Improving ecological conservation and restoration through payment for ecosystem services in Northeastern Tibetan Plateau, China

Ecosystem Services 31 (2018) 181–193

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Improving ecological conservation and restoration through payment for ecosystem services in Northeastern Tibetan Plateau, China Lin Huang a,⇑, Quanqin Shao a, Jiyuan Liu a, Qingshui Lu b a b

Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China University of Jinan, Jinan, China

a r t i c l e

i n f o

Article history: Received 30 September 2016 Received in revised form 7 April 2018 Accepted 14 April 2018

Keywords: Payment for ecosystem services Ecological restoration and conservation Ecosystem change Alpine regions

a b s t r a c t To protect biodiversity, restore ecosystems and improve the livelihoods of indigenous herders, a payment for ecosystem services program has been implemented in the Northeastern Tibetan Plateau. We monitored and assessed its effectiveness and analysed the factors that may contribute to the success or failure of the program. By comparing ecosystem changes between project and non-project regions, we found that the increased area of grassland and wetland, the proportion of restored grassland, and the enhanced net primary production and forage yields were higher in project regions, which indicated that the majority of restoration measures are effective at the local scale. However, the soil erosion modulus and ecosystem soil conservation service were ineffective owing to unrecovered root systems and increased precipitation. The results of interviews with herdsmen demonstrated a slight increase in annual net income for herder households, especially for eco-immigrants compensated by the program. However, it was difficult to reduce overgrazing dramatically because eco-immigrants mainly included elderly herders and herders with less livestock. Therefore, the eco-immigrants and their livelihoods need to be reconsidered in targeting for subsequent programs. Furthermore, this study reinforced the need to apply multiple sources of funds and measurements to benefit ecological conservation in alpine regions. Ó 2018 Elsevier B.V. All rights reserved.

1. Introduction Governments and non-governmental organizations have invested billions of dollars to restore and conserve biodiversity and ecosystem services. However, these investments still fall far short of what is required. To minimize biodiversity loss with limited monetary resources, biodiversity hotspots have been prioritized for investment (Myers et al., 2000; Brooks et al., 2006). Efficient conservation investments should integrate biological values with demographic, political, cultural and socioeconomic conditions (Wilson et al., 2006; Chen et al., 2009). Payment for Ecosystem Services (PES) represents an important conservation policy in recent years (Lima et al., 2017; Arriagada et al., 2018), and emerged as a measurement for maintaining and providing of ecosystem services, conserving biodiversity and enhancing rural livelihoods (Torres et al., 2013; Ingram et al., 2014; Grima et al., 2016). It can serve as the role of a ’market’ for ecosystem services (Scheufele and Bennett, 2017), and an innovative approach to restoration that is being applied increasingly often at scales ranging from the local to the global (Wunder et al., 2008; Farley and ⇑ Corresponding author. E-mail address: [email protected] (L. Huang). https://doi.org/10.1016/j.ecoser.2018.04.005 2212-0416/Ó 2018 Elsevier B.V. All rights reserved.

Costanza, 2010). It seeks to engage a much wider range of people, policies, and financial resources in conservation and offers a promising way to align conservation and economic development to simultaneously enhance human well-being and protect biodiversity and life-support systems (Balvanera et al., 2001; Goldman et al., 2008). Since the early 1990s, hundreds of Payment for Ecosystem Services (PES) schemes have been implemented worldwide (Grima et al., 2016). Numerous schemes of PES are in place in Latin America (Martin-Ortega et al., 2013), especially United States, Mexico, Brazil. And Asia countries like China, Indonesia, the Philippines, Nepal, Vietnam, and Cambodia. Some Europe countries like UK, Germany and Finland, and some Africa countries like Tanzania. These PES schemes varied amongst PES type, ecosystem service paid for types of services, payments specifics, involved actors, duration, and spatial scale (Sattler et al., 2013). It focused on water-related (Huber-Stearns et al., 2015; Richards et al., 2017), forest (Suhardiman et al., 2013; Matthies et al., 2015; Thompson et al., 2017), agricultural land (Kwayu et al., 2014). However, PES schemes have received as much criticized as they are acclaimed (Lima et al., 2017; Grima et al., 2018). Critical aspects demonstrated as the measurement of ecosystem services and the valuation of additional services (Kumar et al., 2014), whether or not

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these schemes improve quality of life (Arriagada et al., 2018), unreliable assumptions and hardly demonstrated evidence of outcomes, and neglecting uncertainties (Lima et al., 2017). Therefore, many scientists and practitioners have proposed that more new methods, tools, and approaches were needed aiming to improve the scientific basis, to enhance the positive outcomes and to overcome some of the limitations (Lima et al., 2017; Grima et al., 2018). A detailed account of ecosystem services, and a better understanding of how and at what rate ecosystem services are produced, can be used to motivate payment for restoration. These payments may come from people who directly or indirectly interact with the ecosystems and from governmental and other agencies that would have to pay for these services if the ecosystems were to become degraded (Tallis et al., 2008). However, enhancing the protection of important ecosystems often requires tradeoffs between regulation and cultural services (Raudsepp-Hearne et al., 2010). Environmental restoration implemented in a way that is desirable from a societal point of view is often unattractive to those who directly manage ecosystems (Wunder et al., 2008; Cao et al., 2009). Therefore, the tradeoffs among multiple ecosystem services and economic feedback, as well as the causes of these tradeoffs and possible interventions, should be identified in different landscapes and at different scales (Raudsepp-Hearne et al., 2010). Current approaches to biodiversity conservation and poverty alleviation have significant limitations, particularly a lack of sensitivity to local cultural and social contexts (Palma-Solis et al., 2008). However, economic poverty tends to be high within biodiversity hotspots, making it necessary to address conservation and poverty simultaneously (Fisher and Christopher, 2007). The challenge for sustainable development in biodiversity hotspots, therefore, is to reduce poverty without increasing the ecological footprint (Bhagwat et al., 2011). A number of large-scale ecological conservation programs and policies utilizing PES schemes have been implemented at national, regional and local levels in China. The important PES schemes were implemented for Ecosystem function conservation areas (EFCAs) since 2011, for forest benefits like the Natural Forest Conservation Program (NFCP) (Yin et al., 2014; Viña et al., 2016) and the Grain for Green Program (GFGP) (Liu et al., 2008a; Cao et al., 2009; Schomers and Matzdorf, 2013; Wang et al., 2017), for grassland and watershed conservation and for environmental restoration of mining sites (Pan et al., 2017). Comprehensive monitoring and assessment of the effectiveness of PES programs are essential to adjust and refine policies (Yang et al., 2013). Many studies have assessed the ecological and socioeconomic impacts of the largescale national PES and some local schemes. Liu et al. (2017) highlights the importance of strictly protected nature reserves be used to guide eco-compensation for local beneficiaries. Shen et al. (2017) recommended three payment standards to protect mountain ecological forests in Beijing. Sheng and Webber (2017) suggested that many factors need to be considered in designing payment systems for watershed services to establish an incentive-compatible scheme. However, these assessments are mostly scattered, fragmented, short-term and opportunistic (Liu et al., 2008a). Little is known about the effectiveness of these programs and policies at the national level (Viña et al., 2016) and interactive effects of ecological and socioeconomic benefits. From 2005 to 2012, 7.5 billion Yuan (US$924.79 million) have been allocated to restoring the ecosystems through an integrated PES program in the Three River’s Source Region (TRSR), Northeastern Tibetan Plateau. It has been mainly implemented in the Sanjiangyuan National Nature Reserve (SNNR), which covers 41.67% of the TRSR (PGQP, 2005) and was established to protect the headwaters of the Yangtze River, the Yellow River, and the Mekong River. The payment funds were provided by the central

government (6.576 billion Yuan) and local government (0.931 billion Yuan), of which 65.6% was invested in ecological conservation and restoration, 27.6% was used to build infrastructure to improve resource production and living conditions for the local communities, and 6.8% was used for artificial rainfall, monitoring and research, according to the plan for the program (See Supplementary Table S1). For the primary project, key measurements were taken and assessment focused on the objectives that were defined (See Supplementary Table S2). The main goal of the program is to increase the vegetation coverage of grassland, enhance the water conservation capacity, and reduce soil erosion, to improve the ecological quality of wildlife habitat and the welfare of the area’s herdsmen, by fostering markets for the goods and services that local people can produce or extract from their local ecosystems (Shao et al., 2016). It seeks to maintain reasonable livestock and population carrying capacity in the natural grassland by reducing or transferring 4.59 million sheep unit. It is important to evaluate the efficacy of the payment program, which promote ecological restoration with measures designed to ensure the livelihoods and cultural survival of herdsmen and mobilize the entire community to pursue a well-articulated conservation strategy. To this end, a standard set of measures and approaches was established to quantify and monitor changes in ecosystem services and the responses of local communities. In this study, to assess the ecological and parts of socioeconomic improvement of the program, we first examined the changes of ecosystem area and conditions, especially the variations of grassland ecosystem, using a rigorous before-and-after comparison between regions undergoing a series of ecological restoration projects and other non-project regions. Then, we quantified the changes in living conditions of herders due to the impacts of program and their responses. In addition, we analyzed the factors that may contribute to the success or failure of the program, with the goal of promoting sustainable restoration through balancing ecological and socioeconomic consequences. 2. Methods The field observations, herdsman interviews, remote sensing satellite products, and modeling approaches were integrated to monitored and assess the ecological and effectiveness of the payment for ecosystem services program and its impacts on the social well-being of impacted populations, and then the factors that may contribute to the success or failure of the program were analysed. 2.1. Study area The TRSR is the headwaters of the Yangtze River, the Yellow River, and the Mekong River (Fig. 1) and covers 0.36 million km2. It is also one of the most important biodiversity hotspots in China. The region is regarded as a gene pool of 2238 rare species of vascular plateau plants and is a suitable habitat for more than 400 endangered animal species (Li and Li, 2002). Glaciers, permafrost, lakes and snow are widespread in this region, as its average altitude is above 4000 meters and its average annual temperature is
5.6 to
3.8 °C. According to 2010 census data on the household registration statistics of populations by region, approximately 0.6 million people live in the region, of which 68.15% are herders. Natural grazing is the main mode of production. The traditional customs and concepts of herders consider livestock ownership to be a sign of wealth. Therefore, high grazing and poaching pressures, high poverty, and socially marginalized populations of indigenous people have resulted in serious grassland degradation and desertification and rapid biodiversity loss (Fan et al., 2011). Nearly 600 million people who live downstream depend on the proper

L. Huang et al. / Ecosystem Services 31 (2018) 181–193

183

Fig. 1. Distribution map showing the location and project regions of the Three River’s Source Region.

functioning of the ecosystems in this region for their livelihoods. The SNNR can be divided into 6 subareas, including the source region of the Yellow River (HR), the source region of the Yangtze River (YR), and the Central Southern (CS), Southeastern (ES), Geladandong (GL), and Maixiu (MX) project regions. 2.2. Interviews with herdsmen Ecological migration here refers to the government-led migration of herdsmen out of the SNNR to conserve and restore the ecosystem and environment. Those herdsmen need to change their original nomadic pastoralist lifestyle to modern living style. Investments in ecological migration accounted for 8.4% of the total funds paid to reduce anthropogenic pressures on grassland. To evaluate the success or failure of ecological migration, we interviewed the herdsmen in the TRSR using Participant Rural Appraisal (PRA) from mid-July to mid-August in 2007 and 2011. We investigated their opinions of the ecosystem conservation program and analyzed their behaviors. We selected herdsmen who were both migrants and non-migrants as our interviewees to compare their responses. Our questionnaire was implemented with a sample of 152 households, which was randomly chosen from 1057 households in total. For non-immigrant households, the interview survey was only conducted in the area reachable by off-road automobiles or motorcycle. Information on 41 herdsmen’s households from totally 696 non-immigrant households was obtained, which accounted for approximately 5.9% of all non-immigrant households in the investigation region. For the immigrant households, 101 households were investigated from totally 361 immigrant households, which accounted for 28% of immigrant households in the investigation region. The information obtained addresses animal husbandry, income, employment, living conditions, demographic status, and the effects of migration (See Supplementary Table S3). The interviewees were asked how they would maintain their livelihoods if the program ended. In addition, the payments and incomes of herdsmen in the study area were also monitored by the Statistics Bureau. 2.3. Remote sensing methods and model simulation Remote sensing investigations were performed by human– computer interaction using Landsat satellite images from a multispectral scanner (MSS), thematic mapper (TM) and enhanced thematic mapper plus (ETM+) to survey changes in ecosystem type and the restoration of degraded grassland. The Landsat images were georectified using topographic map and ground control points, and then interpreted through analysis on RS images in two time series to produce ecosystem type spatial distribution

consisting of forest, grassland, wetland, desert and other types in the periods of 1990, 2004 and 2012, and dynamics from 1990 to 2004 and from 2004 to 2012. The grassland degradation data from 1990 to 2004 produced by Liu et al. (2008b), which can be classified into 7 categories includes fragmentation, coverage decrease, fragmentation and coverage decrease compound, swamp meadow drying, sandification and salification, grassland improving and bettering, and no degradation. Based on the degradation data, the restoration of degraded grassland was detected from 2004 to 2012 and was classified as new degradation, enhanced degradation, constant, light restoration, obvious restoration, and wetland restoration. The 1 km SPOT-VGT NDVI for 10-day intervals from 1998 to 2012 was collected and composited to produce the annual maximum NDVI values, which were then applied to calculate annual maximum vegetation coverage,

VC ¼ ðNDVI
NDVImin Þ=ðNDVImax
NDVImin Þ

ð1Þ

In which VC is vegetation coverage, NDVImin is the NDVI value of bare land without vegetation, and NDVImax is the NDVI value of pure vegetation. Then, the vegetation coverage was analyzed and compared between the periods of 1998–2004 and 2004– 2012 to illustrate the restoration or deterioration of vegetation. The Global Production Efficiency Model (GLO-PEM) was applied to measure Net Primary Production (NPP), which uses satellitederived variables that consist of linked components describing the processes of canopy radiation absorption, utilization, autotrophic activity and respiration as well as the regulation of these processes by environmental factors (Prince and Goward 1995). The details of the model were provided in Supplementary content. In the more sophisticated version of the model improved by Chen et al. (2012), we used detailed data that were specific to the grassland types in the study area and additional remote sensing inputs of photosynthetically active radiation (PAR) and soil moisture, along with local parameters of optimum temperature for vegetation growth and the ratio of above- and below-ground grassland production (Fan et al., 2008) to predict daily and annual NPP on each grid from 1988 to 2012. Outputs of the model were evaluated using the field-collected data. Annual variation rates of NPP were calculated as a function of climate, elevation, vegetation density, grass type, land use, and the timing of land-use transition. 2.4. Field investigation, observation and other materials To provide a basis for comparison, 113 representative grassland monitoring plots in the project region and 75 plots outside the project region with similar background climate and site conditions were selected according to constructive species of grassland to

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collect data on grassland ecosystem change (Fig. 2). In each field plots, five 1  1 m quadrats were established in a 40  50 m region, and community-level structure, species, below-ground and aboveground biomass were observed annually from 2006 to 2012. We performed an analysis of grass coverage, community diversity and yield proportion over 5 years to produce overall values inside and outside of the project region to avoid statistical uncertainties. The soil erosion modulus was monitored in 21 fixed sites (Fig. 2) from 2004 until 2012 by traditional virtual erosion pins. In addition, to quantitatively measure the soil erosion modulus in different degraded grassland, 137Cs techniques was applied. Two parallel transects are set from the top to the bottom of a slope, and 7–9 sampling plots separated by a 15–30 m interval in each of two parallel transects were established, in which 2 plots were section samples and 5–7 were bulk samples. The bulk samples were collected using a column cylinder drill with a 90 mm internal diameter and 24 cm depth, and section samples were collected as sub-samples with 2–6 cm increments (0–2, 2–4, 4–6, 6–8, 8–12, 12–18, and 18–24 cm). The average annual soil erosion modulus of the slope could be calculated based on the observations of each sample. We obtained observation data sets of the temperature and precipitation from 17 national and local meteorological stations that are located in the TRSR and have weather records spanning the study period. The surface runoff data between 1975 and 2012 in the primary hydrological control stations on the Yellow River (Jimai station with no glacier) and on the Yangtze River (Tuotuo River station, with glacier) were collected from hydrological yearbooks and analyzed to assess the variations of glaciers. In addition, investments in education, communication and other cultural, social or economic indicators were gathered from the statistics of the local governments within each study area, or were collected from statistical yearbooks in Qinghai Province.

changes for control and intervention (CI). BACI is theoretically a stronger research design than BA or CI, because a BACI study design with matching allows the analyst to isolate the causal effects of any conservation or climate change intervention, even when implemented in carefully selected sites that are subject to multiple other influences (Sills et al., 2017). To implement the BACI study design, answer cause-and-effect questions, and analyzes the multiple factors that may contribute to the ecosystem change in study area, two comparisons were processed. One compared the ecosystem change in and outside of project areas before and after program, and the differences were considered the main effects of the program. The other comparison between actual climate and program, and what would have happened in the absence of the program, by applying the GLO-PEM and take the NPP as an example. The treatment group inputted multi-year mean temperature, precipitation and solar radiation to simulate NPP under average climate conditions. The comparison group inputted actual climate and land surface conditions. The estimated impact of the program is calculated as the difference in mean outcomes between the treatment group and the comparison group. Specifically, the separate impacts can be calculated as follows (Shao et al., 2017):

CC ¼

GT a
GT b jGC a
GCb j

ð2Þ

CP ¼

GC a
GCb
CC jGC a
GCb j

ð3Þ

where C P represent impacts of ecological program, C C represent impacts of climate change, GT a and GT b represent indicators amount after and before the program for the treatment group, GCa and GC b represent indicators amount after and before the program for the comparison group.

2.5. Impact evaluation and attribution analysis 3. Results The impact evaluation employed a before-after-control-inter vention (BACI) study design (Khandker et al., 2010) to address the changes and evaluate the impacts of payment for ecosystem services program. BACI data on conservation initiatives are rare in part because of the requirement for careful sample design and data collection before the intervention begins (Sills et al., 2017). The designs commonly used by researchers were comparing changes before and after (BA) the intervention, or comparing

3.1. Area changes of ecosystems inside and outside of the project regions Comparing the trends before and after the program, the grassland area in the project region increased by 135.2 km2, while it decreased by 11.4 km2 in the non-project regions (Table 1, Fig. 3). Increasing grassland primarily occurred in the HR and CS

Fig. 2. Distribution of the field investigation plots in the Three River’s Source Region.

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L. Huang et al. / Ecosystem Services 31 (2018) 181–193 Table 1 Area changes of ecosystems inside and outside of project regions during the period of 1990–2004 and 2004–2012. 1990–2004

CS HR ES YR GL MX Pro Npro

2004–2012

Agr

For

Gra

Wet

Desert

Other


3.3


5.8
1.7
5.6


8.6
477.3 6.9 99.9
2.4 0.7
380.7
83.4


0.08
21.9

13.3 503.5
1.3
102.4
5.4
0.3 407.4 43.8

1.1 0.6 0.03


3.3 1.3


0.3
13.4
0.7

2.4 7.9
11.7
14.7

1.7
53.6

Agr

7.8

For

Gra

Wet

13.6
1.51

59.9 77.8 3.9
2.7
3.5
0.3 135.2
11.4

4.3 96.7
3.3 5.8 1.4

0.22 12.3 3.3

104.9 181.1

Desert
171.8
3.2
17.1
192.1
300.5

Other
77.8
1.6
0.6 0.1 19.2 0.3
60 119.7

Note: HR: the source region of the Yellow River; YR: the source region of the Yangtze River; CS: the Central Southern; ES: Southeastern; GL: Geladandong; MX: Maixiu. Pro: the sic subareas of SNNR consist of CS, HR, ES, YR, GL, MX; Npro: Non-project regions of SNNR out of the six subareas. Agr: agricultural area; For: forest; Gra: grassland; Wet: wetland.

Fig. 3. The proportion of area changes (above) and annual area change rates (below) of four primary ecosystems accounted for in the total area of each region before (grey bar for 1990–2004) and after (black bar for 2004–2012) the program.

project regions, with increases of approximately 77.8 and 59.9 km2, respectively, which were mainly transferred from deserts. Decreasing grassland area primarily occurred in the GL and YR project regions with decreases of 3.5 and 2.7 km2, respectively, which was mainly covered by expanding wetlands. The wetland area in the project region increased by 104.9 km2 (Table 1, Fig. 3), which was lower than the increase of 181.1 km2 in the non-project region. The primary reason for this was that increases in precipitation and glacial melt-off have led to gradual

improvement in the runoff and moisture conditions in the TRSR (Fig. 4). Increase in the wetland area was most prominent in the HR project region (Fig. 3), with a net increase of 96.65 km2. It was primarily transferred from desert and grassland around Zhalin Lake and Erlin Lake, the largest wetland area in the source region of the Yellow River, which has expanded quickly in recent years. We compared changes in desert area before and after the program. Before the program, the desert area within the project region increased more than that outside the project region, and then after

Fig. 4. The anomaly of annual precipitation in each region and runoff in key hydrological stations from 1975 to 2012.

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L. Huang et al. / Ecosystem Services 31 (2018) 181–193

Table 2 Vegetation change as a result of the environmental conservation program. Items

In the project regions

Shrub cover, % Shrub biomass, g/m2 Average vegetation species, No. per ha Forage yield, kg per ha Note: *p value < 0.01,

**

0.01 < p value < 0.05,

***

Non-project regions

1990–2004

2004–2012

Change%

1990–2004

2004–2012

Change%

11.65** 780.53** 11.33*** 2161.37**

32.82** 869.69** 13.11** 2342.20**

181.72 11.42 15.93 8.37

25.68** 803.68** 11.65*** 2384.82**

43.46** 829.75** 12.46** 2386.72**

69.24 3.24 6.84 0.08

0.05 < p value < 0.1,

****

p value > 0.1.

the program decreased by 192.1 km2 less than the decrease in the non-project regions (Table 1, Fig. 3), which could indicate that the program curbed the trend of desertification. Based on the monitored results of the areas where desertification prevention programs were implemented (Table 2), it can be seen that the desert area in protected areas decreased by 17,235 hectares, which amounts to 39% of the intended goal. The most prominent reduction in desert area (171.8 km2) was observed in the HR project region. This can be attributed primarily to increases in grassland and wetland ecosystems. The second largest reduction was seen in the GL project region, with a net reduction of 17.1 km2. To a certain degree, changes in the desert ecosystem reflect the current gradual improvement of the TRSR ecosystem structure. Forest was mainly distributed in the CS, ES and MX project regions. It was found that the forest area within the project region increased by 12.3 km2 (Table 1, Fig. 3), which was much greater than the increase in forest area in the non-project regions. The forest ecosystem in the CS project region experienced a major

increase, growing by 13.59 km2. This indicates that the forest conservation projects were effective in increasing the forest area in the CS project region more than in the non-project region. However, the increased forest area in MX was less than in the non-project region, there was no significant change in ES, and there was even a decrease of 1.51 km2 in the HR project region, which means that the forest projects showed very limited effects in the TRSR. The agricultural area within the project regions remained unchanged, while that in the non-project regions had a net increase of 7.84 km2. 3.2. Variations in the grassland ecosystem before and after the projects According to the statistics on grassland change, we can see that the area of grassland restoration accounted for 30.9% of the total grassland area in the project region, which was significantly greater than the 21.13% in the non-project regions (Fig. 5a). The percentage of light and obvious grassland restoration in the project

Fig. 5. (a) The statistics of grassland restoration and degradation inside each project region and outside the project area, and (b) spatial distribution of grassland restoration during 2004–2012 in the TRSR.

Fig. 6. The (a) spatial variation of vegetation coverage and (b) temporal trends of NPP in the TRSR.

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L. Huang et al. / Ecosystem Services 31 (2018) 181–193 Table 3 The variation in trends of vegetation coverage and NPP inside and outside of the project area before and after the program in the Three River’s Source Region. Regions

CS HR ES YR GL MX In the project region In the non-project regions

NPP variation (gC m
2 y
1)

Vegetation coverage (%) 1990–2004

2004–2012

Changes

1990–2004

2004–2012

Changes

61.27** 46.25* 69.64** 39.47* 18.92*** 70.34*** 44.94** 41.58**

63.67** 49.47* 71.59** 42.64* 20.27** 73.69** 47.81** 44.15**

2.39 3.21 1.95 3.18 1.34 3.35 2.87 2.57

0.17** -1.47* 2.346** 2.11* 1.99** 0.53** 0.95** 0.79**

4.77** 7.77* 6.41** 4.15* 0.376** 5.917** 4.90 ** 1.08**

4.59 9.23 4.06 2.04 -1.61 5.39 3.95 0.29

Note: HR: the source region of the Yellow River; YR: the source region of the Yangtze River; CS: the Central Southern; ES: Southeastern; GL: Geladandong; MX: Maixiu. NPP: net primary production. * p value < 0.01, ** 0.01 < p value < 0.05, *** 0.05 < p value < 0.1, ****p value > 0.1

regions was higher than in the non-project regions by 7.53% and 2.24%, respectively. In addition to the positive impacts of warmer and wetter weather, this can be explained by the fact that grassland restoration measurements were effective. Especially in the regions that implemented the BBH and FRRP, the proportion of restored grassland accounted for 4.49% (156.4 km2) and 1.35% (866.7 km2) of planning area (Table 2), respectively. The spatial distribution of grassland restoration (Fig. 5b) shows that the obvious grassland restoration in western HR and Northern YR were continuous with large areas. The light and obvious restorations in HR and YR accounted for 28.26% (4283.2 km2) and 10.54% (1598.3 km2), and 22.95% (5002.5 km2) and 5.99% (1304.9 km2) of its total grassland area, respectively. According to grassland monitoring in plots, the number of plant species in the project region increased by 15.93% where grazing was prohibited (Table 2), which is a greater increase than that reported outside of the project region. In our interviews with the herders, we learned that populations of wildlife increased dramatically on conservancy lands owing to protection and the halting of poaching. Some populations even increased by as much as 500%, especially the endangered Tibetan antelope (Pantholops hodgsonii), Kiang (Equus kiang), Tibetan gazelle (Procapra picticaudata), and blue sheep (Pseudois nayaur). Some species, such as wild ass, wild yak, argali, snow leopard, and black-necked crane returned to inhabit the area. Corridors across fences and roads were constructed to allow wildlife to move. According to field investigations in grassland plots, the shrub cover increased by 181.7%, which was a significant improvement compared with the increase of 69.24% in the non-project region (Table 2). Comparing the spatial trends before and after the

program (Fig. 6a, Table 3), the multi-year average vegetation cover increased in the project region by 2.87% and by 2.57% in the nonproject regions. The HR, YR, and MX project regions experienced the most pronounced increase. Concerning the changes in vegetation coverage, growth (0.98%/year) in the HR project region was much higher than that in the non-project regions (0.37%/year), which indicates that the implementation of the program has been effective in improving the level of vegetation coverage to some extent. 3.3. Changes in ecosystem conditions due to the projects Vegetation NPP in the project region saw a fluctuating growth trend (Fig. 6b, Table 3). After eight years of program implementation (2004–2012), when compared with the 14 years prior to implementation (early 1990s to 2004), the NPP for each project region showed a growth trend in the CS, ES, and MX project regions, performing better than in the non-project regions. Furthermore, shrub biomass was observed to increase by 8.18% in the project region, a greater increase than outside the project region. This may reflect the ability of the project to improve the ecosystem’s production. From the field plots, the soil erosion modulus of slopes typical of alpine-cold meadows in the TRSR ranged from 4.15–8.80 t hm
2 yr
1 and increased to 11.96, 24.56 and 38.24 t hm
2 yr
1 when the meadow degraded by an intermediate, severe and extreme degree, respectively. The average soil erosion modulus in 21 fixed soil erosion observation sites appeared to fluctuate; trends averaged 2579.5 t km
2 yr
1 from 2004 to 2012 (Fig. 7a). The land experiencing moderate soil erosion changed from

Fig. 7. (a) Average soil erosion modulus in the field observation sites, and (b) area change of soil erosion before and after the program inside and outside of the project area in TRSR.

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increasing erosion before the projects to decreasing erosion after the projects in project regions, and it showed continuously increasing erosion in the non-project regions (Fig. 7b). Moreover, these decreases were significantly greater than those found outside the projects. Average water conservation amounts in the forest, grassland and wetland ecosystems were 14.25 billion m3 during 1997–2004

and 16.47 billion m3 from 2004 to 2012 in the TRSR (Fig. 8a). The anomalous amount represents an apparent increase in recent years, which indicates a sufficient water supply. The water conservation per unit area in the project area changed from 1106.97 m3/ hm2 during 1997–2004 to 12164.76 m3/hm2 during 2004–2012 (Fig. 8b). It increased by 14.27%, which is higher than the rate of increase of 6.89% outside of the project area. Annual runoff

Fig. 8. (a) Average water conservation amounts of forest, grassland and wetland ecosystems in the TRSR, and (b) water conservation per unit before and after the program inside and outside of the project area.

Table 4 Statistical data of items related to eco-immigration, according to interviews in year of 2007 and 2011. Items

Indicators

Degree

Proportion

Willing to eco-immigrate

Livestock numbers

<20 sheep-units per person >20 sheep-units per person 25–35 yr 35–50 yr > 50 yr No education Primary school High school 1 person 2–3 persons 4–6 persons More than 6 persons

100% 16.1% 12.6% 20.7% 43.4% 37% 57.3% 5.7% 2% 31.7% 53.3% 13%

Yes No Folk dancing Sewing Cooking Driving Cultivation

92.4% 7.6% 9.3% 17.6% 15.3% 30.3% 19.9%

Yes No Cleaner Builder Picking Cordyceps Grazing Temporary workers Others

20.6% 79.4% 4.3% 15.2% 54.3% 8% 12% 6.2%

Improve Decrease Satisfied Dissatisfied Food and clothing Religious activities Education Medical care Yes No

86.1% 13.9% 43.6% 56.4% 50% 20.65% 18.5% 10.85% 12.5% 87.5%

Grazing Rely on relief Self-employed Unknown

21.8% 18.8% 14.9% 44.5%

Ages of interviewer

Education

Family size

Skills training

Willing to attend the training Training career choice

Employment of immigrants

Work or not Engaged in work

Livelihood of immigrants

Changes in living standards Satisfaction level Family expenses items

Enjoy free medical care Planning

Work planning in future

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increased from 12.43 billion m3 from 1975–2004 to 16.89 billion m3 from 2004 to 2012 in YR, indicating an intensified water supply to the downstream region. In contrast, the average runoff in HR decreased from 20.19 billion m3 to 19.51 billion m3. However, the reduction rate declined, implying a relatively improved water supply compared to earlier (Fig. 4a). 3.4. The effects of program on herdsman and their responses According to the analysis on the interviews, the herdsman having the willing to resettlement were mainly the elderly aged (greater than 50-year ages), which accounted for 43.4% of the investigated eco-immigrants (Table 4), mainly decided by the profit difference between the ecological migration and socioeconomic situations of herdsman households. The elderly interviewed choosing to immigrate in order to lighten the load on their children, because they are not able to graze and relied on their children. Young and middle-aged people need to support the elderly and raise the children, while the conditions provided by program cannot meet their needs of life. Therefore, the herdsman with middle-aged (ages between 35 and 50 years) and young-aged (ages less than 35 years) accounted for only 20.7% and 12.6% of the investigated eco-immigrants, respectively. In terms of the family size, 57.4% households with 3–5 persons willing to immigrant, but households with less than 3 persons or more than 8 persons unwilling to immigrant. Due to the special household structure in this region that some herdsman shared one rangeland certificate with their parents or brothers, which accounted for 54.5% of ecoimmigrant household. Grassland animal husbandry was the main industry of Tibetan herdsmen, which were also the sources of the food, clothing, housing, fuel and other basic necessities of life. Therefore, herdsman households with livestock more than 20 sheep units per person are unwilling to move out of their original region. However, households with less livestock (livestock numbers less than 20 sheep-units per person), or even no livestock having the willing to immigrant, which accounted for 100% of the investigated immigrants. Because their previous lives was depended on the meager income of rental pastures and national relief. In addition, only 5.7% of the respondents received high school education, however the population with no education accounted for 37%, and 57.5% of the respondents received 3–5 years primary school. Lower education makes it difficult for them to integrate into modern society. According to statistics, the average annual livestock number in the TRSR was 15.41 million sheep unit during 2004–2012, and compared to the livestock number of 16.53 million sheep unit during 1997–2004, it only decreased by 6.6% since the program (Fig. 9). Skills training provided by the government was undertaken by 92.4% of the investigated immigrants (Table 4). The training activities consists of scientific breeding, epidemic preventing, automobile repair and driving, vegetable cultivation in greenhouses,

Fig. 9. The livestock numbers from 1990 to 2012.

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carpet weaving, folk dancing, folk art carving and painting, etc. Approximately 30.3% of immigrants chose driving training. This was followed by training in breeding and sewing, which accounted for 19.9% and 17.6% respectively. And 15.3% selected the training of cooking, and only 9.3% likes to choose the folk dancing. However, the actual employment rate in the resettlement area was only 20%, out of which approximately 54.3% of the immigrants chose to pick wild Cordyceps, which provides high income at low cost. This was followed by builders and temporary workers, accounting for 15.2% and 12%, respectively. Because animal husbandry is the primary source of income, and many people are nomadic, the employment rates presented above do not completely reflect the actual standard of living in a largely non-cash economy. After 3–6 years, 86.1% of the immigrants felt that their lives had improved compared to pre-resettlement, due to convenient transportation and electricity, better education and housing. However, only 43.6% of the immigrants were satisfied with their lives. The main reason was the lower subsidies of resettlement and higher consumption expenditure compared with that before the migration. Due to the increased expenses of meat, milk and other food, they had to change the traditional meat based diet to plant food. In addition, the pastoral medical insurance system was provided by the government, but only 12.5% of respondents receiving free medical treatment. Most herders feel that the effects of free medical treatment were poor and unwilling to it. Examining the views of eco-immigrants regarding their future livelihoods when the program ends, we see that 44.5% of immigrants did not know what they would do, 21.8% planned to return to grazing, 18.8% planned to rely on relief, and only 14.9% hoped for self-employment. 4. Discussion and conclusions 4.1. The effects of climate change and payment programs on ecological restoration According to attribution analysis of climate change and payment program by applying the impact evaluation, we can see that the results under treatment and comparison conditions showed large discrepancies between the project regions (Table 5). It could be concluded that climate change is the primary driving forces for the ecological dynamics in this region (Chen et al., 2014), with impacts accounted for 67–86% in six project regions especially in ES and GL, and nearly 90% outside of the project region. Compared to the average temperature during 2004–2012, the average temperature increased by 0.62 °C, and average annual precipitation increased by 55.1 mm in the period of 2004–2012. Increased temperature and precipitation contribute to a warm and wet climate in the region, resulting in the slowdown of the desertification process and a reduction in the area affected by desertification (Xue et al., 2009). In addition to these climatic impacts, ecological conservation and restoration measures in the payment program contributed 14–33% to ecological change in project regions especially in HR and MX, which were higher than that outside of the project regions (Table 5). Ecological resettlement and decreased livestock contributed to reducing human activities and decreased the intensity of land use in the region. These factors also promoted local improvement of ecosystems, enhanced ecosystem services, and curbed the trend of grassland degradation to some extent (Alkemade et al., 2013). Since the implementation of the payment program, water bodies have expanded and the desert has been partially transferred to grassland. This shows that while the ecological situation in the TRSR has gotten better in the past decade, it has not yet reached the optimal ecological status of the 1970s. Comparing

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Table 5 Attribution analysis on the impacts of climate change and payment for ecosystem services program. Regions

CS HR ES YR GL MX Inside the project region Outside the project regions

Treatment condition

Comparison condition

GT b

GT a

Change

GC b

GC a

Change

331.29 277.99 349.46 214.15 128.90 390.60 308.38 288.99

340.80 298.46 360.00 228.07 144.88 408.09 328.37 303.17

9.51 20.47 10.54 13.92 15.98 17.49 19.99 14.18

326.58 267.38 347.07 208.74 124.13 380.75 297.77 284.40

339.45 297.21 359.29 227.71 143.72 407.03 327.23 300.21

12.87 29.83 12.22 18.97 19.59 26.28 29.46 15.81

CP

CC

26.11 31.38 13.75 26.62 18.43 33.45 32.15 10.31

73.89 68.62 86.25 73.38 81.57 66.55 67.85 89.69

Note: HR: the source region of the Yellow River; YR: the source region of the Yangtze River; CS: the Central Southern; ES: Southeastern; GL: Geladandong; MX: Maixiu. C P : impact of ecological program; C C : impact of climate change, GT a : indicator amount after the program (2004–2012) for the treatment group; GT b indicator amount before the program (1990–2004) for the treatment group; GC a indicator amount after the program (2004–2012) for the comparison group; GC b indicator amount before the program (1990–2004) for the comparison group.

vegetation coverage before and after the program, we can see that the average annual vegetation coverage in the TRSR improved significantly. The area with improved vegetation coverage accounted for 79.18% of the total area of the TRSR, in which slight and significant improvements accounted for 43.67% and 35.51%, respectively. Therefore, we can conclude that the regional vegetation coverage at the spatial scale was controlled by climate. However, the increase was obvious in local regions that implemented the projects under similar climate conditions. Furthermore, vegetation restoration enhanced the ecosystem service of soil conservation. However, the area of land experiencing severe soil erosion decreased more sharply in the non-project regions than in the project regions, which illustrated that the impacts of the projects on the control of soil erosion are limited at present. However, grasslands in both the project region and non-project region also showed mild degradation, which means that human disturbances continue to damage the grassland and require sustained attention in the future. In addition, when compared to coverage by the same healthy grass type in the 1970s, approximately 35% of the grassland still requires further restoration, mainly in the source region of the Yangtze River and the source region of the Yellow River. Furthermore, besides to promoting vegetation growth, increased precipitation has also led to a significant increase in the rainfall erosion force, and thus the amount of soil erosion has increased. Against the background of climate change, ways to identify and promote the effects of ecological conservation should be further discussed. Therefore, the preliminary protection and partial improvement of the eco-environment is a reminder that ecological restoration and conservation in the TRSR require continuous and sustainable efforts. 4.2. Is ecological migration an effective means of reducing overgrazing and improving herders’ livelihoods? In the TRSR, ecological migration means that herders must not only change their locations but also their lifestyles. They must shift from traditional nomadism to settlement and from livestock breeding to functioning in a complicated market-oriented economy (Zhou et al., 2010). Due to the sudden changes in the language environment, lifestyle, production mode, interpersonal relationships, it is very difficult for herdsmen to change their traditional lifestyles that they have followed for thousands of years (Li et al., 2014). It is often more difficult than teaching a production skill. In addition, most of the immigrants did not adapt to new patterns of town life after leaving their nomadic lives behind, and so it needs a long period for several years of adaptation, and additional support in the form of training and money. Although the herdsmen that chose to migrate were compensated with a number of subsidies, they experienced difficulties in

increasing their incomes owing to their lack of skills and the lack of appropriate jobs in the settlement. The immigrant households were primarily composed of older individuals with little or no livestock. Therefore, it was difficult to decrease overgrazing through ecological migration. After they moved to new places, approximately 92% of them were trained. However, only 20% of the immigrants were employed. The lower employment rate indicates the difficulties a herdsman faces in shifting from a nomadic pastoralist life to a settled rural lifestyle, as well as the absence of appropriate jobs in the settlement. Compared with the previous, the overall income decreased significantly. There are several main reasons: 1) based on traditional habits, pastoralists have long been grazing on grassland. Most of them are reluctant to engage in other work, so they are free at home and have no income source; 2) immigrant herdsmen with lower cultural quality and poor labor skills, and the average educational level is less than three years, so their nongrazing employment is poor and income is unstable (Zhou et al., 2010); 3) Suitable jobs for these herdsmen are limited; and 4) ecological payment cannot effectively compensate for the loss of income in response to ecological protection. At the same time, living expenses increased obviously compared to that before. Before the resettlement, the herdsmen obtain daily life necessities through the use of grassland resources. But all of these need to buy from the market after the migration. Although most of the eco-immigrants we investigated felt that their living standards had improved, most households were not satisfied with their current lifestyles and felt that the medical insurance provided by the government was not sufficient. The herders’ need to maintain a sustainable livelihood may restrict environmental conservation in the TRSR. If the resettled herdsmen do not achieve sustainable livelihoods, many of them will have no alternative other than to return to their old way of life, leading to a resumption of the activities that were responsible for the original environmental degradation. Therefore, in the early years of resettlement, herdsmen’s satisfaction is still relatively high, however, the satisfaction of herdsmen gradually declines along with the consumption of savings and the lack of stable income, and then most of them are eager to move back to the grassland. Single government subsidies for resettlement can only solve the problem of food and clothing. Therefore, to improve the capacity of herders to maintain a good standard of living and to manage ecosystems adaptively, major investments in public goods, especially education, are needed in the future. Considering the human aspects of development, providing appropriate long-term support on technical training and employment opportunities to those affected by the program appears to be an effective way to improve the provision of ecosystem services. Policies should be established to help herders solve their employment problems and increase their incomes. The existing more successful ecological

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resettlement policy (Farley and Costanza, 2010) cannot apply due to the minimal effects for Tibetan ecological immigrants in this region. Special ecological resettlement policies need to developed, for example, Tibetan immigrants received the subsidies also be included in the range of national ‘‘subsistence allowances”, and the medical insurance could be supported by government, and strengthen the basic education of immigrant children. In addition, attention must be directed to development of appropriate economic activities suitable for this region. These problems could be resolved by establishing livestock systems and low-income insurance systems, and by developing secondary and tertiary industries in multiple sources and forms. To treat herdsman resettlement, ecological restoration, and economic development as an integrated, multifaceted, and interlinked undertaking, herdsman should became the main part of ecological conservation, and industries should be developed ecologically. For example, the herders could be employed as the managers of ecological conservation and the undertaker of plateau ecotourism and eco-intensive animal husbandry, to establish a long-term income mechanism and expand income sources of immigrants. Therefore, it was hard to greatly decrease the overgrazing through ecological migration, because the herds and rangeland of immigrated herdsman were under the nonimmigrants shared the certificate. In terms of herders’ freedom of choice regarding resettlement, it was deduced from the interviews that the effects of the ecological migration policy were primarily influenced by livestock numbers, the herder’s age, education level, and family size. Because ecological migration would have led to an end of their pastoral lifestyles, the older herders with less livestock preferred to migrate, which limited the effects of the policy in reducing livestock numbers. 4.3. Implications and further measurements of ecological restoration in alpine regions Well-designed monitoring programs are necessary for the successful implementation of conservation and development projects (Tallis et al., 2008). In the TRSR, almost 55 million yuan raised for ecosystem monitoring has been used since 2005 to establish a comprehensive monitoring network. However, it almost focused on the monitoring of the regional ecological conditions, but ignored the changes of the level of people’s livelihood, especially the household activity monitoring. From above results we can concluded that the level of herdsmen’s livelihood directly related to the success or failure of the payment program. Therefore, an important content should be added in the comprehensive monitoring network to piloting, experimenting, and monitoring the household activities. It will contribute to play positive initiatives of households, social organizations, local governments and the central government’s enthusiasm, to the ecological conservation and restoration. Payment for ecosystem services across the region should be established according to the principles of ‘‘the one who benefits is the one who should pay” and ‘‘the one who conserves should receive payment” (Wunder et al., 2008; Farley and Costanza, 2010). In the TRSR, the payments for ecosystem services have primarily been governmental investments accomplished through financial transfers. These payments can therefore be regarded as ‘‘blood transfusion” payments rather than real payments. According to general planning (PGQP, 2005), 87.59% of the payments for ecosystem services in this program have come from China’s national government, with the remaining 12.41% of the accumulated value provided by local governments and self-supporting herders’ funds. Ideally, funding for conservation should come from downstream or from an economic development zone charging beneficiaries for the use of ecosystem services, especially water

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sources. Alternatively, funds could be generated from corporate sponsorships and other financial resources instead of only from traditional political investment payments. The high costs of conservation also encourage the development of privately funded payment schemes by nongovernmental organizations (NGOs), which can strengthen the network of protected areas (Kati et al., 2015). Some NGOs may consider increasing their spending on areas designated as priority conservation areas which, at present, are relatively underfunded (Holmes et al., 2012). Substantial gains can be made in environmental conservation, particularly in developing countries, by investing more in communication, education, and public awareness campaigns (Van der Ploeg et al., 2011), which serve as essential first steps in transforming people’s attitudes and behavior (Keane et al., 2010). According to the statistics, the expenditures for education in the TRSR increased from an annual average of 113.7 million RMB before the program to 695.48 million RMB after the program, and the number of villages with telephone service increased from 46 to 205, indicating that communication and education were improved but that effectiveness needed to be further observed. Communitybased approaches advocate the participation of local resource users and the integration of conservation and development objectives (Berkes, 2004), which allow for the sustainable management of natural resources. Community consultations can build constituencies and contextualize the concerns of directly affected people and, as such, are indispensable channels for environmental communication and education (Van der Ploeg et al., 2011). In the eastern TRSR, 11 villages launched a pilot project of village-level cooperatives by integrated the rangeland and livestock to develop modern animal husbandry since 2012. Intelligent ecological animal husbandry information platform would be developed and provided to both management and herdsmen to exchange the information of livestock and grassland by communication equipment. Policy makers might desire to see indigenous livelihoods transition from pure grazing to the industrial sector, and local governments might help some households by relaxing local constraints on off-grazing industries. However, traditional realities and the lack of institutional infrastructure mean that the local communities that directly use the ecosystems still cannot reallocate their livelihoods to other activities. We suggest that policy analysis should take into account the heterogeneity of local participants and their livelihood transition decisions, as well as how payments should target constrained communities. Policy makers need to develop more lucrative opportunities and provide more training programs to support participating herdsmen engaging in nongrazing activities. Increasing investment in local infrastructure can also help herdsmen to break down institutional constraints, achieving benefits for all parties involved. Although direct payments are expected to be cost effective, they have so far proven to be less effective in the TRSR. Therefore, it is important to consider how to balance ecological conservation and socioeconomic development. Since 2013, the second-stage program in the TRSR (NDRC, 2013) has planned to steadily promote pastoral production and living standards and further improve the payment mechanism. Herders could be employed as the managers of ecological conservation. We call for more diverse funding, effective compensation, integrated research, and comprehensive monitoring and assessments. For a large-scale payment strategy to be effective and sustainable, it must be credible, replicable, scalable, and sustainable in the long term. Payment programs should track how services flow from one region to another, who benefits from the ecosystem services, what funding pays for the protection of ecosystem services and who provides it. These programs should also track which groups or populations would need to be compensated for protecting ecosystem services and whether the project affects the delivery

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of ecosystem services (Tallis et al., 2008). Furthermore, short-term payment programs may result in only temporary conservation benefits, leading to uncertainty after the programs end. Without such support, herdsmen are likely to return to their previous activities when they can no longer survive solely on government subsidies, thereby eliminating any gains from the project (Cao et al., 2009). Acknowledgements This work was financially supported by the Key Research Program of Frontier Sciences, the Chinese Academy of Sciences (QYZDB-SSW-DQC005), the National Natural Science Foundation of China (41501117) and the National Key Research and Development Program (2017YFC0506503). We acknowledge the contributions of all members of the Three River’s Source Region-EA teams and partners who helped make this research possible. We give special thanks to the interviewees in the Three River’s Source Region for their cooperation. We thank anonymous reviewers for their helpful comments on this manuscript. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at https://doi.org/10.1016/j.ecoser.2018.04.005. References Alkemade, R., Reid, R.S., Van, d.B.M., De, L., Jeuken, M., 2013. Assessing the impacts of livestock production on biodiversity in rangeland ecosystems. Proc. Natl. Acad. Sci. U.S.A. 110 (52), 20900. Arriagada, R., Villaseñor, A., Rubiano, E., Cotacachi, D., Morrison, J., 2018. Analysing the impacts of PES programmes beyond economic rationale: Perceptions of ecosystem services provision associated to the Mexican case. Ecosyst. Serv. 29 (A), 116–127. Balvanera, P., Daily, G.C., Ehrlich, P.R., Ricketts, T.H., Bailey, S., Kark, S., Kremen, C., Pereira, H., 2001. Conserving biodiversity and ecosystem services. Science 291, 2047–2048. Berkes, F., 2004. Rethinking community-based conservation. Conserv. Biol. 18, 621– 630. Bhagwat, S.A., Dudley, N., Harrop, S.R., 2011. Religious following in biodiversity hotspots: challenges and opportunities for conservation and development. Conserv. Lett. 4, 234–240. Brooks, T.M., Mittermeier, R.A., da Fonseca, G.A.B., Gerlach, J., Hoffmann, M., Lamoreux, J.F., Mittermeier, C.G., Pilgrim, J.D., Rodrigues, A.S.L., 2006. Global biodiversity conservation priorities. Science 313, 58–61. Cao, S.X., Zhong, B.L., Yue, H., Zeng, H.S., Zeng, J.H., 2009. Development and testing of a sustainable environmental restoration policy on eradicating the poverty trap in China’s Changting County. Proc. Natl. Acad. Sci. U.S.A. 106, 10712–10716. Chen, B., Zhang, X., Tao, J., Wu, J., Wang, J., Shi, P., Zhang, Y., Yu, C., 2014. The impact of climate change and anthropogenic activities on alpine grassland over the Qinghai-Tibet Plateau. Agri. Forest Meteorol. 189, 11–18. Chen, X.D., Lupi, F., He, G.M., Liu, J.G., 2009. Linking social norms to efficient conservation investment in payments for ecosystem services. Proc. Natl. Acad. Sci. U.S.A. 106, 11812–11817. Chen, Z.Q., Shao, Q.Q., Liu, J.Y., Wang, J.B., 2012. Analysis of net primary productivity of terrestrial vegetation on the Qinghai-Tibet Plateau based on MODIS remote sensing data. Sci. China Earth Sci. 55, 1306–1312. Fan, J.W., Zhong, H.P., Harris, W., Yu, G.R., Wang, S.Q., Hu, Z.M., Yue, Y.Z., 2008. Carbon storage in the grasslands of China based on field measurements of above- and below-ground biomass. Clim. Change 86, 375–396. Fan, J.W., Shao, Q.Q., Wang, J.B., Chen, Z.Q., Zhong, H.P., 2011. An analysis of temporal-spatial dynamics of grazing pressure on grassland in Three River’s Headwater Region. Chin. J. Ecol. 33 (3), 64–72. Farley, J., Costanza, R., 2010. Payments for ecosystem services: from local to global. Ecol. Econ. 69, 2060–2068. Fisher, B., Christopher, T., 2007. Poverty and biodiversity: measuring the overlap of human poverty and the biodiversity hotspots. Ecol. Econ. 62, 93–101. Goldman, R.L., Tallis, H., Kareiva, P., Daily, G.C., 2008. Field evidence that ecosystem service projects support biodiversity and diversify options. Proc. Natl. Acad. Sci. U.S.A. 105, 9445–9448. Grima, N., Singh, S.J., Smetschka, B., Ringhofer, L., 2016. Payment for Ecosystem Services (PES) in Latin America: analysing the performance of 40 case studies. Ecosyst. Serv. 17, 24–32. Grima, N., Singh, S.J., Smetschka, B., 2018. Improving payments for ecosystem services (PES) outcomes through the use of Multi-Criteria Evaluation (MCE) and the software OPTamos. Ecosyst. Serv. 29, 47–55.

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