Assessment of ecosystem services and dis-services of an agro-ecosystem based on extended emergy framework: A case study of Luancheng county, North China

Ecological Engineering 82 (2015) 241–251

Contents lists available at ScienceDirect

Ecological Engineering journal homepage: www.elsevier.com/locate/ecoleng

Assessment of ecosystem services and dis-services of an agro-ecosystem based on extended emergy framework: A case study of Luancheng county, North China Fengjiao Ma a,b , A.Egrinya Eneji c, Jintong Liu a, * a Key Laboratory of Agricultural Water Resources, Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang, Hebei 050022, China b University of Chinese Academy of Sciences, Beijing 100049, China c Department of Soil Science, Faculty of Agriculture, University of Calabar, Calabar, Nigeria

A R T I C L E I N F O

A B S T R A C T

Article history: Received 8 October 2014 Received in revised form 3 April 2015 Accepted 28 April 2015 Available online xxx

An agricultural ecosystem provides provisioning, regulating and supporting services for humans. At the same time, it consumes the resources of other ecosystems, including the investment of economic resources and can generate useless or harmful services, collectively called dis-services. Here, we built a framework for assessing agricultural ecosystem services and dis-services based on emergy analysis of Luancheng County, China. We analysed the inputs and outputs of the agricultural ecosystem from the three aspects of consumption of resources, ecosystem services and ecosystem dis-services and explored the variations in inputs and outputs from 1984 to 2008. We then proposed composite indexes for measuring the sustainable development of the agro-ecosystem. Our analysis showed that the agricultural ecosystem consumed a lot of resources, especially the nonrenewable ones; provisioning services were the largest services and provisioning dis-services were the largest dis-services. Both provisioning services and dis-services increased yearly as purchased nonrenewable inputs increased. The overall evaluation of the Luancheng agricultural ecosystem showed it to be a serious consumer system and thus not developing sustainably. The farming community should take steps, such as controlling excess inorganic fertilizer input, increasing organic fertilizer use and improving water and fertilizer use efficiency to ensure sustainability. ã 2015 Elsevier B.V. All rights reserved.

Keywords: Emergy analysis framework Resource consumption Agro-ecosystem services Sustainable development Luancheng County China

1. Introduction Ecosystem services, defined as the benefits human beings derive from the ecosystem, has become the focus of ecosystem research in recent years (Brander et al., 2013; Daily and Matson, 2008; Kinzig et al., 2011; Rey Benayas et al., 2009; Schröter et al., 2005; Tallis et al., 2008). Ecosystem services have been authoritatively classified into provisioning services, regulating services, supporting services and cultural services (Lü et al., 2012; Millennium Ecosystem Assessment, 2005). However, considering the relationship between ecosystems and human beings, this classification framework ignored the negative impact of the ecosystem, especially the agro-ecosystem, which accounts for one-third of the land area (FAOSTAT, 1999). While an agroecosystem provides important provisioning services, it also creates

* Corresponding author: Tel.: +86 311 85871749; fax: +86 311 85871749. E-mail address: [email protected] (J. Liu). http://dx.doi.org/10.1016/j.ecoleng.2015.04.100 0925-8574/ ã 2015 Elsevier B.V. All rights reserved.

dis-services and consumes resources from other systems. The consumption of water, emissions of greenhouse gases and discharging of underutilized fertilizer adversely affect human beings. Ecosystem dis-services are relatively new concepts with no consensus on their definition. They could represent reduced productivity or increased production costs or can be considered as ecosystem functions disturbed or damaged by human activities or even unwanted effects (Lyytimäki et al., 2008; Swinton et al., 2007; Zhang et al., 2007). In this study, we classify the adverse outputs contrasting with benefits or ecosystem services as the ecosystem dis-services. Monetary valuation methods (like market prices method for direct valuations and contingent valuation method, travel cost method for indirect valuations) have been used widely to estimate the value of ecosystem services because they assign the different services a uniform value to allow for direct comparison (Egoh et al., 2008; Jenkins et al., 2010; Naidoo and Ricketts, 2006; Olschewski et al., 2010; Yang et al., 2008). In addition, costing or pricing could make decision-makers more profoundly intuitive in their

242

F. Ma et al. / Ecological Engineering 82 (2015) 241–251

understanding of ecosystem benefits to humans. However, monetary methods have some limitations because: (1) product pricing is mainly based on human labor or investment, ignoring or underestimating natural inputs. For example, water resources, including the underground water used for irrigation is free; farmers merely pay for the irrigation equipment and electricity cost; (2) traditional economic value is affected by market, such as the relationship between supply and demand. This has resulted to different prices for the same products in different years; (3) the willingness-to-pay and contingent evaluation methods often used for the services without market prices rely on human preferences while capturing the value of ecosystem entities only narrowly and anthropocentrically (Rugani and Benetto, 2012; Rugani et al., 2013). As a result, the value of ecosystem services is usually not objective. Emergy analysis is an ecological valuation method based on thermodynamic principles, which translates different inputs and outputs of an ecosystem into the same solar emjoule (sej) unit using solar energy as the base energy (Herendeen, 2004; Lan et al., 2002; Odum, 1996). According to the emergy theory, value does not rely on human preferences and willingness to pay, but instead it stems from the work of the biosphere to develop and stabilize an ecosystem structure, growth, organization and diversity (Dong et al., 2012). The emergy theory estimates the ecocentric value rather than the humancentric value (Rugani et al., 2013). It could quantify some ecosystem services that are difficult to evaluate otherwise but its limitations have also been highlighted (Cleveland et al., 2000; Ingwersen, 2010). The widespread use of GIS (Geographic Information System) and geospatial data has emerged as an important support in planning and environmental decisionmaking processes (Mellino and Ulgiati, 2014). Since natural resources are not uniformly distributed across the landscape, it was suggested that an emergy-GIS approach may also be useful for making decisions on how the limited resources can be used and managed sustainably within an existing area (Mellino et al., 2014). It is important to try to understand many different ecosystem theories in relation to each other and examine if they are contradictory or form a pattern that can be used to give a better understanding of the nature of ecosystems (Jørgensen et al., 2007). Jørgensen and Nielsen (2012) stated that a complete diagnosis focusing on the ecosystem services could be developed by the use of complementary indicators such as emergy and eco-exergy. Pulselli et al. (2011) considered ecosystem services as a counterpart of emergy flows to the ecosystem. Although several related studies have tried to link the ecosystem services to emergy analysis (e.g., Campbell and Tilley, 2014a,b; Coscieme et al., 2014; Dong et al., 2012; Pulselli et al., 2011; Vassallo et al., 2013; Watanabe and

Ortega, 2014), there are few reports on ecosystem dis-services. Ecosystem services research started in 1997 and has developed considerably since 2005 (Ma et al., 2013), while ‘ecosystem disservices’ within the scope of ecosystem services received some attention only ten years later in 2007 (Zhang et al., 2007). Evaluations of ecosystem dis-services have increased recently, using mainly a monetary valuation method which is the same as ecosystem services evaluation (Chang et al., 2011; Yuan et al., 2011). Thus, development of a new ecosystem services valuation framework based on emergy analysis, but including both the positive and negative ecosystem function is necessary. In this study, we aimed to develop a comprehensive evaluation framework that considers ecosystem services and dis-services, based on emergy analysis. We analysed the structure of inputs and outputs in a typical agro-ecosystem and explored the variations in structural components and ecosystem services sustainability indexes from 1984 to 2008. 2. Materials and methods 2.1. Study area The study area was located in Luancheng County (114
410 E, 37
530 N), a typical high production agro-ecosystem in North China (Fig. 1). The area is characterized by warm temperate continental monsoon climate with an annual mean temperature of 12.7
C with the highest temperature (26.4
C) in July and lowest (3.9
C) in January, a mean solar radiation value of 724 kJ/(cm2 a) and annual sunshine of 2521.8 h. Annual precipitation is about 536 mm, twothirds of which is concentrated in summer. The geomorphology is piedmont alluvial plain and topography is flat with meadow cinnamon soil type. The groundwater resource is abundant with salinity of 0.5–1.0 g/L and water table is shallow. However, the water table has continued to decline in successive years due to severe overexploitation for irrigation. The contradiction between water scarcity and irrigation of the agro-ecosystem has increasingly intensified in this region. 2.2. Methods 2.2.1. Conceptual framework for evaluating ecosystem services Ecosystem services have become the focus of ecosystem evaluation and any ecosystem can be evaluated, including the agricultural ecosystem. The Millennium Ecosystem Assessment (MA) defined the ecosystem services as the benefits people obtain from the ecosystem and provided an evaluation framework which divided ecosystem services into provisioning services, regulating

Fig. 1. Map of China showing the location of Luancheng County.

F. Ma et al. / Ecological Engineering 82 (2015) 241–251

services, supporting services and cultural services. The framework has been widely used for evaluating ecosystem services (Millennium Ecosystem Assessment, 2005; Carpenter et al., 2009). For this study, we adopted this definition and classification framework, ignoring the cultural services since the agro-ecosystem provides almost no cultural services. However, this conceptual framework mainly assesses the economic value and ignores ecosystem disservices, although some studies on ecosystem dis-services have been defined and evaluated using economic evaluation method in agricultural and urban ecosystems (Escobedo et al., 2011; Limburg et al., 2010; Pataki et al., 2011). Here we defined ecosystem disservices as adverse effects on human beings and other ecosystems. We extended the MA framework to include ecosystem dis-services and consumption resources (Fig. 2). The valuation object was an agro-ecosystem, whose boundary was defined to include two subsystems: crops and topsoil (0–20 cm deep). Our framework divided all the resources consumed by the agro-ecosystem into three systems: natural renewable resources system, other ecosystems and human economic system. The natural system represented the provision of renewable resources from sun, atmosphere and interior of the earth. For an agro-ecosystem, other systems mainly referred to groundwater system (the water table was deeper than 15 m) used for irrigation while the human economic system included the inputs of manpower, machinery, fossil fuel, etc. The outputs of our conceptual framework included the ecosystem provisioning services and dis-services as well as regulating services and dis-services. Provisioning services included different kinds of crop products, while provisioning dis-services were the underutilized fertilizer and pesticides. Regulating services included the release of O2, purifying the atmosphere and fixing CO2, considering the peculiarities of the agro-ecosystem under study and previous reports (Chang et al., 2011; Chang et al., 2011). Another regulating service was absorption of CH4, because the dry farmland could absorb CH4 from the surrounding atmosphere (Zhang, 2003) and our study location was in a relatively dry land. Regulating dis-services were emissions of greenhouse gases (Burgin et al., 2013). Supporting services and

243

supporting dis-services were the intrinsic services of the agroecosystem as represented by maintenance and leaching of nutrients from the soil. 2.2.2. Data collection Long-term (1984–2008) annual mean climatic data for solar radiation and rainfall were taken from the National Ecosystem Research Network of China and Luancheng County weather station. Socio-economic data were obtained from statistical yearbooks of the local government. Soil data were taken from the National Ecosystem Research Network of China, the second national soil survey data and relevant literatures (see Table 1). Other parameters, like products economic coefficient, price value of O2 release, CO2 fixation, etc. were obtained from the literature (Table 1). 2.2.3. Calculation of emergy This was done by transforming the different inputs and outputs into energy or mass data (see supplementary Tables 1–4) and then multiplying by the appropriate transformities (cited from the literatures (Table 1) or calculated from our data) to obtain the emergy (Table 1). The formulas for converting raw data are also shown in Table 1. 2.2.4. Emergy evaluation of agricultural ecosystem services sustainability Commonly-used emergy indexes do not include all the services, especially the regulating services and dis-services. This is understandable since most emergy indexes have been developed to capture the use and effects of natural and purchased resources in obtaining economic products and/or in providing support for society. The methodological problem faced in this study was to develop emergy indexes suitable for sustainable ecosystem services evaluation based on our conceptual framework. These indexes were divided into four aspects: input-output, input resources, output ecosystem services and emergy of sustainability (Table 2).

Fig. 2. Conceptual framework for evaluating farmland ecosystem based on the emergy flow.

244

F. Ma et al. / Ecological Engineering 82 (2015) 241–251

Table 1 Emergy transformity and emergy input and output in the agro-ecosystem The renewable emergy base for the earth is 9.26E + 24 semi/y. Items Natural renewable resources system

Unit Transformity (sej/unit) Renewable resources (R)

Solar radiation

b

J

10300

Rain (chemical)

J

18100c

J

c

Other systems

Nonrenewable resources (N) Underground water Human economics system Purchased renewable Seeds resources (FR) Human labor

33700

J

This study

J

78600d

J

7.79E + 04e a

g

2.60E + 06

Purchased nonrenewable resources (FN)

Inorganic fertilizer Pesticide Mulch Machine and tools Fossil fuel

g g g J J

2.80E + 09d 2.49E + 10d 3.65E + 08a 7.50E + 07f 1.70E + 05c

Provisioning services (PS)

Wheat

J

6.54E + 04a

Corn Oilseeds

J J

8.19E + 04d 8.27E + 04a

Cotton

J

8.27E + 05a

Supporting services (SS)

Provisioning dis-services (PDS)

Regulating dis-services (RDS)

Supporting dis-services (SDS)

g

O2 release

g

9.26E + 06

SO2 absorption

g

5.26E + 10h a

CO2 fixation

J

6.01E + 04

CH4 absorption

g

2.14E + 10i

Nitrogen

g

4.42E + 09e

Phosphorus

g

1.71E + 10e

Potassium

g

1.67E + 09e

Loss of inorganic fertilizer Loss of pesticides

g

2.80E + 09d

g

2.49E + 09d

CO2 release

g

2.35E + 07i

g

j

N2O release Loss of soil

6.62E + 10

This study

Sources of raw data

Solar radiation = arable area (e)  solar radiation intensity (e) Rain geopotential = arable area (e)  elevation (e)  average rainfall(e)  density  gravitational acceleration Rain chemical energy = arable area (e)  average rainfall (e)  Gibbs energy  density Earth cycle = arable area (e)  average geothermal (a)

e

(1)

Organic fertilizer

Regulating services (RS)

Ecosystem dis-services

1a

Rain (geopotential)

Earth cycle

Ecosystem services

J

Formulation of raw data

e

e ae e

Seed = the amount of seed per unit area (f)  arable area(e) Human labor = the amount of human labor per unit area (f)  arable area (e) Organic fertilizer = the mass of Organic fertilizer per unit area (f)  arable area (e) Raw data (h) Raw data (h) Raw data (h) Raw data (h) Raw data (h) Wheat energy = wheat yield (h)  wheat calorific value (g) Corn energy = corn yield (h)  corn calorific value (g) Oilseeds energy = oilseeds yield (h)  oilseeds calorific value (g) Cotton energy = cotton yield (h)  cotton calorific value (g) NPP = produce yield (h)  [1-moisture content of each products (i)]/each products economic coefficient (i)O2 Release = NPP  (32/30) SO2 Absorption = arable area (e)  capacity of absorption SO2 (j) Energy of CO2 fixation=accumulation of organic matter in soil (eklmn)calorific value of organic matter (g) Absorption CH4 = arable area(e)  capacity of absorption CH4 (o) Nitrogen = arable area (e)  topsoil thickness  density  percentage content of nitrogen (eklmn) Phosphorus = arable area (e)  topsoil thickness  density  percentage content of Phosphorus (ekl) Potassium = arable area (e)  topsoil thickness  density  percentage content of Potassium (ekl) Loss of inorganic fertilizer mass = mass of inorganic fertilizer (h)  inorganic fertilizer loss rate (p) Loss of pesticide mass = mass of pesticide (h)  pesticide loss rate (q) Release CO2 = arable area (e)  amount of release CO2 (o) Release N2O = arable area (e)  amount of release N2O (o)

ef ef ef h h h h h gh gh gh gh hi

ej egklmn

o eklmn

ekl

ekln

hp hq eo eo

(2)

Note: (1) Emergy of groundwater = energy of groundwater  transformity of groundwater; the amount of irrigation water was calculated by using Yuan’s approach (Yuan and Shen, 2013), this method using meteorological data and crop yield. Transformity of groundwater = energy of groundwater  transformity of rainfall  update time (Lan et al., 2002); the relationship between groundwater update time (Y) and groundwater table (m) was Y = 0.13x + 6.73 in North China Plain according to Wei (2007). (2) Emergy of topsoil loss = loss of topsoil organic matter  transformity of organic matter + loss of topsoil nitrogen  transformity of nitrogen + loss of topsoil phosphorus  transformity of phosphorus + loss of topsoil potassium  transformity of potassium (3) References of transformity: a Odum (1996); bLu et al. (2007); cLi et al. (2011);dHu et al. (2010); eLiu et al. (2009); fDu (2008); gTonon and Mirandola (2003); hCampbell and Tilley (2014b); iCampbell et al. (2014); jWatanabe and Ortega (2011). And transformity from a and e were converted to 9.26 baseline from 9.44 E + 24 sej/yr. The convert method referred to Lu and Campbell (2009a) (4) References of raw data: e Hu and Cheng, 2011; fChen et al. (2008); gLuo (2001); hHebei Bureau of Statistics, 1984–2008; iChinese, (2006); jTang et al.(2008); kDing (1992); l Zeng et al.(1996); mZhang and Yuan, 1995; nZhang (1997); oZhang (2003); pZhang et al.(2006); qLiu (2004). (5) The corresponding sources are showed in () beside the topic in formulations. We assumed SO2 and CH4 absorption as well as CO2 and N2O release to be constant based on experience. Raw data could be obtained from relevant references. Raw data for other indicate those that could be collected almost yearly from yearbooks, National Ecosystem Research Network of China and references shown in note (4).

F. Ma et al. / Ecological Engineering 82 (2015) 241–251

245

Table 2 Existing and revised emergy indexes used in this study. Items

Indexes

Formulation

Input-output index

Economic emergy provisioning services yield ratio (EYR)a Economic emergy ecosystem services yield ratio (EESR) Economic emergy net ecosystem services yield ratio (nEESR) Natural emergy ecosystem services yield ratio (NESR) Natural emergy net ecosystem services yield ratio (nNESR) Other emergy ecosystem services yield ratio (OESR) Other emergy net ecosystem services yield ratio (nOESR)

PS/(FR + FN) ES/ (FR + FN) nES/ (FR + FN) ES/R nES/R ES/N nES/N

Input resources index

Emergy investment ratio (EIR)b Environment loading ratio (ELR)b Emergy self-sufficiency ratio (ESR)b Natural emergy self-sufficiency ratio (N-ESR)

(FR + FN)/(R + N) (N + FN)/(R + FR) (R + N)/(FR + FN) R/(FR + FN)

Output ecosystem services index

Ecosystem services and ecosystem dis-services ratio (EDR)

ES/EDS

Sustainability index

Emergy sustainability index (ESI)b Ecosystem services emergy sustainability index (ESSI) Net ecosystem services emergy sustainability index (nESSI)

EYR/ELR EESR/ELR nEESR/ELR

Note: References for the existing emergy indexes:

a

Lan et al. (2002);

b

Lu et al. (2009b).

(1) Input-output index The emergy yield ratio (EYR) is used widely in emergy analysis and represents the ability of the larger system/process to exploit local resources (Lu et al., 2009b, 2011). We built and introduced the economic system emergy ecosystem services yield ratio (EESR) considering that provision ecosystem is not the only output service in our classification framework. If we deduct the ecosystem disservices from the ecosystem services outputs, we would obtain the net economic system emergy ecosystem services (nEESR) which could more comprehensively reflect the economic output ability. Furthermore, the emergy yield ratio focused on the human economic system only. But the natural and other ecosystems also provide lots of emergy inputs to the agro-ecosystem. Thus, we developed four new indexes using natural and other systems’ inputs emergy, replacing human economic system inputs emergy. These were natural ecosystem services emergy yield ratio (NESR), net natural ecosystem services emergy yield ratio (nNESR), other ecosystem services emergy yield ratio (OESR) and other net ecosystem services emergy yield ratio (nOESR). (2) Input resources index The emergy investment ratio (EIR), environmental loading ratio (ELR) and emergy self-sufficiency ratio (ESR) retained the same meaning as previously defined (Dong et al., 2011; Lu et al., 2009b). Emergy investment ratio is the degree of utilization of environmental resources by the system and measures the economic development and environmental load. Environmental loading ratio is an indicator of potential pressure on the local ecosystem, or the ecosystem stress due to production activity. Emergy selfsufficiency ratio is an indicator of the fraction of emergy used from within the system. Actually, an agro-ecosystem has no input emergy investment and only the renewable resources inputs of the natural system could ostensibly belong to the agro-ecosystem based on our classification system. We defined the real emergy self-sufficiency as the natural emergy self-sufficiency ratio (N-ESR). (3) Output ecosystem services index The outputs emergy of an agro-ecosystem summarized as ecosystem services includes the beneficial ecosystem services and non-beneficial or even harmful ecosystem dis-services. The ecosystem services and dis-services ratio (EDR) represents the degree of optimization of the system output structure. We could clearly recognize the negative effects on the environment from the pursuit of beneficial services. (4) Emergy of sustainability

Emergy sustainability index (ESI) is a common indicator of system sustainability, the ratio of emergy yield ratio to environmental loading ratio (Lu et al., 2009b). We defined ecosystem services sustainability index (ESSI) as the ratio of the economic system emergy ecosystem services (EESR) to environmental loading ratio in order to indicate the sustainability based on ecosystem services rather than ecosystem provisioning services. Similarly, the net ecosystem services sustainability index (nESSI) was estimated from the ratio of net economic emergy ecosystem services (nEESR) to environmental loading ratio and indicated the sustainability based on both ecosystem services and dis-services. 3. Results and discussion 3.1. Structure of inputs and outputs in the agro-ecosystem of Luancheng County Based on the framework in Table 1, we summarized the structure of emergy inputs and outputs of a typical agricultural ecosystem in Luancheng County from 1984 to 2008 (Fig. 3). The average consumption emergy, i.e., the inputs to the agricultural ecosystem were 27.7  1019 sej and the highest inputs were purchased nonrenewable resources, being 20.7  1019 sej. The ecosystem services outputs were 51.7  1019 sej. The provisioning services were 34.5  1019 sej, being the largest outputs. The ecosystem dis-services outputs were 3.10  1019 sej, with provisioning dis-services and regulating dis-services (1.41 1019 sej) as the largest components. We compared our evaluation which was done based on emergy analysis with that based on economic methods. Food production is the core of the agricultural ecosystem as confirmed by both our evaluation and economic evaluation. Chang et al. (2011, 2013) assessed the economic value of vegetable cultivation in China using an evaluation system that differed from ours in several respects. Firstly, they merely considered the outputs, which included ecosystem services and dis-services, but not the inputs. Secondly, they considered water-saving irrigation as a regulating service. Actually, water for irrigation is one kind of resource consumption and water saving just enabled less consumption rather than additional services. This deficiency was also noticed in Yuan et al. (2011) and Zhang et al. (2007) although Zhang et al. (2007)’s conceptual framework was similar to ours. On the other hand, where the inputs and outputs analyses based on emergy were extensive (e.g., Li et al., 2011; Lu et al., 2009a,b), the output

246

F. Ma et al. / Ecological Engineering 82 (2015) 241–251

emergy was focused on provisioning services with little attention to other services (e.g., Liu et al., 2009). In general, the ecosystem dis-services were ignored. Our analysis showed that the agro-ecosystem provided large services for humans and provisioning services (34.5  1019 sej) were the most important outputs. The ecosystem dis-services provided by the agro-ecosystem accounted for a relatively small proportion of all the ecosystem services. The total consumption emergy was 27.7  1019 sej. Although we only considered the ecosystem services as outputs, consumption emergy also accounted for 54%. This shows that although the agro-ecosystem provided significant benefits, its large resource consumption (inputs) is also of concern. 3.2. Variation in inputs-outputs structure in the agro-ecosystem of Luancheng County from 1984 to 2008 3.2.1. Inputs of three systems to the agro-ecosystem of Luancheng County The agro-ecosystem received inputs from three different systems (Table 1). Inputs from the natural system were renewable resources while those from other ecosystems were mainly from the underground system. Because our study sites received insufficient rainfall and lacked surface water, farmers must lift the underground water to irrigate crops for high yield. However, the rate of extraction of groundwater was far greater than the rate of recharge, resulting in continued decline of groundwater with successive years. We considered groundwater as nonrenewable resource because of its storage due to continued decline. The resources from the human economic system were purchased resources, including renewable and nonrenewable ones. It can be seen from Fig. 4 that inputs from natural renewable resources were stable and relatively lower than those from other systems. The groundwater resource input fluctuated considerably

but with an upward trend. And the largest input system, the human economic system invested more and more purchased resources. The trends noticed here for the natural renewable resources system and other human economic systems were typical of Chinese agriculture (Chen et al., 2006). However, they differed from those of other countries, such as the Japanese agricultural system where the renewable resources declined and both the nonrenewable and purchased resources increased from 1975 to 2005 (Gasparatos, 2011). In San Luis Basin of the USA, the renewable resources varied and each component of the nonrenewable resources, including the purchased resources followed a characteristic change from 1980 to 2005 (Campbell and Garmestani, 2012). These differences in trends are ascribed to the stages of development, management practices and technical conditions of each country. The renewable resources supplied by natural system changed little within a short time but varied from year to year with the greatest variation between high and low year occurring for rainfall. Luancheng County has a temperate continental monsoon climate, where the amount and time of rainfall are determined by irregular movement of tropical pressure on the Pacific Ocean. The underground water, which is a nonrenewable resource, has a relatively high emergy. The amount of input is directly determined by rainfall since it is a supplement to water resources. The underground system need not supply any water in wet years like 1996 and 2003 but a large volume of irrigation water from underground was demanded in dry years. Unfortunately, the rainfall became less and less for a long time (IPCC, 2007), meaning that the input emergy of the underground system became more pronounced. The trend is in line with the regular pattern. The purchased nonrenewable resources supplied by the human economic system were the largest inputs, being nearly 10 times those of the natural renewable resources and more than 12 times the underground system in 1984. These proportions became

Fig. 3. Structure of the average emergy inputs and outputs of a typical agricultural ecosystem from 1984 to 2008 in Luancheng County, China. Renewable resources R; Nonrenewable resources N; Purchased renewable resources FR; Purchased nonrenewable resources FN; Provisioning services PS; Regulating services RS; Supporting services SS; Provisioning dis-services PDS; Regulating dis-services RDS; Supporting dis-services SDS. The inputs emergy were under the emergy consumption of the agricultural ecosystem and have negative benefits for humans. The ecosystem services which are of benefit to humans had positive values and the harmful parts had negative values.

F. Ma et al. / Ecological Engineering 82 (2015) 241–251

247

Fig. 4. Changes in the three input systems (natural, underground and human economic) from 1984 to 2008.

23 and 7 times respectively, twenty years later as the purchased nonrenewable resources input increased sharply. One reason for this phenomenon was that the development of technology, enhanced productivity and social progress encouraged farmers to devote more purchased nonrenewable resources to the agroecosystem. The other reason was that the falling water table made farmers expend more energy and machinery to extract the same amount of groundwater, not to mention the increasingly high demand for groundwater. 3.2.2. Output emergy of the agro-ecosystem services The variations in the three ecosystem services from 1984 to 2008 (Fig. 5) showed that the provisioning services increased slowly before 1990, then faster from 1990 to 1998, and was

relatively stable during the last ten years. The regulating services showed dramatic changes among years while the supporting services remained stable with lower values after 1998. Although research into ecosystem services valuation is widely done around the world, the intensity of using emergy analysis to evaluate ecosystem services is low. For example, Liu et al. (2009) explored the ecosystem services supplied by different conversion systems in Yancheng National Nature Reserve using emergy analysis but they did not factor in the time scale. Lin et al. (2013) and Huang et al. (2011) performed a long-term study of the agricultural and peri-urban ecosystem services based on emergy analysis. Lin et al. (2013) considered the food provisioning services, soil loss and surface runoff which is defined as regulating services loss in an agro-ecosystem. Based on available

Fig. 5. Variations in the output of three ecosystem services from 1984 to 2008.

248

F. Ma et al. / Ecological Engineering 82 (2015) 241–251

data and the raw data for supporting services in our study area, the possible ecosystem services could be obtained only from 1998 (Fig. 5). The regulating services loss in Lin et al. (2013)’s research was defined as supporting dis-services in our research. Because supporting services were defined as maintaining ecosystem services provision (Millennium Ecosystem Assessment, 2005), once soil loss occurs in the agro-ecosystem, other services would be affected negatively. The main agro-ecosystem services are provisioning services which have grown rapidly owing to continuous input of human economic system. But it could not maintain a linear growth since the natural renewable resources system is fixed and limited. The other important reason was that the arable land declined successively because recent economic development led to conversion of arable land to housing and other uses. Regulating services fluctuated considerably with no apparent increasing or decreasing trend, suggesting that their provision by the agro-ecosystem was relatively stable. The fluctuation was because the raw data were from field samples with relatively high variation. Thus, we suggest that regulating services were relatively stable (ignoring any random error). Supporting services are rather controversial among many scholars since some consider them as indirect services, thus including them under provisioning and regulating services (Fu et al., 2010). Our estimate of supporting services was quite low relative to other services and the data were incomplete (only from 1998) and not enough for deeper analysis. 3.2.3. Outputs emergy of the agro-ecosystem dis-services The values of provisioning and regulating dis-services were almost five times larger than those of supporting dis-services. The provisioning dis-services increased each year while the regulating dis-services remained stable with some decline in the last ten years (Fig. 6). The supporting dis-services were stable with the lowest value. Although recent evaluations of ecosystem dis-services have relied on economic method (Chang et al., 2011; Yuan et al., 2011), our research is the first attempt to evaluate agro-ecosystem

dis-services based on emergy analysis from a systems perspective and a long time scale. We calculated the leaching of inorganic fertilizer and pesticide, the release of greenhouse gases and soil loss. Then we classified them as provisioning dis-services, regulating dis-services and supporting dis-services, respectively. As shown in Fig. 6, the regulating dis-services declined in later years. Controlling greenhouse gas emissions has become a serious challenge to decision-makers under the global warming background. China is a major agricultural country and the agroecosystem is a huge source of greenhouse gases. Series of measures, such as recycling of crop residue and use of more organic fertilizer were adopted to reduce greenhouse gas emissions with obvious benefits in recent years. The provisioning dis-services increased rapidly from year to year. Because more and more agrochemicals were put into the farming system, their absolute loss to the environment also increased with successive years. The supporting dis-services were less important because of their low value and characteristics like supporting services and their stable trends conferred little attention on them. 3.3. Variations in comprehensive indexes of the agro-ecosystem We explored the variations in the indexes by dividing the study period into three stages: 1980s, 1990s and 2000s. The average value and variability of the indexes are shown in Table 3. 3.3.1. Input–output index As can be seen in Table 3, the EYR, EESR and nEESR declined sharply with time. The values of EESR were nearly twice those of EYR and those of nEESR were slightly less than those of EESR. The variation in EYR was consistent with that of EYR of Chinese agriculture with a lower absolute value and a faster decline rate (Chen et al., 2006). The EYR of agriculture in OECD countries was stable with a relatively low (1.73) value (Hoang and Alauddin, 2011). The observed values and trend of EESR informed us that the agro-ecosystem actually supplied more benefits than merely providing grains.

Fig. 6. Variations in three ecosystem dis-services output from 1984 to 2008.

F. Ma et al. / Ecological Engineering 82 (2015) 241–251

249

Table 3 Comparison of emergy indexes among different periods. Items

Indexes

1980s

1990s

2000s

1980s

1990s

Input-output index

Economic emergy provisioning services yield ratio (EYR)a Economic emergy ecosystem services yield ratio (EESR) Economic emergy net ecosystem services yield ratio (nEESR) Natural emergy ecosystem services yield ratio (NESR) Natural emergy net ecosystem services yield ratio (nNESR) Other emergy ecosystem services yield ratio (OESR) Other emergy net ecosystem services yield ratio (nOESR)

1.96 3.35 3.14 37.64 35.29 16.67 15.64

1.93 2.79 2.63 46.21 43.60 7.76 7.30

1.22 1.99 1.88 54.00 50.96 8.85 8.38

0.02 0.17 0.16 0.23 0.24 0.53 0.53

0.37 0.29 0.28 0.17 0.17 0.14 0.15

Input resources index

Emergy investment ratio (EIR)b Environment loading ratio (ELR) b Emergy self-sufficiency ratio (ESR) b Natural emergy self-sufficiency ratio (N-ESR)

6.25 12.59 0.16 0.08

4.17 22.25 0.24 0.05

6.20 32.65 0.18 0.03

0.33 0.77 0.48 0.30

0.49 0.47 0.26 0.42

Output ecosystem services index

Ecosystem services and ecosystem dis-services ratio (EDR)

15.97

17.16

17.90

0.07

0.04

0.16 0.27 0.26

0.11 0.16 0.15

0.04 0.06 0.06

0.27 0.42 0.42

0.66 0.60 0.59

Sustainability index

Average value

b

Emergy sustainability index (ESI) Ecosystem services emergy sustainability index (ESSI) Net ecosystem services emergy sustainability index (nESSI)

Variability

Note: References for the existing emergy indexes: Lan et al. (2002) a; Lu et al. (2009b) b.

For the natural and other systems—the underground system, the emergy yield ratios were much higher than the economic emergy yield ratio because their inputs emergy was much lower than the economic system inputs emergy. Both the NESR and nNESR increased rapidly as the natural renewable resources inputs remained stable but the ecosystem services outputs increased faster. The OESR and nOESR showed poorly defined trends, with both declining during the first ten years but increasing thereafter. This was due to the faster growth rate of underground water emergy relative to that of ecosystem services emergy. The value of groundwater emergy increased linearly with the reduction in groundwater table but the growth rate of ecosystem services emergy declined due to natural factors. However, this has increased recently, possibly because the amount of underground water use has reduced due to temporary increase in rainfall in recent years. The OESR and nOESR fluctuated similarly as the input of underground system emergy. 3.3.2. Input resources index The emergy investment ratio EIR decreased at first and then increased. Considering the stable natural renewable resources inputs, this trend was due to economic and underground system inputs. The speed of underground water consumption was initially more than the economic inputs and was exacerbated by changes in rainfall pattern well beyond that of economic investment. The same reason explained the changes in OESR and nOESR. Rapid economic development was another important reason. A similar trend was reported for Chinese agriculure (Chen et al., 2006), but the EIR was much lower than our estimate for Luancheng County. This suggests that the degree of utilization of environmental resources in the county was considerably more than in other areas in China. The environment loading ratio (ELR) showed a rising trend because there was no obvious growth in the natural renewable resources system while other nonrenewable inputs showed significant yearly growth. The value of the ELR was much larger than that reported for Chinese agriculture (Chen et al., 2006), thus the local natural environment is under tremendous pressure. The emergy self-sufficiency ratio ESR was less than the average for Chinese agriculture although it first increased and then declined in later years. However, the natural emergy selfsufficiency ratio (N-ESR), which only included the input emergy of the natural renewable resources system decreased year by year.

The real emergy self-sufficiency ratio was rather low and heavily dependent on other systems. 3.3.3. Output ecosystem services index The EDR grew steadily during the 25 years (1984–2008), suggesting that the increase in ecosystem services was faster than the ecosystem dis-services. The simple reason was that ecosystem services kept growing at an irregular speed while the ecosystem dis-services showed a decreasing trend in later years. However, the evaluation method for ecosystem dis-services was the essential reason. We defined the ecosystem dis-services as useless or harmful outcomes for humans. For example, leaching of inorganic fertilizer is useless for humans but harmful to other ecosystems, such as eutrophication of water bodies or pollution of underground water. The potential dis-service mentioned above might be much larger than the emergy value of leaching of inorganic fertilizer. 3.3.4. Emergy of sustainability As can be seen from Table 3, all the indexes of sustainability were in decline (Table 3). The relationship between ESI and sustainability of a system could be summarized as: 1 10 symbolizing economic underdevelopment and ESI < 1 indicating the system is based on consumption (Lan et al., 2002; Ulgiati and Brown, 1998). Data in Table 3 showed that the agro-ecosystem of Luancheng County was a consumer-based system and the consumption was growing. For comparison, the ESI of Chinese agriculture decreased from 1.32 in 1980 to 0.67 in 1997, that of Italy was 0.11 in 1989 and that of Switzerland was 0.28 in 1996 (Chen et al., 2006). Our ESI for Luancheng County was the lowest relative to the above values. Although we considered the ecosystem services, the ESSI was still far less than 1, not to mention the nESSI. 4. Conclusions and recommendations 4.1. Conclusions (1) The agro-ecosystem provides large services for humans, mainly

provisioning services, and some ecosystem dis-services. All the outputs in our study area were achieved at a tremendous cost of resource consumption, especially the purchased nonrenewable resources. Although the agro-ecosystem gave more benefits, its

250

F. Ma et al. / Ecological Engineering 82 (2015) 241–251

resource consumption and associated dis-services should not be overlooked. (2) Both provisioning services and dis-services increased with increases in purchased nonrenewable inputs in successive years and the progressive decline in the nonrenewable underground water has become a problem of great concern. (3) The emergy of sustainability indexes showed that the agroecosystem of Luancheng County relied on resource inputs and was not under sustainable development. The non-sustainability seemed to be worsening with time. Effective measures must be taken to change this status for the better.

4.2. Recommendations (1) To ensure the sustainability of the agro-ecosystem under study,

the farming community should avoid excessive use of inorganic fertilizer input, increase organic fertilizer use and improve water and fertilizer use efficiency. (2) Future research analyzing the agro-ecosystem services (and dis-services) will benefit from the combined tool of emergy analysis and life cycle assessment. Since natural resources are not uniformly distributed across the landscape, the combined use of emergy-GIS approach may also be useful for making decisions on how best to use and manage the limited resources in any given area sustainably.

Acknowledgment We thank the anonymous reviewers for their insight and critical review of the manuscript. The study was supported by the Project of “973” (2015CB452705). Prof. A. Egrinya Eneji thanks the CAS Senior Visiting Fellowship for the opportunity. We are grateful for the support of Dr. Lipu Han Dr. Huiyi Yu and Mr. Yueyan Liu. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j. ecoleng.2015.04.100. References Brander, L., Brouwer, R., Wagtendonk, A., 2013. Economic valuation of regulating services provided by wetlands in agricultural landscapes: a meta-analysis. Ecol. Eng. 56, 89–96. Burgin, A.J., Lazar, J.G., Groffman, P.M., Gold, A.J., Kellogg, D.Q., 2013. Balancing nitrogen retention ecosystem services and greenhouse gas disservices at the landscape scale. Ecol. Eng. 56, 26–35. Campbell, D.E., Garmestani, A.S., 2012. An energy systems view of sustainability: emergy evaluation of the San Luis Basin, Colorado. J. Environ. Manage. 95, 72– 97. Campbell, E.T., Tilley, D.R., 2014a. The eco-price: how environmental emergy equates to currency. Ecosyst. Services 7, 128–140. Campbell, E.T., Tilley, D.R., 2014b. Valuing ecosystem services from Maryland forests using environmental accounting. Ecosyst. Services 7, 141–151. Campbell, D.E., Lu, H., Lin, B.-L., 2014. Emergy evaluations of the global biogeochemical cycles of six biologically active elements and two compounds. Ecol. Mode 271, 32–51. Carpenter, S.R., Mooney, H.A., Agard, J., Capistrano, D., Defries, R.S., Diaz, S., Dietz, T., Duraiappah, A.K., Oteng-Yeboah, A., Pereira, H.M., Perrings, C., Reid, W.V., Sarukhan, J., Scholes, R.J., Whyte, A., 2009. Science for managing ecosystem services: beyond the millennium ecosystem assessment. Proc. Natl. Acad. Sci. U. S. A. 106, 1305–1312. Chang, J., Wu, X., Liu, A., Wang, Y., Xu, B., Yang, W., Meyerson, L.A., Gu, B., Peng, C., Ge, Y., 2011. Assessment of net ecosystem services of plastic greenhouse vegetable cultivation in China. Ecol. Econ. 70, 740–748. Chang, J., Wu, X., Wang, Y., Meyerson, L.A., Gu, B., Min, Y., Xue, H., Peng, C., Ge, Y., 2013. Does growing vegetables in plastic greenhouses enhance regional ecosystem services beyond the food supply? Front. Ecol. Environ. 11, 43–49.

Chen, G.Q., Jiang, M.M., Chen, B., Yang, Z.F., Lin, C., 2006. Emergy analysis of Chinese agriculture. Agric. Ecosyst. Environ. 115, 161–173. Chen, D.D., Gao W.S, Sui P., Wu, T.L., 2008. Dynamic analysis on energy efficiency of modern planting system and grain production—a case study of Luancheng, Hebei. Prog. Geog. 27, 99–104 (in Chinese). Chinese Agricultural Yearbook Editorial Board, 2006. China Agriculture Yearbook. Chinese Agriculture Press, Beijing (in Chinese). Cleveland, C.J., Kaufmann, R.K., Stern, D.I., 2000. Aggregation and the role of energy in the economy. Ecol. Econ. 32, 301–317. Coscieme, L., Pulselli, F.M., Marchettini, N., Sutton, P.C., Anderson, S., Sweeney, S., 2014. Emergy and ecosystem services: a national biogeographical assessment. Ecosyst. Services 7, 152–159. Daily, G.C., Matson, P.A., 2008. Ecosystem services: from theory to implementation. Proceedings of the National Academy of Sciences 105, 9455–9456. Ding, D.Z., 1992. Hebei Soil Types. Hebei Science and Technology Press, Shijiazhuang (in Chinese). Dong, X.B., Zhang, Y.F., Cui, W.J., Xun, B., Yu, B.H., Ulgiati, S., Zhang, X.S., 2011. Emergy-based adjustment of the agricultural structure in a low-carbon economy in Manas County of China. Energies 4, 1428–1442. Dong, X., Yang, W., Ulgiati, S., Yan, M., Zhang, X., 2012. The impact of human activities on natural capital and ecosystem services of natural pastures in North Xinjiang, China. Ecol. Modell. 225, 28–39. Du, F.Y., 2008. Emergy Analysis of Farmland system in Hebei Province. Dissertation for master degree of Agricultural University of Hebei (in Chinese). Egoh, B., Reyers, B., Rouget, M., Richardson, D.M., Le Maitre, D.C., van Jaarsveld, A.S., 2008. Mapping ecosystem services for planning and management. Agric. Ecosyst. Environ. 127, 135–140. Escobedo, F.J., Kroeger, T., Wagner, J.E., 2011. Urban forests and pollution mitigation: analyzing ecosystem services and disservices. Environ. Pollution 159, 2078– 2087. FAOSTAT, 1999. http://faostat.fao.org/?alias=faostat1999. Fu, B.-J., Su, C.-H., Wei, Y.-P., Willett, I.R., Lü, Y.-H., Liu, G.-H., 2010. Double counting in ecosystem services valuation: causes and countermeasures. Ecol. Res. 26, 1– 14. Gasparatos, A., 2011. Resource consumption in Japanese agriculture and its link to food security. Energ. Policy 39, 1101–1112. Hebei Bureau of Statistics, 1984. Hebei Rural Statistical Yearbook. China Statistics Press, Beijing (in Chinese). Herendeen, R.A., 2004. Energy analysis and emergy analysis- a comparison. Ecol. Model 178, 227–237. Hoang, V.N., Alauddin, M., 2011. Analysis of agricultural sustainability: a review of exergy methodologies and their application in OECD countries. Int. J. Energ. Res. 35, 459–476. Hu, C.S., Cheng, Y.S., 2011. Chinese Ecosystem Observation and Research Data Sets, Agro-ecosystem Volume, Hebei Luancheng Station. China Agriculture Press, Beijing (in Chinese). Hu, S., Mo, X., Lin, Z., Qiu, J., 2010. Emergy assessment of a wheat-maize rotation system with different water assignments in the north China plain. Environ. Manage. 46, 643–657. Huang, S.L., Chen, Y.H., Kuo, F.Y., Wang, S.H., 2011. Emergy-based evaluation of penurban ecosystem services. Ecol. Complex 8, 38–50. IPCC, 2007. Summary for policymakers. In: Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Avery, K.B., Tignor, M., Miller, H.L. (Eds.), Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom/New York, NY, USA, pp. 216–220. Ingwersen, W.W., 2010. Uncertainty characterization for emergy values. Ecol. Mode 221, 445–452. Jørgensen, S.E., Nielsen, S.N., 2012. Tool boxes for an integrated ecological and environmental management. Ecol. Indicators 20, 104–109. Jørgensen, S.E., Fath, B.D., Bastianoni, S., Marques, J.C., Mueller, F., Nielsen, S.N., Patten, B.C., Tiezzi, E., Ulanowicz, R.E., 2007. A New Ecology: Systems Perspective. Elsevier. Jenkins, W.A., Murray, B.C., Kramer, R.A., Faulkner, S.P., 2010. Valuing ecosystem services from wetlands restoration in the Mississippi Alluvial Valley. Ecol. Econ. 69, 1051–1061. Kinzig, A.P., Perrings, C., Chapin, F.S., Polasky, S., Smith, V.K., Tilman, D., Turner, B.L., 2011. Paying for ecosystem services-promise and peril. Science 334, 603–604. Lü, Y., Liu, S., Fu, B., 2012. Ecosystem services: from virtual reality to ground truth. Environ. Sci. Technol. 46, 2492–2493. Lan, S.F., Qin, P., Lu, H.F., 2002. Emergy Analysis of Ecological Economic Systems. Chemical Industrial Press, Beijing. Li, L.J., Lu, H.F., Ren, H., Kang, W.L., Chen, F.P., 2011. Emergy evaluations of three aquaculture systems on wetlands surrounding the Pearl River Estuary, China. Ecol. Indicators 11, 526–534. Limburg, K.E., Luzadis, V.A., Ramsey, M., Schulz, K.L., Mayer, C.M., 2010. The good, the bad, and the algae: perceiving ecosystem services and disservices generated by zebra and quagga mussels. J. Great Lakes Res. 36, 86–92. Lin, Y.C., Huang, S.L., Budd, W.W., 2013. Assessing the environmental impacts of high-altitude agriculture in Taiwan: a Driver-Pressure-State-Impact-Response (DPSIR) framework and spatial emergy synthesis. Ecol. Indicators 32, 42–50. Liu, J., Zhou, H., Qin, P., Zhou, J., Wang, G., 2009. Comparisons of ecosystem services among three conversion systems in Yancheng National Nature Reserve. Ecol. Eng. 35, 609–629.

F. Ma et al. / Ecological Engineering 82 (2015) 241–251 Liu, G.D., 2004. Methods and Applications to Evaluate the Environmental Impacts of Regional Agriculture–A Case Study on High-Yielding Count. Dissertation for doctoral degree of China Agricultural University, Huantai, North China (in Chinese). Lu, H.F., Campbell, D.E., 2009a. Ecological and economic dynamics of the Shunde agricultural system under China’s small city development strategy. J. Environ. Manage. 90, 2589–2600. Lu, H.F., Campbell, D., Chen, J., Qin, P., Ren, H., 2007. Conservation and economic viability of nature reserves: an emergy evaluation of the Yancheng Biosphere Reserve. Biol. Conserv. 139 (3–4), 415–438. Lu, H.-F., Kang, W.-L., Campbell, D.E., Ren, H., Tan, Y.-W., Feng, R.-X., Luo, J.-T., Chen, F.-P., 2009b. Emergy and economic evaluations of four fruit production systems on reclaimed wetlands surrounding the Pearl River Estuary. China. Ecol. Eng. 35, 1743–1757. Lu, H.F., Wang, Z.H., Campbell, D.E., Ren, H., Wang, J., 2011. Emergy and eco-exergy evaluation of four forest restoration modes in southeast China. Ecol. Eng. 37, 277–285. Luo, S.M., 2001. Agroecology. China Agriculture Press, Beijing (in Chinese). Lyytimäki, J., Petersen, L.K., Normander, B., Bezák, P., 2008. Nature as a nuisance? Ecosystem services and disservices to urban lifestyle. Environ. Sci. 5, 161–172. Ma, F.J., Liu, J.T., Eneji, A.E., 2013. A review of ecosystem services and research perspectives. Acta Ecol. Sin. 33, 5963–5972. Mellino, S., S., Ulgiati. 2014. Mapping the evolution of impervious surfaces to investigate landscape metabolism: An Emergy-GIS monitoring application. Ecological Informatics, In press. http://dx.doi.org/10.1016/j.ecoinf.2014.03.003. Mellino, S., Ripa, M., Zucaro, A., Ulgiati, S., 2014. An emergy–GIS approach to the evaluation of renewable resource flows: a case study of Campania Region. Italy Ecol. Model. 271, 103–112. Millennium Ecosystem Assessment, 2005. Ecosystems and Human Well-being. Island Press, Washington, D.C. Naidoo, R., Ricketts, T.H., 2006. Mapping the economic costs and benefits of conservation. Plops Biol. 4, e360. Odum, H.T., 1996. Environmental Accounting Emergy and Environmental Decision Making. Wiley, New York. Olschewski, R., Klein, A.M., Tscharntke, T., 2010. Economic trade-offs between carbon sequestration, timber production, and crop pollination in tropical forested landscapes. Ecol. Complex. 7, 314–319. Pataki, D.E., Carreiro, M.M., Cherrier, J., Grulke, N.E., Jennings, V., Pincetl, S., Pouyat, R.V., Whitlow, T.H., Zipperer, W.C., 2011. Coupling biogeochemical cycles in urban environments: ecosystem services green solutions, and misconceptions. Front. Ecol. Environ. 9, 27–36. Pulselli, F.M., Coscieme, L., Bastianoni, S., 2011. Ecosystem services as a counterpart of emergy flows to ecosystems. Ecol. Mode 222, 2924–2928. Rey Benayas, J.M., Newton, A.C., Diaz, A., Bullock, J.M., 2009. Enhancement of biodiversity and ecosystem services by ecological restoration: a meta-analysis. Science 325, 1121–1124. Rugani, B., Benetto, E., 2012. Improvements to emergy evaluations by using life cycle assessment. Environ. Sci. Technol. 46, 4701–4712. Rugani, B., Benetto, E., Arbault, D., Tiruta-Barna, L., 2013. Emergy-based mid-point valuation of ecosystem goods and services for life cycle impact assessment. Revue de Métallurgie 110, 249–264. Schroter, D., Cramer, W., Leemans, R., Prentice, I.C., Araujo, M.B., Arnell, N.W., Bondeau, A., Bugmann, H., Carter, T.R., Gracia, C.A., de la Vega-Leinert, A.C., Erhard, M., Ewert, F., Glendining, M., House, J.I., Kankaanpaa, S., Klein, R.J., Lavorel, S., Lindner, M., Metzger, M.J., Meyer, J., Mitchell, T.D., Reginster, I.,

251

Rounsevell, M., Sabate, S., Sitch, S., Smith, B., Smith, J., Smith, P., Sykes, M.T., Thonicke, K., Thuiller, W., Tuck, G., Zaehle, S., Zierl, B., 2005. Ecosystem service supply and vulnerability to global change in Europe. Science 310, 1333–1337. Swinton, S.M., Lupi, F., Robertson, G.P., Hamilton, S.K., 2007. Ecosystem services and agriculture: cultivating agricultural ecosystems for diverse benefits. Ecol. Econ. 64, 245–252. Tallis, H., Kareiva, P., Marvier, M., Chang, A., 2008. An ecosystem services framework to support both practical conservation and economic development. Proceedings of the National Academy of Sciences 105, 9457–9464. Tang, H., Zheng, Y., Chen, F., Chen, L., Zhang, H., Kong, J., 2008. Ecosystem services valuation of difference croplands and cropping systems in beijing suburb. Ecol. Econ. 7, 86–89. Tonon, S., Mirandola, A., et al., 2003. Emergetic and exergetic analysis of a combined cycle power plant. In: Brown, M.T. (Ed.), Emergy Synthesis 2: Theory and Application of the Emergy Methodology. Center for Environmental Policy, University of Florida, Gainesville, FL, pp. 157–170. Ulgiati, S., Brown, M.T., 1998. Monitoring patterns of sustainability in natural and man-made ecosystems. Ecol. Model. 23–36. Vassallo, P., Paoli, C., Rovere, A., Montefalcone, M., Morri, C., Bianchi, C.N., 2013. The value of the seagrass Posidonia oceanica: a natural capital assessment. Marine Pollution Bull. 75, 157–167. Watanabe, M.D.B., Ortega, E., 2011. Ecosystem services and biogeochemical cycles on a global scale: valuation of water: carbon and nitrogen processes. Environ. Sci. Policy 14, 594–604. Watanabe, M.D.B., Ortega, E., 2014. Dynamic emergy accounting of water and carbon ecosystem services: a model to simulate the impacts of land-use change. Ecol. Model. 271, 113–131. W., Wei, 2007. Groundwater age and recharge temperature in the Quantenary aquifers in North Chian Plain. Dissertation for master degree of Chinese Academy of Geological Sciences. (in Chinese). Yang, W., Chang, J., Xu, B., Peng, C., Ge, Y., 2008. Ecosystem service value assessment for constructed wetlands: a case study in Hangzhou, China. Ecol. Econ. 68, 116– 125. Yuan, Z., Shen, Y., 2013. Estimation of agricultural water consumption from meteorological and yield data: a case study of Hebei, North China. PloS One 8, e58685. Yuan, Y., Liu, J., Jin, Z., 2011. An integrated assessment of positive and negative effects of high-yielding cropland ecosystem services in Luancheng County, Hebei Province of North China. Chin. J. Ecol. 30, 2809–2814. Zeng, J.H., Wang, Z.P., Hu, C.S., Zhang, Y.M., 1996. Soil organic matter decomposition and accumulation characteristics in North China. Soil Fertil. 4, 1–14. Zhang, X.Y., Yuan, X.L., 1995. A field study on the relationship of soil water content and water uptake by winter wheat root system. Acta Agric. Boreali-Sin. 10, 99– 104 (in Chinese). Zhang, Y.M., Hu, C.S., Zhang, J.B., Li, X.X., Dong, W.X., 2006. Nitrogen cycling and balance in agricultural ecosystem in piedmont plain of Taihang Mountains. Plant Nutr. Fertil. Sci. 12, 5–11. Zhang, W., Ricketts, T.H., Kremen, C., Carney, K., Swinton, S.M., 2007. Ecosystem services and dis-services to agriculture. Ecol. Econ. 64, 253–260. Zhang, X.Y., 1997. Variation of root, leaf water potentials and stomatal resistance among ten millet varieties. Eco-Agric. Res. 5, 37–39 (in Chinese). Zhang, G.M., 2003. Study on emission fluxes of greenhouse gases from cropland soils and their regional estimation. Dissertation for master degree of Shanxi Agricultural University (in Chinese).