

Figure 2 A regional model of desertification rehabilitation (according to Ostrom, 2009)

5 Conclusions

Anthropogenic pressure and challenge from desertification or land degradation have in a large way critically affected human existence and the environment in many aspects. This threat is real where integral and positive measures need to be enacted without delay.Actually, many attempts have already been put into practice, but whether they are effective, sustainable and cost saving is under debate.

After a prudent and comprehensive review of recent literature, we emphasize the logical and sequential importance of desertification identification as prerequisite to evaluation as given in figure 1. Fundamental identification could be operated by both direct and indirect implementations, though direct implementation usually seems to be a prior alternative.The recommendation of direct implementation is the framework of Zhaoet al.(2008) plus the size decrease of desertification areas (Table 2), of course, detailed indicators should be modified according to natural and economic conditions. The indirect identification is an alternative and still applicable when direct identify is unavailable.

Logically, if identification is completed, then comprehensive evaluation should follow. Recent studies rarely focus specifically on desertification and its rehabilitation. But its attribute of ecological product/service as others provides a theoretical rationale to take modes focused on other ecological issues into this account. Actually, these modes are indeed widely adopted in evaluation of ecological issues including land degradation.

Available studies have provided numerous models(see table 3), however, they all failed to clarify ecological issues due to theoretical deficiencies. With regard to desertification rehabilitation, the defensive expenditure model and others like WTP/WTA could be supplementary assessment of effective reference but not the dominated model. Because there is hiatus for them to incorporate economic segment and ecological segment together, except for their innate theoretical deficiencies. The accepted framework should be based on Ostrom (2009). Although theoretical, this framework takes into consideration sustainable development, cost and benefits, public interest and individual behavior. As outlined in figure 2, this framework also conceptually mingles economic and ecological segments into one theoretical framework. Of course, the same challenge of this model is practical rectification and mathematics. Additionally, no matter how elaborate the model, the failure of dynamic interpretation is the apparent gap of both identification and evaluation. Thus, it is imperative that future interpretation models should be taken into consideration of the dynamics of desertification.

This paper was financially supported by the 100 Talents Program of the Chinese Academy of Sciences, the Key Project of the Chinese Academy of Sciences (No.KZZD-EW-04-05), the National Natural Science Foundation of China (40971278), and the 2010 "Western Light" Project of the Chinese Academy of Sciences.

Abdelgalil A, Cohen I, 2007. Economic development and resource degradation, conflicts and policies. Socio-Economic Planning Sciences, 41: 107–129.

Abuduwaili J, Liu D, Wu G, 2010. Saline dust storms and their ecological impacts in arid regions. Journal of Arid Land, 2(2):144–150.

Berry L, Ford B, 1977. Recommendations for a System to Monitor Critical Indicators in Areas Prone to Desertification. Clark University, Massachusetts.

Bingham G, Bishop R, Brody M,et al., 1995. Issues in ecosystem valuation, improving information for decision making. Ecological Economics, 14: 73–90.

Castellano J, Valone J, 2007. Livestock, soil compaction and water infiltration rate, evaluating a potential desertification recovery mechanism. Journal of Arid Environments, 71: 97–108.

Chen GQ, Jiang MM, Yang ZF,et al., 2009. Exergetic assessment for ecological economic system, Chinese agriculture. Ecological Modeling, 220: 397–410.

Chen GT, Dong ZB, Yan P, 1996. Desertification, international research topics and research strategies of China. Exploration of Nature, 15: 1–5.

Chen YP, Li YQ, Awada T,et al., 2012. Carbon sequestration in the total and light fraction soil organic matter along a chronosequence in grazing exclosures in a semiarid degraded sandy site in China. Journal of Arid Land, 4(4): 411-419. DOI:10.3724/SP.J.1227.2012.00411.

Common M, Perrings C, 1992. Towards an ecological economics of sustainability. Journal of Ecological Economics, 6: 7–34.

Costanza R, D’Arge R, de Groot R,et al., 1997. The value of the world’s ecosystem services and natural capital. Nature, 387:253–260.

Daily C, Soderquist T, Aniyar S,et al., 2000. The value of nature and the nature of value. Science, 289: 395–396.

Daily G, 1995. Restoring value to the world’s degraded lands.Science New Series, 269(5222): 350–354.

De Groot R, Wilson M, Boumans R, 2002. A typology for the classification, description and valuation of ecosystem functions,goods and services. Ecological Economics, 41: 393–408.

Dong YX, 1997. Preliminary study on evaluation of the economic loss of sandy desertification––A case study in Tibet. Journal of Desert Research, 17(4): 383–388.

Farber S, Costanza R, Wilson M, 2002. Economic and ecological concepts for valuing ecosystem services. Ecological Economics, 41: 375–392.

Fuhlendorf D, Briske D, Smeins E, 2001. Herbaceous vegetation change in variable rangeland environments, the relative contribution of grazing and climatic variability. Applied Vegetation Science, 4: 177–188.

Gao J, Zha Y, Ni S, 2001. Assessment of the effectiveness of desertification rehabilitation identifys in Yulin, north-western China using remote sensing. International Journal of Remote Sensing, 22(18): 3783–3795.

Georgescu-Roegen N, 1975. Energy and economic myths. Southern Economic Journal, 41: 347–381.

Guo HC, Wu DR, Zhu HX, 1989. Land restoration in China. Journal of Applied Ecology, 26: 787–792. DOI: 10.1007/BF02664542.

Hardin G, 1968. The tragedy of the commons. Science, 162:1243–1248.

Heal M, 2000. Valuing ecosystem services. Ecosystems, 3: 24–30.

Helldén U, 2008. A coupled human–environment model for desertification simulation and impact studies. Global and Planetary Change, 64: 158–168.

Helliwell R, 1969. Valuation of wildlife resources. Regional Studies, 3: 41–49.

Huang YZ, Wang NA, Cheng HL,et al., 2013. Historical desertification of the Mu Us Sandy Land: A perspective from the Beidachi section. Sciences in Cold and Arid Regions, 5(3):293–300.

Hueting R, 1970. Moet de natuur worden gekwantificeerd? Should Nature be Quantified. Economica Statistische Berichten,55(2730): 80–84.

Jia KL, Chang QR, Zhang JH, 2009. Spatial-temporal change characteristics of sandy desertification lands in agro-pasture interlacing zone in northern Shaanxi. Journal of Desert Research, 29(2): 223–228.

Jogo W, Hassan R, 2010. Balancing the use of wetlands for economic well-being and ecological security, the case of the Limpopo wetland in southern Africa. Ecological Economics, 69:1569–1579.

Kramer R, Richter D, Pattanayak S,et al., 1997. Ecological and economic analysis of watershed protection in Eastern Madagascar. Journal of Environmental Management, 49: 277–295.

Ladisa G, Todorovic M, Trisorio G, 2011. A GIS-based approach for Desertification Risk Assessment in Apulia region, SE Italy.Physics and Chemistry of the Earth. DOI: 10.1016/j.pce.2011.05.007.

Li AM, Han ZW, Huang CH,et al., 2008. Remote sensing monitoring on dynamic of sandy desertification degree in Horqin Sandy Land at the beginning of 21st Century. Journal of Desert Research, 28(1): 8–15.

Li ZS, Bao HJ, Wang T, 2006a. Assessment of sustainable development in desertified area: I. Indicators. Journal of Desert Research, 26(3): 432–439.

Li ZS, Bao HJ, Wang T, 2006b. Assessment of sustainable development in desertified area: II. Case study. Journal of Desert Research, 26(3): 440–446.

Liu T, 2006. Desertification economic loss assessment in China.Journal of Desert Research, 26(1): 40–46.

Ma YH, Zhou LH, Fan SY,et al., 2006. Rehabilitation of land desertification in China and the strategic shift of ecological control policies. China Soft Science, 6: 53–59.

Mabbutt A, 1986. Desertification indicators. Climatic Change, 9:113–122.

Millennium Ecosystem Assessment, 2005. Ecosystem and Human Well-being, Desertification Synthesis. World Resource Institute, Washington D.C..

Mohammad R, 2012. The effect of water spreading system on the functionality of rangeland ecosystems. Journal of Arid Land,4(3): 292–299.

Ostrom E, 2009. A general framework for analyzing sustainability of social-ecological systems. Science, 325: 419.

Patterson M, 2002. Ecological production-based pricing of biosphere processes. Journal of Ecological Economics, 41: 457–478.

Rasmussen K, Fog B, Madsen E, 2001. Desertification in reverse?Observations from northern Burkina Faso. Global Environmental Change, 11: 271–282.

Reining P, 1978. Handbook on Desertification Indicators. American Association for the Advancement of Science, Washington D.C..

Rubio L, Bochet E, 1998. Desertification indicators as diagnosis criteria for desertification risk assessment in Europe. Journal of Arid Environments, 39: 113–120.

Salvati L, Zitti M, 2009. Assessing the impact of ecological and economic factors on land degradation vulnerability through multi-way analysis. Ecological Indicators, 9: 357–363.

Salvati L, Zitti T, Ceccarelli T, 2008. Integrating economic and environmental indicators in the assessment of desertification risk, a case study. Applied Ecological and Environmental Research, 6(1): 129–138.

Sepehr A, Hassanli M, Ekhtesasi R,et al., 2007. Quantitative assessment of desertification in south of Iran using MEDALUS method. Environmental Monitoring and Assessment, 134:243–254.

Sinden A, 1994. A review of environmental valuation in Australia.Review of Marketing and Agricultural Economics, 62:337–368.

Sinden A, Griffith G, 2007. Combining economic and ecological arguments to value the environmental gains from control of 35 weeds in Australia. Ecological Economics, 61(2–3): 396–408.

Straton A, 2006. A complex systems approach to the value of ecological resources. Ecological Economics, 56: 402–411.

Su YZ, Zhao WZ, Su PX, 2007. Ecological effects of desertification control and desertified land reclamation in an oasis–desert ecotone in an arid region, A case study in Hexi Corridor,northwest China. Ecological Engineering, 29: 117–124. DOI:10.1016/j.ecoleng.2005.10.015.

Sun DF, Dawson R, Li BQ, 2006. Agricultural causes of desertification risk in Minqin, China. Journal of Environmental Management, 79(4): 348–356.

Valone J, Meyer M, Brown H,et al., 2002. Timescale of perennial grass recovery in desertified arid grasslands following livestock removal. Conservation Biology, 16: 995–1002.

Volk M, Hirschfeld J, Dehnhardt A,et al., 2008. Integrated ecological-economic modelling of water pollution abatement management options in the Upper Ems River Basin. Ecological Economics, 66: 66–76.

Wang T, 2008. Desertification process and reversion during last 5 decades in northern China. Essays of First Annual China Sand Industry Forum. China Forestry Publishing House, Beijing.

Wang T, Wu W, Xue X,et al., 2003. Time–space evolution of desertification land in northern China. Journal of Desert Research,23: 230–235. DOI: 10.3321/j.issn:1000-694X.2003.03.004.

Wang T, Wu W, Xue X,et al., 2004a. Spatial-temporal changes of sandy desertified land during last 5 decades in northern China.Acta Geographica Sinica, 59(2): 203–212.

Wang T, Wu W, Zhao HL, 2004b. Analyses on driving factors to sandy desertification process in Horqin Region, China. Journal of Desert Research, 24: 519–528. DOI: 10.3321/j.issn:1000-69 4X.2004.05.001.

Wang T, Xue X, Luo YQ,et al., 2008. Human causes of aeolian desertification in northern China. Sciences in Cold and Arid Regions, 12: 1–13.

Wang XM, Chen FH, Dong ZB, 2006. The relative role of climatic and human factors in desertification in semiarid China. Global Environmental Change, 16: 48–57.

Wang XM, Chen FH, Hasi E,et al., 2008a. Desertification in China, An assessment. Earth-Science Reviews, 88(3–4):188–206.

Xu D, Kang X, Liu Z,et al., 2009. The research of relative role of climate change and human activities in desertification process in Ordos Plateau, China. Science China, 39(4): 516–528. DOI:10.1007/s11430-009-0079-y.

Xu DY, Kang XW, Zhuang DF,et al., 2010. Multi-scale quantitative assessment of the relative roles of climate change and human activities in desertification— A case study of the Ordos Plateau, China. Journal of Arid Environments, 74(4): 498–507.

Xu LH, Wang JH, Li Y,et al., 2008. Variations of soil physical properties in desertification rehabilitation process at south edge of Tengger Desert. Journal of Desert Research, 28(4):690–695.

Xu ZM, Cheng GD, Zhang ZQ,et al., 2003. Applying contingent valuation in China to identify the total economic value of restoring ecosystem services in Ejina region. Ecological Economics, 44(23): 345–358.

Yang X, Zhang K, Jia B,et al., 2005. Desertification assessment in China, An overview. Journal of Arid Environments, 63(2):517–531.

Zha Y, Gao J, 1997. Characteristics of desertification and its rehabilitation in China. Journal of Arid Environments, 37(3):419–432.

Zhang JP, Chang XL, Cai MY,et al., 2009. Effects of land use on desertification in typical regions in the Horqin Sandy Land.Arid Zone Research, 26(1): 39–44. DOI:10.3724/SP.J.1148.2009.00039.

Zhang XJ, Zhou LH, Chen Y, 2013. Non-market evaluation of Eco-economic benefit of desertification reversion: a case study of Yanchi County in Ningxia, China. Journal of Desert Research, 33(1): 271–280. DOI: 10.7522/j.issn.1000-694X.2013.00037.

Zhao HL, Zhao RL, Zhao XY,et al., 2008. Ground discriminance on positive and negative processes of land desertification in Horqin Sand Land. Journal of Desert Research, 28(1): 8–15.

Zhao XY, Zuo XA, Huang G,et al., 2010. Desertification reversion in relation to land use change and climate in Naiman County, Inner-Mongolia, China. Sciences in Cold and Arid Regions, 2(1): 15–20.

Zhou W, Sun ZG, Li JL,et al., 2013. Desertification dynamic and the relative roles of climate change and human activities in desertification in the Heihe River Basin based on NPP. Journal of Arid Land, 5(4): 465-479. DOI: 10.1007/s40333-013-0181-z.

Zhu Z, Wu Z, Liu S,et al., 1980. An Introduction to Chinese Desert. Science Press, Beijing.

Zhu ZD, Liu S, Xiao LS, 1981. The characteristics of the environment vulnerable to desertification and the ways of its control in steppe zone. Journal of Desert Research, 1: 2–12.