Ecological and environmental consequences of ecological projects in the Beijing–Tianjin sand source region

Ecological Indicators 112 (2020) 106111

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Ecological and environmental consequences of ecological projects in the Beijing–Tianjin sand source region ⁎

T

⁎

Yuanyuan Zhaoa,b, , Wenfeng Chic, , Wenhui Kuangd, Yanfeng Baoe, Guodong Dinga,b a

Yanchi Research Station, School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China Key Laboratory of State Forestry Administration on Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China c College of Resources and Environmental Economics, Inner Mongolia University of Finance and Economics, Inner Mongolia, Hohhot 010070, China d Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China e Institute of Desertification Study, Chinese Academy of Forestry, 100091 Beijing, China b

A R T I C LE I N FO

A B S T R A C T

Keywords: Wind erosion Ecosystem services Sustainability Spatiotemporal pattern Land use/cover change Ecological project

Evaluation of influences of the Beijing–Tianjin Sand Source Control Project on soil wind erosion and ecosystem services is imperative for mastering the benefits and drawbacks of the program, as well as for distinguishing more reasonable estimations to evaluate regional sustainable development. Within the Beijing–Tianjin Sand Source Region, we quantified the spatiotemporal patterns of land use/cover changes (LUCCs), soil wind erosion modulus (SWEM), and essential ecosystem services throughout 2000–2015 by utilizing field investigations, remotely sensed data, meteorological data, and modeling. The influences of ecological projects on wind erosion and ecosystem services has been subsequently assessed by using those modifications brought on via the LUCCs (e.g., conversion from cropland to grassland/woodland) during the ecological construction. The results indicated that the SWEM showed a decline and ecosystem services which included carbon storage, water retention, and air quality regulation exhibited growth driven by using both local climate exchanges and human activities such as ecological projects. Excluding the effects of climate factors, the LUCCs stemming from ecological projects caused a total SWEM decrease of 3.77 million tons during 2000–2015, of which approximately 70% was prompted by the way of the transition from desert to sparse grassland. And from this transition, ecosystem services including both water retention and aboveground net primary productivity manifest a general increase. The sub-regions of desert grassland in Bayannur, Ordos Sandy Land, and Otindag Sandy Land were hot spots for wind erosion declines and ecosystem service enhancements induced by the ecological projects. We recommend that endeavors be coordinated toward the scientific management of the degraded lands and distribution of the local populace, as well as the implementation of diverse measures in the expected hotter and drier future.

1. Introduction The escalating loss of topsoil through erosion has been distinguished as a tremendous environmental hassle that can lead to genuine land degradation in drylands (Pimentel et al., 1995; FAO, 2015; Borrelli et al., 2017). The erosion process entails domestic misfortune of exceptional soil particles and significant declines in agricultural productivity, which in flip can threaten the delivery of ecosystem services and socio-economic development (Lal, 2003; Zhao et al., 2009; Du et al., 2016). The consequences of wind erosion show up at the field, landscape, regional, and global scales (FAO, 2015). Ecological projects (e.g. sandification control, grain for green, shelterbelt development) are

a quintessential path to manipulate environment problems such as soil erosion and assist ecosystem adaptation and restoration (Cai et al., 2015; Bryan et al., 2018). Quantifying influences of ecological projects on ecosystem and environments is a basic research for advantageous ecosystem management and regional sustainable development. China is a country that endures from soil erosion problems caused by factors such as overgrazing, agricultural expansion, and forest exploitation to meet food security demands and support economic development, and in response to this problem, a series of sustainability packages massive in scale have been actualized since 1978 (Chen et al., 1994; Bryan et al., 2018). In particular, to make strides and optimize the ecological environment in Beijing, Tianjin, and surrounding zones,

⁎ Corresponding authors at: Key Laboratory of State Forestry Administration on Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China (Y. Zhao). E-mail addresses: [email protected] (Y. Zhao), [email protected] (W. Chi).

https://doi.org/10.1016/j.ecolind.2020.106111 Received 7 June 2019; Received in revised form 9 January 2020; Accepted 14 January 2020 1470-160X/ © 2020 Elsevier Ltd. All rights reserved.

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the Beijing–Tianjin Sand Source Control Project was inaugurated in the early 2000s (Wu et al., 2012). Several on-the-ground movements inclusive of returning cropland to forest, afforestation of barren land, and prohibitions on grazing were embraced in the Beijing–Tianjin Sand Source Region (BTSSR) to control soil erosion from 2001 onward. A more profound understanding of the spatiotemporal patterns of eroded landscapes and ecological and environmental consequences in the BTSSR would consequently be essential for evaluating the direct effects of the ecological projects and the agricultural management activities. Wind-induced erosion is one of most prominent environmental issues in the BTSSR, and it will increase the hazard of sandstorm risks (Zhao et al., 2018). Various models were utilized to retrieve the wind erosion process from small size-plots to gigantic geographical scales (Woodruff and Siddoway, 1965; Fryrear et al., 2001). The Revised Wind Erosion Equation (RWEQ) designed by the United States Department Agriculture has been applied extensively in models to estimate the soil mass transportable by wind over agricultural fields (Fryrear et al., 2001). It is an observational model with climate, soil erodibility, surface roughness, vegetation, and crop residues as the most important elements. With the enhancements in geographical information systems and remote sensing techniques, the RWEQ is turning into an extensively used tool for evaluations of soil wind erosion on multiple spatial and temporal scales (Zobeck et al., 2000; Guo et al., 2013; Chi et al., 2019). Calibration and validation of the model are commonly aided by the 137 Cs tracing technique and wind tunnel experiments (Zhang et al., 2007; Qi et al., 2008; Chi et al., 2018). All of these strategies have given ways to investigate the wind erosion process in eroded landscapes. Ecosystem services, as the bridge connecting characteristic natural ecosystems and human well-being, represent quantifiable indicators for assessing the ecological consequences of land cover changes initiated amid the implementation of sustainability programs (MEA, 2005; Dominati et al., 2010; de Araujo Barbosa et al., 2015; Costanza et al., 2017; Huang et al., 2019). The Millennium Ecosystem Assessment categorized ecosystem services into four classes, namely, provisioning services (e.g., food production), supporting services (e.g., nutrient cycling), regulating services (e.g., water retention), and cultural services (e.g., esthetics). For the BTSSR, it seems obvious that the drier climate in the windy season makes soils prone to erosion, which can result in misfortunes of fine particles and nutrients, as well as diminishments in regional carbon storage, water conservation, air quality, and even human health. However, it is far from clear whether the ecosystem services are indeed showing an improving trend at present times. The answers to such questions are quintessential for comprehensively assessing the ecological projects, distinguishing suitable wind erosion combating measures, and inevitably accomplishing regional sustainable development. This study aimed to reveal the spatiotemporal patterns of soil wind erosion and ecosystem services and examine the impacts of ecological construction projects on wind erosion and ecosystem service modifications in the BTSSR. Specifically, we addressed the following three key research questions. (1) How have wind erosion and key ecosystem services changed from 2000 to 2015? (2) What roles did ecological restoration projects have on the minimization of wind erosion and improvements in ecosystem services? (3) What strategies should be used in future ecological construction projects and agricultural management activities in order to enhance sustainability in the BTSSR?

Fig. 1. Study area and the land use/cover in 2015. Note: ① Typical grassland ② Southern Greater Hinggan Mountains ③ Horqin Sandy Land ④ Water conservation zone of Yanshan mountainous region ⑤ Otindag Sandy Land ⑥ Desert grassland in Ulanqab ⑦ Farming-pastoral ecozone ⑧ Northern Shanxi Mountains ⑨ Ordos Sandy Land ⑩ Agricultural irrigation area of Hetao Plain ⑪ Desert grassland in Bayannur.

counties throughout the six provinces (autonomous regions and municipalities) of Beijing, Tianjin, Hebei, Shanxi, Shaanxi, and Inner Mongolia (Zhao et al., 2018). The local climate zones alter from warm temperate semi-humid zones to temperate semi-humid, temperate semiarid, temperate arid, and eventually temperate extraordinarily arid zones from south to north. Both the annual average temperature and total annual precipitation have a decreasing trend from east to west with ranges of −2 to 13 °C and 250–470 mm, respectively. The grassland areas represent the largest ecological system type in the BTSSR, and we classified these areas into dense grass, moderate grass, and sparse grass according to the vegetative cover. The desert areas, which include gobi, sandy land, bare soil, and bare rock are commonly positioned in the western part of the BTSSR, Otindag Sandy Land, Horqin Sandy Land, and Mu Us Sandy Land. Based on natural conditions, we divided the BTSSR into 11 sub-regions (Fig. 1). According to statistical yearbooks, a total investment of $ 7.95 billion (2015 USD) and a series of sandification manipulate estimations has been made till 2015. Major ecological shelterbelts had been constructed such as shelterbelts on south edge of the Otindag Sandy Land, in the north edge of Yinshan Mountain, in the border area of Hebei and Inner Mongolia, on the eastern margin of the Mu Us Sandy Land (Bryan et al., 2018). Millions of hectare of cropland were transformed to forest, typically positioned in the sub-region of the Otindag Sandy Land, Horqin Sandy Land, Farming-pastoral ecozone, Southern Greater Hinggan Mountains and Northern Shanxi Mountains (Gao et al., 2012a). In addition, performances inclusive of afforestation, aerial seeding, and grassland enclosure were undertaken to reduce desertification and aeolian erosion.

2. Methods 2.1. Study area

2.2. Data The BTSSR (36°50′–46°40′ N, 105°15′–120°50′ E) initially covered a total area of 458,000 km2 including 101,800 km2 of sandy land during the first segment of project execution (2001–2012). The area was subsequently extended to 706,000 km2 including 202,200 km2 of sandy land during the second segment (2013–2022). It encompasses 138

Land use/cover datasets with a scale of 1:100,000 for 2000 and 2015 were obtained from the national China Land Use/Cover Datasets (CLUDs) created by the Chinese Academy of Sciences (Liu et al., 2014, 2018). These data were human–computer interactively interpreted 2

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from Landsat TM/ETM+/OLI and some CCD (charge coupled device) multispectral data from the Huanjing-1 satellite. These data had been originally divided into six classes and 25 sub-classes with an accuracy of more than 90% (Liu et al., 2018). In sequence to clarify the influences of typical land use/cover changes (LUCCs) in the BTSSR, we merged the sub-classes of gobi, sandy land, bare soil, and bare rock into desert ecosystem. The revised land use/cover system included nine ecosystems of sparse grass, moderate grass, dense grass, woodland, cropland, desert, built-up land, water body, and others. Remotely sensed data including the normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), photo synthetically active radiation (PAR), and land surface water index (LSWI) with a spatial resolution of 500 m during 2000–2015 were freely downloaded from the Moderate Resolution Imaging Spectroradiometer (MODIS) website links of the U.S. National Aeronautics and Space Administration (NASA) (http://ladsweb.nascom.nasa.gov/). Meteorological information (e.g., wind speed, sand-dust weather days, daily precipitation, and daily temperature) was obtained from 66 meteorological stations dispersed in and around the BTSSR; this information was shared by the Chinese National Meteorological Information Center (http://data.cma.cn/). The records of sand-dust weather (2000–2013) consisting of blowing sand, floating dust, sandstorm, strong sandstorm, and super-strong sandstorm events were used to evaluate the ecosystem service of air quality regulation. Soil and snow cover data at the 1:1,000,000 scale were freely downloaded from the Environmental and Ecological Science Data Center for West China (http://westdc.westgis.ac.cn). In order to avoid scale-conflicting problems, all of the data were analyzed or resampled to a spatial resolution of 1 km.

Fig. 2. The validation of the soil wind erosion modulus (SWEM).

(1)

Natural vegetation including grassland, forests and desert comprise of approximately 76% of the total area. Land degradation and sandstorm break are the foremost genuine eco-environmental problems of this semi-arid region (Li et al., 2015). In order to evaluate benefits individuals get from ecosystems earlier than and after the projects implementation, we selected three key ecosystem services along with water retention, aboveground carbon storage, and air quality regulation. These three ecosystem services have been expressed by using the net primary productivity (NPP), water retention quantity, and annual no sand-dust days, respectively (Zhao and Running, 2010; Zhao et al., 2018; Zhang et al., 2019). The NPP was retrieved by employing a vegetation photosynthesis model (VPM). The VPM is a light use efficiency model established over an assortment of ecological ecosystems at globally-distributed flux towers (Xiao et al., 2004; Zhang et al., 2016). The study on the Loess Plateau, China, which is positioned in the western of the BTSSR, indicated that VPM was an effective method for modeling NPP (Liu et al., 2017). It can be generally expressed as following:

(2)

GPP = εg × FPAR chl × PAR

(4)

(3)

NPP = GPP − Ra

(5)

2.3. Evaluation of the aeolian erosion process and ecosystem services 2.3.1. Quantification of the soil wind erosion The aeolian processes, which were quantified as the annual soil wind erosion modulus (SWEM), were mapped by using the RWEQ model. This model can be expressed as follows (Fryrear et al., 2001):

SWEQ =

x 2 2x Qmax e−( s ) s2

Qmax = 109.8(WF × EF × SCF × K '× COG ) s = 150.71(WF × EF × SCF × K '×

COG )−0.3711

where x is the distance from the upwind side of the field; Qmax is the maximum transport capacity; s is the critical field length; WF is the weather factor calculated by using data on precipitation, average temperature, snow cover, and wind velocity; EF and SCF represent the soil erodible fraction and soil crust factor, respectively, and these rely on the contents of sand, silt, clay, calcium carbonate, and organic matter; K’ is the soil roughness; and COG is the combined vegetation factor. The key parameters along with vegetation cover, surface roughness, soil erodibility, and soil crust were localized with field samplings (Chi et al., 2019). We additionally used 137Cs tracing technique to validate the accuracy of the SWEM data retrieved from RWEQ. A total of 40 sampling points were selected across the study area from 2000 to 2014 (Fig. 1). For each examining plot, soil samples were collected as subsamples with 2 cm increment from 0 to 8 cm depth and 4 cm increment from 8 to 24 cm depth. The soil samples were tested by gamma-ray spectrometry equipped with hyperpure germanium (HPGe) detector to obtain the 137Cs activities and calculate the actual SWEM. We compared the 137Cs measurements with the corresponded SWEM modeled from the RWEQ and found that they were significantly correlated with each other (p < 0.01) (Fig. 2).

Where GPP is the gross primary productivity; PAR is the photosynthetically active radiation; FPARchl is the faction of PAR absorbed by the plant canopy; εg is the rate of transformation of FPAR into organic matter; and Ra is the autotrophic respiration. Remotely sensed data including MODIS EVI and LSWI have been used for localizing the parameters of the model in accordance with the strategies portrayed in Chen et al. (2014). The water retention alludes to the water remaining in the soil within a certain period (Ouyang et al., 2016). It relies on the soil type, soil texture, soil structure, stable organic matter. We utilized the extensively used equation (Eq. (6)) to express the water retention quantity (Yang et al., 2015a,b). This model was also affirmed to viably assess this services in the region with comparable natural condition (Zhang et al., 2017).

WRm, i = Ai × Pi × Ki × Rm, i

(6)

where WRm,i is the water retention for pixel i in land use/cover type m; Ai is the area of pixel i; Pi is the annual precipitation for pixel i; Ki is the proportion of runoff of the total rainfall, which we defined as 0.6 according to related studies; and Rm,i is the coefficient of land use/cover type m in pixel i, where values were 12%, 20%, and 11% for cropland, woodland, and grassland, respectively (Zhang et al., 2017). The indicator of annual no sand-dust days was expressed by way of the usage 365 days minus the sand-dust weather days. Larger values

2.3.2. Evaluation of the key ecosystem services The BTSSR is section of the ecological barrier in northern China. 3

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signify higher air quality regulation services. 2.4. Quantifying the environmental and ecological consequences of ecological projects The wind erosion and ecosystem services, which were represented by the environmental and ecological variables, can be influenced with the aid of both climate factors and human activities such as ecological projects. The LUCCs have been assumed to replicate the direct ecological project effects. In this manner, we focused on the influences of LUCCs on wind erosion and ecosystem services in this study. Firstly, we modeled the annual SWEM and ecosystem services from 2000 to 2015 employing Eqs. (1)–(6). In sequence to debilitate the influences of climate, we first averaged the SWEM and ecosystem services amongst the 16 years, assuming that the SWEM and ecosystem services were assessed within the same climate condition. At that point, the unaltered land use/cover region were extracted essentially based on the land use/cover statistics in 2000, 2010, and 2015. By overlaying the averaged SWEM/ecosystem services map with the unaltered land use/ cover, we had been able to statistically analyze the average value for each land use/cover in each sub-zone. Consequently, the SWEM/ecosystem service alters influenced by LUCCs in each sub-zone were assessed as follows (Chi et al., 2019):

Ei =

j

∑k =1 Ai,k

× (ei, m − ei, n )

(7)

where Ei refers to the net SWEM/ecosystem service change in sub-region i; j refers to the amount of change types; Ai,k refers to the LUCC region of the kth change type in sub-zone i; and ei,m and ei,n refer to the average value with land use/cover m (the end year) and n (the start year) for the duration of the analysis in sub-zone i, respectively. Because the BTSSR covered a large area, all statistics were conducted in the scale of sub-region. All the spatial analyses were conducted in ArcGIS 10, and the statistical analyses were carried out with SPSS for Windows. 3. Results 3.1. Land use/cover changes after project implementation The characteristics of LUCC in the BTSSR varied spatially and temporally. From 2000 to 2010, there were approximately 271 km2/a of cropland and 177 km2/a of desert that were returned to grassland/woodland, and 539 km2/a of grassland that were strengthened after project implementation (Table 1). The returned croplands were mainly located in the farming-pastoral ecozone (79 km2/a), Ordos Sandy Land (65 km2/a), northern Shanxi Mountains (50 km2/a), typical grassland

Fig. 3. Distribution of dominant Land use/cover conversion during 2000–2010, 2010–2015. Note: The name of each sub-region is shown in Fig. 1.

Table 1 The land use/cover changes during ecological project phase from 2000 to 2015. Land use/cover change

2000–2010 km2/a

2010–2015 km2/a

Cropland reclamation

From woodland/grassland to cropland

251

130

Cropland return

From cropland to woodland/grassland

271

87

Vegetation degradation

From From From From Sum

grassland/woodland to desert dense grass to moderate/sparse grass/desert moderate grass to sparse grass/desert sparse grass to desert

244 210 272 139 865

12 301 231 7 551

Vegetation improvement

From From From From Sum

desert to grassland/woodland sparse grass to moderate/dense grass/woodland moderate grass to dense grass/woodland dense grass to woodland

177 277 234 28 716

221 257 575 4 1057

4

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(20 km2/a), and Horqin Sandy Land (16 km2/a). The desert vegetation converted to woodland or grassland was mainly positioned in Otindag Sandy Land (50 km2/a), Ordos Sandy Land (34 km2/a), and desert grassland in Ulanqab (27 km2/a) and in Bayannur (17 km2/a). The strengthened vegetation areas including lands where there was a transformation from sparse grass and moderate grass to dense grass or woodland areas were mainly positioned in Ordos Sandy Land (168 km2/a), desert grassland in Ulanqab (111 km2/a), Otindag Sandy Land (71 km2/a), and typical grassland (64 km2/a) (Fig. 3). From 2010 to 2015, the annual returned cropland quantity diminished to 87 km2/a, and these sites were mainly positioned in Otindag Sandy Land (33 km2/a) and the farming-pastoral ecozone (32 km2/a). In the interim, the vegetation enhancement area expanded to 1057 km2/a, of which the modification from moderate grass to dense grass/woodland accounted for 61% (575 km2/a). The strengthened vegetation area during this period was mainly positioned in the western part of Ordos Sandy Land (227 km2/a), typical grassland (192 km2/a), desert grassland in Ulanqab (184 km2/a), and Otindag Sandy Land (135 km2/a). 3.2. Spatiotemporal patterns of soil wind erosion The soil wind erosion was much more severe in the west and north than that in the eastern part of the BTSSR. In 2015, approximately 4.27 × 104 km2 (6.02% of the study area) experienced “severe erosion” with soil losses larger than 5 kg/(m2·a). In terms of the sub-region, the SWEM of desert grassland in Bayannur, the agricultural irrigation region of Hetao Plain, desert grassland in Ulanqab, Otindag Sand Land, and Ordos Sand Land was 5.01, 4.33, 2.21, 1.70, and 1.21 kg/(m2·a) higher than that of other regions (Fig. 4a). The SWEM showed a frequent diminshing trend after the ecological projects were implemented in 2000 (Fig. 4b). Before 2000, the average SWEQ in the BTSSR was once 2.15 kg/(m2·a), and it dropped to 1.55 kg/(m2·a) amid 2000–2015. The value remained steady from 2003 to onward. The changes in magnitude was substantially distinctive

Fig. 5. Spatiotemporal patterns of ecosystem services in the Beijing-Tianjin Sand Source Region, China (2000–2015). Note: (a), (c), (e) refer to the average NPP, water retention and no-sand-dust weather days, respectively. (b), (d), (f) refer to the change trend of the above ecosystem services. Note: The name of each sub-region is shown in Fig. 1.

among the diverse sub-regions. The diminishes in quantity have been large in the agricultural irrigation region of Hetao Plain, desert grassland in Bayannur, and desert grassland in Ulanqab with values of 1.36, 1.12, and 1.11 kg/(m2·a), respectively (Fig. 4c). The change percentages were much greater in other sub-regions including Horqin Sandy Land, desert grassland in Ulanqab, and Ordos Sandy Land, where values decreased by at least 25% (Fig. 4c). 3.3. Spatiotemporal patterns of ecosystem services All three ecosystem services displayed generally enhancing trends, be that as it may, spatial contrasts were apparent. The aboveground NPP was more prominent in the east and diminished in the west (Fig. 5a). The aboveground NPP in the sub-region named water conservation zone of the Yanshan mountainous region was the highest with a value of 463 g C/(m2·a), and that in the desert grassland in Ulanqua and in Bayannur was the least with values of 52 and 60 g C/(m2·a), respectively. The regional average NPP significantly increased from 223 g C/(m2·a) in 2000 to 257 g C/(m2·a) in 2015 with the highest value of 266 g C/(m2·a) in 2013 and an annual increment rate of 1.78 g C/(m2·a) (Fig. 5b). The increasing rate was much higher in the water conservation zone of the Yanshan mountainous region (slope = 5.22, p < 0.001), northern Shanxi Mountains (slope = 3.98, p < 0.01), and Ordos Sandy Land (slope = 1.42, p < 0.01). However, the aboveground NPP in other sub-regions did not appear a significant change trend. The water retention service showed a comparative spatial pattern (Fig. 5c). The forest overwhelming regions including the water

Fig. 4. The spatiotemporal pattern of soil wind erosion modulus (SWEM) in the Beijing-Tianjin Sand Source Region, China (a) the spatial pattern of SWEM in 2015; (b) the variation of regional average SWEM from 1990 to 2015; (c) the changes of SWEM in different sub-regions. Note: The name of each sub-region is shown in Fig. 1. 5

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conservation zone of the Yanshan mountainous region, northern Shanxi Mountains, and southern Greater Hinggan Mountains had higher water retention services with values of 577, 349, and 339 thousand m3/km2, respectively. The regional average water retention increased from 172 thousand m3/km2 in 2000 to 209 thousand m3/km2 in 2015 with an annual increasing rate of 2.28 thousand m3/km2 (Fig. 5d). Water retention in most sub-regions expect for in the typical grassland and farming-pastoral ecozone showed a significant increasing rate. Sand-dust weather occurred more frequently in the western and northern areas of the BTSSR (Fig. 5e). During 2000–2015, the days without sand-dust weather showed a significant increasing trend (Fig. 5f). That in Otindag Sandy Land, desert grassland in Ulanqab, and Ordos Sandy Land showed a more significant increasing trend with annual increases of more than 1 day. 4. Discussion 4.1. Ecological projects had positive impacts on wind erosion in the BTSSR The overall Beijing–Tianjin Sand Source Control Project involved numerous tasks inclusive of the strengthening of vegetation protection and desertified land management, forest plantation enhancements, improvements in the satisfactory and scope of existing vegetation. The land use/cover data and their correlation with the surface roughness can serve as an instrument for manipulate of the wind field and sanddust emission, transport, and deposition processes. The desert experienced the foremost severe erosion because of the drier soil and large quantity of exposed land. Grasslands with distinctive grazing intensities or vegetative covers are recognized to have distinct velocity profiles and threshold wind velocities (Sun et al., 2013). Studies have observed that wind erosion values are diminished linearly or exponentially with expanding grassland conditions consisting of coverage, plant density, canopy height, aboveground biomass, and species richness (Li et al., 2005; Zhao et al., 2017). Soils of croplands with lower residue covers are at higher risk of experiencing wind erosion, especially during the unused period of the rotation due to the fact that tillage-based summer unused land has degraded aggregates and minimal biomass cover (Sharratt et al., 2012, 2015). The short-term cultivated soils contain low levels of very fine particles and are 18–38% depleted in organic C, total N, and total P in the top cultivated layer compared to the adjoining grazed grassland (Su et al., 2004). Woody plants with excessive density generally grant higher protection for the soil due to the fact of their potential to disrupt air flow, especially shrubs with low hanging branches. Importantly, the consequences of sparse vegetation on interference flow and erosion processes have been broadly discussed in preceding studies in relation to the impacts on aeolian sediment transport (Leenders et al., 2007; Breshears et al., 2009). In our research, we discovered that LUCCs during the period of ecological project implementation in the BTSSR caused a reduction in soil wind erosion, and the reduction was mainly caused by the land cover modifications from desert to sparse grass or moderate grass (Fig. 6). From 2000 to 2015, the average SWEM of desert (3.72 kg/ (m2·a)) was much higher than that of sparse grass (3.64 kg/(m2·a)), moderate grass (1.45 kg/(m2·a)), cropland (1.16 kg/(m2·a)), dense grass (0.68 kg/(m2·a)), and forest (0.57 kg/(m2·a)). The ecological project implementation prompted SWEM diminish amounting to 3.77 million tons amid 2000–2015, and the amount was equal to one-seventh of the annual total SWEM in Horqin Sandy Land or half of that in Northern Shanxi Mountains. Approximately 70% of diminish was prompted by the modification from desert to sparse grass. For the sub-regions, desert grassland in Bayannur, Ordos Sandy Land, and Otindag Sandy Land were hot spots of wind erosion control triggered via the ecological projects. The wind erosion reductions accomplished were approximately 1.36, 1.11, and 0.71 million tons in these sub-regions, respectively. Additionally, the reductions prompted by the land cover transformation from desert to sparse grass were as high as 70%, 68%, and

Fig. 6. The total soil wind erosion changes caused by LUCCs in the BeijingTianjin Sand Source Region, China (2000–2015). Note: The name of each subregion is shown in Fig. 1.

97% of the corresponding sub-region total, respectively. That caused by the shift from desert to moderate grass accounted for 25%, 12%, and 1%, respectively. 4.2. Ecosystem services were generally improved with the LUCCs and decreases in wind erosion Changes in land use/cover have markedly affected ecosystem services worldwide (van Oudenhoven et al., 2012; Pullanikkatil et al., 2016; Song and Deng, 2017). Costanza et al. (1997, 2014) furnished and afterward upgraded the worldwide values of ecosystem services for distinctive land covers, which served as an inspiration for associated researches. The biomass carbon storage in China’s grasslands was assessed to be 215.8–348.1 g C/m2, and that of forest was assessed to be 4258–4945 g C/m2 (Fang et al., 2001, 2010). The water retention function was observed to be substantially distinctive among various land covers including cropland, grassland, forest, and bare land (Zhang et al., 2017). Studies have additionally discussed the impacts of aeolian processes on ecosystem services mediated through altering soil functions in the affected areas (Zhao et al., 2017). Sand-sized particles of the soil hop along the surface with wind, and these developments contribute to the building of sand dunes and barrier-line drifts on domestic scales, and meanwhile, usually one of the essential mechanisms for dust discharge. Dust manufactured by wind erosion is a major source of atmospheric aerosols influencing the air quality in populated regions adjacent to dust sources. A deficiency of exceptional patches also can contribute to moderate land degradation due to the fact of the decreases in prosperous nutrient and organic matter resources (Shao, 2008). Long-term wind erosion can lead to soils with minimal or no formation capacity, which are thoroughly absorptive and retain litter or no water (Han et al., 2012). Hence, the series of tasks carried out in the Beijing–Tianjin Sand Source Control Project ought to have led to improvements in ecosystem services in theory. All three ecosystem services analyzed in this research usually extended with the LUCCs and diminish in the SWEM. For the BTSSR, the water retention increased in total by 404.3 million m3 from 2000 to 2015, of which 168.7 million m3 of the increase could be attributed to the transformation from cropland to woodland/grassland, whereas approximately 235.6 million m3 was from vegetation recovery during the transition from desert to woodland/grassland. In respect to the subregions, the cropland returns within the sub-region of the northern 6

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Otindag Sandy Land (Fig. 7). Within the three sub-region, cropland returned to grassland accounted for 65.62%, 59.80% and 99.17%, respectively. In spite of the fact that the aboveground carbon storage density was once in a while higher in the croplands than that in the grasslands, specifically for those with irrigation, the carbon storage in the soil and underground biomass was absolutely the highest for natural vegetation such as steppe, shrubs, and steppe-desert (Ni, 2002). In this manner, the total carbon storage would be an increase throughout the cropland returns in a long-term and comprehensive perspective. The patterns of carbon sequestration ought to be further explored. 4.3. The ecological projects should be consolidated and protected Previous studies have affirmed the beneficial impacts of China’s national conservation policies on safeguarding and restoring natural resources (Ouyang et al., 2016; Bryan et al., 2018). Within the BTSSR, more than half of the region has experienced significant vegetation enhancements amid the first decade (Wu et al., 2013; Li et al., 2015; Yang et al., 2015a,b). Afforestation enhanced the physical properties of the top layer of soil at the early stage (Zeng et al., 2014). But that as it may, there had been still large areas of degradation subjected to huge pressures from overgrazing and preposterous cropland reclamation as indicated in Table 1 and associated studies (Wu et al., 2013; Yang et al., 2015a,b). In addition, some recuperated regions were at a hazard of damage once more due to the rare management after project implementation. In spite of the fact that the decline in wind speed was recognized as the dominant factor for the wind erosion diminishes, our study confirmed that afforestation, aerial seeding, grassland enclosures, and grain for green projects had actual beneficial impacts on the protection of the soil surface and increases in the threshold wind velocity. Be that as it may, there were still huge areas of desertification detected, especially in the farming-pastoral ecozone. Moreover, the BTSSR will experience a significant future warming, however the precipitation there is a blend of positive and negative alters in summer and winter (Gao et al., 2012b). This climate change trend is destructive to wind erosion control. With aim of climate change adaption and fostering further enhancements, we offer the following recommendations for future ecological restoration in the BTSSR. First of all, differential measures will be required to control the wind erosion and enhance ecosystem services. In term of the flow and semiflow sand dunes, which are mainly distributed in Otindag Sandy Land and Ordos Sandy Land, engineering measures (e.g., straw checkerboard barriers) coupled with biological measures (e.g., afforestation, aerial seeding), as well as grazing prohibitions should be adopted. A 10–20 cm barrier could reduce the intensity of sand flux of the sand dune surface by as much as 95% and help to build a steady environment to extend the seeding survival rate (Qiu et al., 2004). Studies in Horqin region concluded that shrub planting with straw checkerboard barriers or/and grazing prohibition not only promoted the coverage and diversity of plant species, but also enhanced the soil functions such as total carbon and total nitrogen (Miao et al., 2015). In terms of the fixed sand dunes, livestock grazing ought to be strictly controlled and mechanical disturbances such as those from vehicle rolling ought to be dodged. Meanwhile, it will be imperative for the shrubs (e.g., Caragana korshinskii Kom., Salix cheilophila Schneid.) to be pruned at an interval of 3–4 years to ensure their regeneration and sustainability for grazing. In terms of the cropland disseminated in the southeastern part of the BTSSR, those lands with severe desertification ought to be returned to woodland or grassland. The adoption of conservation tillage and windbreaks might be encouraged in local agriculture practices. Crop residue removal less than 75% of the original height could effectively control the wind erosion (He et al., 2018). Tree windbreaks were also affirmed to have positively influence on crop growth by improving micrometeorology conditions (Iwasaki et al., 2019). Second, scientific management of the degraded land and farmers and herders have to be considered, as well as the need to implement

Fig. 7. The ecosystem services changes caused by LUCCs in the Beijing-Tianjin Sand Source Region, China (2000–2015) (a) aboveground carbon storage (b) water retention.

Shanxi Mountains and farming-pastoral ecozone contributed more to the water retention increases than those in the other sub-regions, and these values amounted to 73.72 million m3 (43.63% of the total water retention increase due to cropland return) and 59.24 million m3 (36.06%), respectively. Moreover, the vegetation recovery in the Ordos Sandy Land (123.32 million m3, 52.34% of the total water retention increase due to transformation from desert to woodland/grassland) contributed the foremost to the growth of the water retention, followed by that in Otindag Sandy Land (30.28 million m3, 12.86%) (Fig. 7). The aboveground NPP did not exhibit a steady increase, of which cropland returns led to a total diminish of 445.40 billion g C in the aboveground biomass and transformation from desert to woodland/ grassland produced an increase of 164.29 billion g C storage in aboveground biomass. As it were two sub-region named Water conservation zone of Yanshan mountainous and Northern Shanxi Mountains confirmed an above ground NPP increase, due to the fact the percentage of croplands returned to forest was 98.19% and 60.47, respectively. Whereas in other sub-regions, most croplands have been returned to grasslands, leading to a massive reduction in aboveground NPP, especially in the farming-pastoral ecozone, Ordos Sandy Land, and 7

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distinctive measures in a hotter and drier future. Our studies confirmed that most wind erosion reductions during the project period had been precipitated by modifications from desert to sparse grass or moderate grass, which nevertheless characterize fragile ecosystems. Management of grazing regimes, cultivation types, etc., may effectively be utilized to extend biodiversity and ecosystem services consisting of the forage amount, soil nutrients, agricultural productivity, and so forth (Marriott et al., 2010). In order to keep away from re-degradation, the following questions will have to be replied. How long until the restored grassland can be reused for grazing? What density is appropriate for forests in the desertified region? How many grasslands could assist sheep/cows according to distinct degradation intensities? How to stability environment protection and living prerequisites for peasants and herders while achieving a goal of zero poverty. All of these research questions with need to be resolved with further and deeper studies aided by field surveys, site experiments, and remotely sensed data.

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5. Conclusions In the BTSSR, the soil wind erosion diminished and the ecosystem services consisting of carbon storage, water retention and air quality regulation increased with the ecological projects implementing since 2000. The transformation from cropland to woodland/grassland and from desert or sparse grass to denser grass driven to a diminishment of SWEM approximate 3.77 million tons amid the 16 years. Meanwhile, the increase of water retention during these LUCCs achieved by 404.3 million m3. In spite of the fact that the cropland returning would lead to a reduction of above-ground carbon storage in some extent, the huge potential of under-ground carbon storage of grass would fill this lost. According to these findings we endorse differential measures and scientific management of the degraded land and farmers and herders, in order to control regional soil wind erosion and enhance ecosystem services in the drier and hotter future. Author contributions Yuanyuan Zhao, Wenfeng Chi, Wenhui Kuang designed the research. Yuanyuan Zhao and Wenfeng Chi analyzed the data. Yuanyuan Zhao wrote the manuscript. All authors discussed results and commented on the manuscript. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgments We thank Weiwei She, Yingbo Qu and Yanhui Lei for providing technical supports. This work was supported by the National Key Research and Development Program of China (2016YFC0500802), National Natural Science Foundation of Inner Mongolia, China (2017BS0402), and the National Natural Science Foundation of China (31600581 & 41971130). References de Araujo Barbosa, C.C., Atkinson, P.M., Dearing, J.A., 2015. Remote sensing of ecosystem services: a systematic review. Ecol. Indic. 52, 430–443. https://doi.org/10. 1016/j.ecolind.2015.01.007. Borrelli, P., Robinson, D.A., Fleischer, L.R., Lugato, E., Ballabio, C., Alewell, C., Meusburger, K., Modugno, S., Schutt, B., Ferro, V., Bagarello, V., Oost, K.V., Montanarella, L., Panagos, P., 2017. An assessment of the global impact of 21st century land use change on soil erosion. Nat. Commun. 8, 2013. https://doi.org/10. 1038/s41467-017-02142-7. Breshears, D.D., Whicker, J.J., Zou, C.B., Field, J.P., Allen, C.D., 2009. A conceptual framework for dryland aeolian sediment transport along the grassland-forest

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