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Journal of Geographical Sciences >

2017 , Vol. 27 >Issue 7: 786 - 800

DOI: https://doi.org/10.1007/s11442-017-1406-4

Orginal Article

Crop cover reconstruction and its effects on sediment retention in the Tibetan Plateau for 1900-2000

  • LI Shicheng , 1, 2, 3, * ,
  • WANG Zhaofeng , 1, * ,
  • ZHANG Yili , 1, 2, 4
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  • 1. Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research (IGSNRR), CAS, Beijing 100101, China
  • 2. University of Chinese Academy of Sciences, Beijing 100101, China
  • 3. School of Public Administration, China University of Geosciences, Wuhan 430074, China
  • 4. CAS Center for Excellence in Tibetan Plateau Earth Sciences, Beijing 100101, China

Author: Li Shicheng (1989-), PhD, specialized in historical land use and cover change reconstruction and its ecological effects assessment. E-mail: ;

*Corresponding author: Zhang Yili and Wang Zhaofeng. E-mail: ;

Received date: 2016-11-05

  Accepted date: 2017-02-06

  Online published: 2017-07-10

Supported by

Strategic Priority Research Program of the Chinese Academy of Sciences, No.XDB03030500

National Natural Science Foundation of China, No.41371120

The Key Foundation Project of Basic Work of the Ministry of Science and Technology of China, No.2012FY111400

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Journal of Geographical Sciences, All Rights Reserved
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Abstract

Geographically explicit historical land use and land cover datasets are increasingly required in studies of climatic and ecological effects of human activities. In this study, using historical population data as a proxy, the provincial cropland areas of Qinghai province and the Tibet Autonomous Region (TAR) for 1900, 1930, and 1950 were estimated. The cropland areas of Qinghai and the TAR for 1980 and 2000 were obtained from published statistical data with revisions. Using a land suitability for cultivation model, the provincial cropland areas for the 20th century were converted into crop cover datasets with a resolution of 1 × 1 km. Finally, changes of sediment retention due to crop cover change were assessed using the sediment delivery ratio module of the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model (version 3.3.1). There were two main results. (1) For 1950-1980 the fractional cropland area increased from 0.32% to 0.48% and land use clearly intensified in the Tibetan Plateau (TP), especially in the Yellow River-Huangshui River Valley (YHRV) and the midstream of the Yarlung Zangbo River and its two tributaries valley (YRTT). For other periods of the 20th century, stability was the main trend. (2) For 1950-1980, sediment export increased rapidly in the Minhe autonomous county of the YHRV, and in the Nianchu River and Lhasa River basins of the YRTT, which means that sediment retention clearly decreased in these regions over this period. The results of this assessment provide scientific support for conservation planning, development planning, or restoration activities.

Key words： cropland reconstruction; ecosystem services; InVEST model; the 20th century; Qinghai province; the Tibet Autonomous Region

Cite this article

LI Shicheng , WANG Zhaofeng , ZHANG Yili . Crop cover reconstruction and its effects on sediment retention in the Tibetan Plateau for 1900-2000[J]. Journal of Geographical Sciences, 2017 , 27(7) : 786 -800 . DOI: 10.1007/s11442-017-1406-4

1 Introduction

Human land use activities have dramatically altered the Earth’s surface, with serious consequences for environmental systems (Ellis et al., 2013; Foley et al., 2005; Future Earth, 2014). Many studies have undertaken historical land use and cover change (LUCC) reconstructions to consider historical LUCC effects (De Brue and Verstraeten, 2014; Gaillard et al., 2010; Sturck et al., 2015; Zorrilla-Miras et al., 2014). An understanding of anthropogenic land use activities and their ecological effects over long time periods will enable us to better manage human-nature relationships and provide governments with more scientific support when deciding on sustainable development policies.
In the historical LUCC reconstruction field, there are many representative historical land use datasets, including the History Database of the Global Environment (HYDE) (Klein Goldewijk et al., 2011), global land use dataset of the Center for Sustainability and the Global Environment (SAGE) (Ramankutty and Foley, 1999), and Kaplan and Krumhardt (KK10) dataset (Kaplan et al., 2011). These datasets have been widely used to assess the effects of land use change on climate change and ecosystem services over long time periods (Jantz et al., 2015; Simmons and Matthews, 2016; Smith et al., 2016). The reconstruction methods used to develop these datasets have been followed and revised by many regional studies (Dias et al., 2016; He et al., 2015; Jin et al., 2016; Leite et al., 2012; Li et al., 2016; Yang et al., 2016).
Although these studies have made substantial contributions to our understanding, there is still much to learn (Klein Goldewijk and Verburg, 2013; Miao et al., 2013; Miao et al., 2016). For example, the spatial and temporal resolutions of these datasets are coarse, which reduce their potential for application in the assessment of ecological effects (De Brue and Verstraeten, 2014). Some studies have indicated that these datasets have captured the general patterns of cropland change over history, and should only be used for continental-to-global scale analysis and modeling (He et al., 2013; Li et al., 2010; Zhang et al., 2013). As a result, many regional to local scale reconstructions have been conducted (Wei et al., 2016; Ye et al., 2009; Ye et al., 2015).
As the highest and most extensive highland in the world, the Tibetan Plateau (TP) has a distinct natural environment (Zhang et al., 2002), with a global impact. Many major Asian rivers originate from this region, providing water for nearly 40% of the world’s population. It is also a global hotspot for biodiversity conservation. It is widely acknowledged that environmental conditions in the region have changed significantly in the last century due to climate change and human activities, including a loss of biodiversity (Newbold et al., 2015), grassland degradation (Lehnert et al., 2016; Sun et al., 2012), and a decrease in water supply (Pan et al., 2015). Consequently, environmental changes in the TP have generated great public and scientific interest in recent years. However, most land use and cover related studies in the TP only cover the period since the 1970s when satellite-based data is available (Cui and Graf, 2009). There are few historical reconstruction studies because historical records are difficult to obtain and interpret, with only a few initial studies available (Li et al., 2015; Luo et al., 2014; Ryavec, 2001; Wang et al., 2015). There have also been few studies concerning the effects of historical crop cover changes on ecosystem services in this remote region of China.
Therefore, the objectives of this study were to reconstruct crop cover over the 20th century and assess the effects of crop cover change on sediment retention services in the TP. Based on historical population data and cropland statistical data, the provincial cropland area of Qinghai and the Tibet Autonomous Region (TAR) for 1900, 1930, 1950, 1980, and 2000 was estimated, and then allocated into 1 × 1 km grid cells using a land suitability for cultivation model. We then used the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model to assess the effects of crop cover change on sediment retention services for 1900-2000. Finally, we considered the uncertainties and prospects of this study.

2 Study area

Because population and cropland area data for the TP are political region-based data, so the administrative-level TP, i.e., Qinghai province and the TAR, are selected as the study area (Figure 1). The land area of the two provinces is 122.84 × 104 and 72.10 × 104 km2, respectively. Most regions of the two provinces are covered by alpine meadows and alpine grassland ecosystems. There is little cropland area, which is mainly distributed in the Yellow River-Huangshui River Valley (YHRV) of Qinghai province, and the midstream of the Yarlung Zangbo River and its two tributaries valley (YRTT: the two tributaries are the Lhasa and the Nianchu rivers) of the TAR. Based on China’s Land-Use/cover Datasets (CLUDs) in 2010, the cropland area of the two provinces was determined to be about 0.30% and 0.85% respectively (Liu et al., 2014b).
Figure 1 Location of the study area. The two red polygons are the main crop distribution areas in the Tibetan Plateau (TP). The right-top polygon is the Yellow-Huangshui River valley (YHRV), and the middle-bottom polygon is the midstream Yarlung Zangbo River and its two tributaries valley in Tibet Autonomous Region (YRTT).
In this study, following the method of Li et al. (2015), the crop cover of the TP for 1900, 1930, 1950, 1980, and 2000 was reconstructed and their effects on sediment retention services were assessed based on the InVEST model, by focusing on two typical regions: the YHRV and YRTT.

3 Data and methods

3.1 Estimation of cropland area

Utilizing the method of Li et al. (2015), the cropland area of Qinghai province and the TAR over the 20th century was estimated. In brief, for 1900, 1930, and 1950, the cropland area was estimated based on the assumption that the per capita cropland area remained constant for the first half of the 20th century. The per capita cropland area of 1953 was determined from cropland area records and a yield inventory (Feng et al., 2005), and historical population data were obtained from Cao and Ge (2001) (Table 1). For 1980, it is believed that the statistical cropland area data was underestimated (Frolking et al., 2002; Liu et al., 2005), and therefore revision was done employing grain yields (Feng et al., 2005). For 2000, existing statistical cropland area data was used.
Table 1 Population of Qinghai province and the Tibet Autonomous Region (TAR) for 1880, 1910, and 1953 (Cao and Ge, 2001) (104 person)
Province name 1880 1910 1953
Qinghai province 32.9 34.4 36.7
Tibet Autonomous Region 127 131.2 137.4

3.2 Crop cover reconstruction

The provincial cropland area cannot be used directly by ecological models. Therefore, the provincial cropland areas were converted into geographically explicit cropland datasets following the model developed by Li et al. (2015). In general, the model consists of the following three steps.
(1) Normalization of land suitability for cultivation factors, including altitude and slope, using Eqs. (1) and (2):
` ${D}'\left( i,{{k}_{n}} \right)=\frac{\text{Max}\left[ D\left( i,{{k}_{n}} \right) \right]-D\left( i,{{k}_{n}} \right)}{\text{Max}\left[ D\left( i,{{k}_{n}} \right) \right]}$ (1)
${S}'\left( i,{{k}_{n}} \right)=\frac{\text{Max}\left[ S\left( i,{{k}_{n}} \right) \right]-S\left( i,{{k}_{n}} \right)}{\text{Max}\left[ S\left( i,{{k}_{n}} \right) \right]}$ (2)
where D′(i, kn) represents the altitude-related cultivation suitability of grid i in province kn, D(i, kn) represents the altitude of grid i in province kn, S′(i, kn) represents slope-related cultivation suitability of gird i in province kn, and S(i, kn) represents the slope of grid i in province kn.
(2) Calculation of the suitability of land for cultivation, using Eq. (3):
${{W}_{suit}}(i,{{k}_{n}})={D}'(i,{{k}_{n}})\times {S}'(i,{{k}_{n}})\times {{W}_{crop}}(i,{{k}_{n}})$ (3)
where Wsuit(i, kn) denotes the suitability of land for cultivation of grid i in province kn, and Wcrop(i, kn) denotes the potential maximum extent of cropland, which was acquired using satellite-based crop cover data (Liu et al., 2014b).
(3) Allocation of the provincial cropland area into 1 × 1 km grids, using Eq. (4):
$Crop\left( i,t \right)={area\left( {{k}_{n}},t \right)\times \frac{{{W}_{suit}}(i,{{k}_{n}})}{\sum\limits_{i}^{{{k}_{n}}}{{{W}_{suit}}(i,{{k}_{n}})}}}/{gridarea\left( i \right)}\;$ (4)
where Crop(i, t) is the cropland area of grid i in year t, area(kn, t) is the cropland area of province kn in year t, and gridarea(i) is the land area of each grid.

3.3 Assessment of changes in sediment retention

The crop cover datasets were used to assess the effects of crop cover change on changes in sediment retention services, focusing on the YHRV and YRTT areas. The InVEST model, which was developed by the Natural Capital Project to quantify and map the values of ecosystem services, was used in this study (Sharp et al., 2015).
The InVEST model is geographically explicit, using maps as inputs and producing maps as outputs. It returns results in either biophysical or economic terms. Due to its openness, it has been used widely by many studies and great results have been obtained (Fu et al., 2014; Hamel et al., 2015; Nelson et al., 2009; Posner et al., 2016; Su and Fu, 2013).
InVEST usually utilizes a production function to quantify and value ecosystem services. In this study, the InVEST model (version 3.3.1) sediment delivery ratio module was used to assess the influence of crop cover change on sediment retention services. Erosion and sediment retention are natural processes that govern the sediment concentration in streams. Sediment dynamics are mainly determined by climate conditions (especially the rainfall intensity), soil properties, topography, land cover, and human activities. Changes in land use and land management practices may dramatically modify the amount of sediment running off a catchment. The sediment delivery module is a geographically explicit model working at the spatial resolution of the input digital elevation model (DEM). For each cell, the model first computes the amount of eroded sediment, then the sediment delivery ratio (SDR), which is the proportion of soil loss actually reaching the catchment outlet.
The amount of annual soil loss for pixel i is given by the revised universal soil loss equation:
$usl{{e}_{i}}={{R}_{i}}\cdot {{K}_{i}}\cdot L{{S}_{i}}\cdot {{C}_{i}}\cdot {{P}_{i}}$ (5)
where uslei denotes the amount of annual soil loss (ton•ha-1 yr-1), Ri denotes the rainfall erosivity (MJ•mm(ha•hr)-1), Ki denotes the soil erodibility (ton•ha•hr(MJ•ha•mm)-1), LSi denotes the slope length-gradient factor, Ci denotes the crop-management factor, and Pi denotes the support practice factor (Renard et al., 1997). The descriptions and sources of the inputs used in the InVEST model in this study are listed in Table 2.
Table 2 Inputs to the sediment delivery ratio module of the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model (version 3.3.1) and data sources
Input Descriptions Data sources
Digital
elevation model (DEM)		 Digital elevation model, reflecting topography properties Geospatial data cloud (http://www.gscloud.cn/)
R Rainfall erosivity index, reflecting climate properties National earth system science data sharing infrastructure (http://www.geodata.cn/)
K Soil erodibility index, reflecting soil properties Liu et al., 2014a
Watersheds A shapefile of polygons. The calculation is also at watershed scale Institute of Geography, Chinese Academy of Sciences, 1997
P and C P is the support practice factor and C is crop-management factor, reflecting vegetation and anthropogenic factors RUSLE handbook (Renard et al., 1997) and the TP related studies (Wang et al., 2004)
Threshold flow accumulation The number of upstream cells that must flow into a cell before it is considered part of a stream Default
kb and IC0 Calibration parameters that determine the shape of the relationship between hydrologic connectivity and the SDR Default
SDRmax The maximum sediment delivery ratio (SDR) that a pixel can reach Default
The crop cover datasets reconstructed in this study were in a fractional format, whereas the land use/cover data required by the InVEST model needs to be in a binary format. Therefore, a transformation was performed. If the percentage of crop area in one grid was not less than 50%, it was classified as crop. Otherwise, the grid was classified as other land use/cover types. A natural vegetation map was used to represent the vegetation types before human disturbances. It should be noted that rainfall erosivity was static in this study because of the lack of geographically explicit climate change data with a high resolution.
The support practice factor, P, accounts for the effects of contour plowing, strip-cropping, or terracing relative to straight-row farming up and down the slope. The cover-management factor, C, accounts for the specified crop and management required relative to the tillage of fallow land. The explicit values of these parameters for the study area were obtained from the Revised Universal Soil Loss Equation (RUSLE) handbook (Renard et al., 1997) and related studies (Wang et al., 2004) in the TP (Table 3).
Table 3 Biophysical values of the cover-management factor C and support practice factor P
Land use/ cover categories Cover-management factor C Support practice factor P
Cropland 0.3 0.4
Forestland 0.003 0.2
Shrubland 0.02 0.2
Grassland 0.01 0.25
Waterbody 0 0
Snow 0 0.001
Wetland 0 0.001
Built-ups 0 0.001
Unused land 1 0.01

4 Results

4.1 Provincial cropland area changes for 1900-2000

The changes of fractional cropland area (FCA) of Qinghai province, the TAR, and the whole study area for 1900-2000 can be divided into three phases: a slow increase phase during 1900-1950, a rapid increase phase during 1950-1980, and an overall steady phase during 1980-2000 (Table 4).
Table 4 Cropland area in the Tibetan Plateau (TP) for 1900-2000. (Units: km2.)
Province 1900 1930 1950 1980 2000
Qinghai 4272 (0.597) 4497 (0.628) 4527 (0.632) 6850 (0.957) 6875 (0.960)
Tibet Autonomous Region 1510 (0.126) 1590 (0.132) 1620 (0.135) 2350 (0.196) 2308 (0.192)
Entire study area 5782 (0.301) 6087 (0.317) 6147 (0.320) 9200 (0.479) 9183 (0.478)

Note: The fractional cropland area (FCA) is provided in the brackets (%).

During 1900-1950, the FCA of the whole study area increased from 0.301% to 0.320%, which is a very slow increase. During 1950-1980, the cropland area of the TP increased rapidly compared with 1900-1950 and the FCA increased from 0.320% to 0.479% (Table 4), which can be attributed to a population increase and the reclamation activities of the Jiang Jieshi and Ma Bufang regimes. For the last two decades, the FCA of the whole study area remained stable. Similar cropland area increase patterns can be detected for Qinghai province and the TAR over the 20th century.

4.2 Crop cover changes for 1900-2000

Crop cover in the TP for 1900, 1930, 1950, 1980, and 2000 is shown in Figure 2, with a particular focus on the YHRV and YRTT regions. It can be seen that land use activities intensified greatly in the YHRV and YRTT regions over the 20th century. Cropland expansion can be detected in the TP, but it was not obvious in the two selected regions because there has been human occupation of both regions since BP 3600 (Chen et al., 2015), with wide spread cultivation even in the 18th-19th centuries (Luo et al., 2014; Ryavec, 2001; Wang et al., 2015).
Figure 2 Crop cover of Qinghai Province and the Tibet Autonomous Region (TAR) with a resolution of 1 × 1 km for 1900, 1930, 1950, 1980, and 2000. The right subfigure is the Yellow River-Huangshui River Valley (YHRV) and the bottom subfigure is Yarlung Zangbo River and its two tributaries valley (YRTT).
In 1900, the cropland was mainly distributed in the YHRV, especially in the Huangshui River Valley. While in the YRTT, the fractional cropland area of most grids was less than 10%. Two decades later, the spatial pattern of crop cover was basically the same as in 1900. By 1950, the land use had intensified slightly compared with the situation in 1900. The fractional cropland area of most grids with a value of 1%-10% in 1900 increased to 11%-20% in 1950, especially in the YHRV. Overall, the spatial pattern of crop cover in the TP for 1900-1950 remained stable, while land use intensified slightly.
During 1950-1980, the land use intensified substantially in both the YHRV and YRTT. The fractional cropland area of most grids increased by more than 10%, and in the YHRV and the YRTT the maximum values of the increase were 34% and 59%, respectively. The most intensified regions in the YHRV were the Huangshui River, the Datong River, and the Yellow River valleys. The most intensified regions in the YRTT were the Nianchu River and the Lhasa River valleys. It can also be seen that close to the main streams, there was a greater rate of increase.
In the last 20 years of the 20th century, the spatial pattern remained basically stable because of the ecological protection policies implemented by the government.

4.3 Sediment retention changes during 1900-2000

The sediment export induced by crop cover changes in the YHRV was generally low during 1900-2000 (Figure 3, Nos. a1-a5). The sediment export value of most grids were less than 11 ton/ha. Grids with relatively high values were only scattered in the Datong River and Huangshui River basins.
Figure 3 Sediment export induced by crop cover change in the Yellow River-Huangshui River Valley (YHRV) (Nos. a1-a5) and Yarlung Zangbo River and its two tributaries valley (YRTT) (Nos. b1-b5) for 1900, 1930, 1950, 1980, and 2000
In terms of the changes in sediment export over time, three stages were identified: a slight increase stage during 1900-1950, a rapid increase stage during 1950-1980, and a stable stage during 1980-2000. In the first stage, sediment export increased slightly and its spatial pattern remained stable over the first half of the 20th century. During 1950-1980, sediment export clearly increased, especially in Minhe autonomous county, with the amount in most grids increasing from less than 46 to 46-116 ton/ha and then further increasing to 116-235 ton/ha. This increase was also detected in the middle reaches of the Datong River and Huangshui River basins. Over the last two decades, the value and spatial pattern of sediment exports remained approximately stable.
An increase in sediment export means a decrease in sediment retention services. In this study, the rainfall erosivity index was static, therefore any changes in sediment retention services could only result from changes in crop cover. During 1950-1980, the increase in the population and the intensification of land use activities led to a decrease in sediment retention services.
It can be seen from the spatial patterns of sediment export in the YRTT that the sediment export north of the Yarlung Zangbo River was greater than the amount exported south of the river, especially in the Lhasa River valley, Nanmulin County, and Xietongmen County in the upper reaches of the Yarlung Zangbo River (Figure 3, Nos. b1-b5). During 1900-1950, sediment export increased slightly in the YRTT, with a similar change also observed in the YHRV. Subsequently, during 1950-1980, sediment export increased in regions where cropland increased, including the Nianchu River and the Lhasa River basins. In the Nianchu River basin, the sediment export increased from 0-3 ton/ha (4-9 ton/ha) to 25-36 ton/ha (37-735 ton/ha). In other words, the sediment retention services in the Nianchu River basin clearly decreased during 1950-1980. For other regions in the YRTT, no obvious changes were detected because changes in crop cover in these regions were not apparent. The spatial patterns of sediment export remained roughly stable during 1980-2000 in the YRTT.

5 Discussion

In this study, using a land suitability for cultivation model, the crop cover of the TP during the 20th century was reconstructed. Then, using the InVEST model (version 3.3.1) sediment delivery ratio module, the sediment retention services of the TP were assessed, with a focus on the YHRV and YRTT. We first compared our historical crop cover datasets with previous studies, and then the uncertainties and prospects were analyzed.

5.1 Comparisons with previous studies

Using a land suitability for cultivation model, Li et al. (2016) reconstructed the crop cover of China over the past 300 years at a resolution of 10 × 10 km. With some revisions to this method, Luo et al. (2014) reconstructed the crop cover of the YHRV in 1726 at a resolution of 2 × 2 km. In this study, we simplified the land suitability for cultivation model and improved the resolution of reconstruction. To evaluate the advances we made and the uncertainties of our study, we compared our results with those of Luo et al. (2014) and Li et al. (2016) respectively (Figure 4).
Figure 4 Comparison of spatial patterns among three datasets. (a) This study with a 1 × 1 km resolution; (b) Luo et al. (2014) with a 2 × 2 km resolution; (c) Li et al. (2016) with a 10 × 10 km resolution
Overall, the spatial patterns of the three studies were similar. All of them showed that cropland was mainly distributed in the Huangshui River, the Yellow River, and the Datong River basins (Figure 4). However, a closer examination indicated some discrepancies. For example, a lower land use intensity in the Yellow River and the Datong River basins was reported by Li et al. (2016) than the intensity found in the present study and in Luo et al. (2014). Further comparisons were therefore necessary. However, the resolutions and time periods of the three studies were different, so a pixel to pixel quantitative comparison was not possible. Therefore, we calculated the percentage cropland area in each elevation and slope interval for the three datasets and made an approximate comparison (Table 5).
It can be seen that the results of this study were basically consistent with those in datasets of Luo et al. (2014) and Li et al. (2016). Among the three datasets, the percentage cropland area was similar at each slope or elevation interval. Cropland was mainly distributed in regions with a slope within the intervals of ≤2°, 2°-6°, and 6°-15°, and in regions with an elevation ranging from 2-3 km. Regardless of elevation or slope, the percentage cropland area in each interval in this study and Luo et al. (2014) was similar. This may be because the spatial scale of the Li et al. (2016) dataset was 10 km, which is very coarse compared with the 1 km dataset used in this study and the 2 km dataset used in Luo et al. (2014). As a national scale dataset, Li et al. (2016) paid more attention to national than local scale reconstruction.
In terms of the model factors and inputs (Table 5), only two factors were considered in this study, whereas in the models used by Luo et al. (2014) and Li et al. (2016), four and three factors were used, respectively. As the third pole of the world, the TP is a remote region of China and there is limited geographical data available. Historical population and climate data in a geographically explicit format are difficult to obtain, which limits the application of models of Luo et al. (2014) and Li et al. (2016). The input cropland area of the present study was at the provincial level, whereas in Luo et al. (2014) a county level input was used. Therefore, the simplified model used in this study has a broader potential for application in the TP.
Table 5 A comparison of the inputs, methods, and results among the three datasets
Reconstruction Resolution
of input		 Factors
considered		 Resolution The percentage cropland area in each slope interval (°) The percentage cropland area in each elevation interval (km)
≤2 2-6 6-15 >15 ≤2 2-3 3-4 >4
This study Province Elevation, slope 1 km 24.1 60.7 15.0 0.1 8.3 79.2 12.5 0.0
Luo et al. (2014) County Elevation, slope, climate, population 2 km 23.0 62.1 14.8 0.2 3.2 85.6 11.2 0.0
Li et al. (2016) Province Elevation, slope, climate 10 km 14.4 59.0 26.3 0.4 5.5 69.7 24.1 0.8

5.2 Uncertainties and prospects

Studies concerning LUCC and its long term ecological effects in the TP are rare. Therefore, we reconstructed the crop cover of the TP for 1900-2000 and assessed its effects on sediment retention services, which represents pioneering work in this field. The uncertainties and future prospects of this work have also been considered. First, because of the scarcity of information, an assumption that the per capita cropland area was constant was applied to the estimation of cropland area in the first half of the 20th century. Because agricultural technology has slowly improved over time, this assumption may have underestimated the cropland area, especially for the earlier part of the century. Thus, a reconstruction of cropland area in the TP that is based on historical documents is needed in future studies. Second, climate change was not considered in the land suitability for cultivation model used in this study due to the unavailability of spatially explicit climate data. However, over the past one hundred years, the climate has clearly changed in the TP (Liu and Chen, 2000). Thus, better crop cover datasets of the TP need to be obtained if this factor is considered in subsequent allocation models.
The sediment delivery ratio module of the InVEST model relies on the universal soil loss equation, which represents rill-inter-rill erosion only. While this feature is common to many models of land use management, three other sources of sediment may contribute to the total sediment budget: gully erosion, stream bank erosion, and mass erosion (de Vente et al., 2013). Therefore, the sediment yield predicted by the model is less than the observations in some places and this needs to be taken into consideration in different decision-making contexts.
Because the resources needed to conduct model calibration and testing are scare, the sediment results used in this study were not calibrated. Without calibration, the InVEST sediment model still provides relevant information for the assessment of ecosystem services, especially in the context of decisions that involve the ranking of sediment export areas, such as the spatial prioritization of conservation, development or restoration activities, and taking into account non-linear sediment responses to changes in land use.

6 Conclusions

The cropland areas of Qinghai province and the TAR for 1900, 1930, 1950, 1980, and 2000 were estimated. Using a land suitability for cultivation model, we then allocated provincial cropland areas into grids with a size of 1 × 1 km. Finally, the influence of land use changes on sediment retention services were then assessed using the InVEST model. The major conclusions were as follows. Over the 20th century, the cropland area clearly increased, and land use activities intensified substantially in the YHRV and YRTT of the TP during 1950-1980. For other periods of the century, the cropland area and crop cover have remained relatively stable. Under the influence of changes in crop cover, sediment export has increased rapidly in Minhe autonomous county of the YHRV and in the Nianchu River and Lhasa River basins of the YRTT. The sediment retention services have clearly decreased in these regions during 1950-1980 because of changes in crop cover.
Comparisons with previous studies indicated that the reconstructed crop cover datasets used in this study are reasonable and the simplified model used in this study has a broader potential application in the TP. Our results will be of use to decision makers for conservation planning in these sensitive regions of the Earth.

The authors have declared that no competing interests exist.

References

Publishing order | Descend order by publishing year | Descend order by cited within
[1]
Cao Shuji, Ge Jianxiong, 2001. China Population History (Volume V: Qing Dynasty). Shanghai: Fudan University Press. (in Chinese)

[2]
Chen Fahu, Dong Guanghui, Zhang Dongjuet al., 2015. Agriculture facilitated permanent human occupation of the Tibetan Plateau after 3600 BP.Science, 347(6219): 248-250.

DOI

[3]
Cui Xuefeng, Graf Hans-F, 2009. Recent land cover changes on the Tibetan Plateau: A review.Climatic Change, 94(1/2): 47-61.This paper reviews the land cover changes on the Tibetan Plateau during the last 50 years partly caused by natural climate change and, more importantly, influenced by human activities. Recent warming trends on the plateau directly influence the permafrost and snow melting and will impact on the local ecosystem greatly. Human activities increased rapidly on the plateau during the last half century and have significant impacts on land use. Significant land cover changes on the Tibetan Plateau include permafrost and grassland degradation, urbanization, deforestation and desertification. These changes not only impact on local climate and environment, but also have important hydrological implications for the rivers which originate from the plateau. The most noticeable disasters include the flooding at the upper reaches of Yangtze River and droughts along the middle and lower reaches of Yellow River. Future possible land cover changes under future global climate warming are important but hard to assess due to the deficits of global climate model in this topographically complex area. Integrated investigation of climate and ecosystems, including human-beings, are highly recommended for future studies.

DOI

[4]
De Brue H, Verstraeten G, 2014. Impact of the spatial and thematic resolution of Holocene anthropogenic land-cover scenarios on modeled soil erosion and sediment delivery rates.Holocene, 24(1): 67-77.During the last decade, several global Holocene land cover scenarios have been produced that enable to quantify human impact on the landscape since the introduction of agriculture. Application of these land cover maps in geomorphic models may constitute a powerful means to estimate the long-term anthropogenic impact on sediment fluxes and thus to reconstruct changes in landscape morphology through time. However, the former coarse spatial resolutions of 5 arc-minutes at best question their potential for use in geomorphic models, since sediment redistribution processes operate at much smaller scales. Furthermore, current land cover reconstructions often do not differentiate the typology of human impact (e.g. cropland, pasture or disturbed forests), although the susceptibility of different anthropogenic land uses towards erosion varies greatly. In this study, we assessed the sensitivity of a spatially distributed erosion and sediment redistribution model (WaTEM/SEDEM) to the spatial and thematic resolution of input land cover maps. This was done through a comparison of two sets of geomorphic model runs. First, low-resolution land cover maps, expressed in proportions of anthropogenic vegetation within 5 grid cells, were simply resampled to a spatial resolution of 100 m for application in WaTEM/SEDEM. In a second set of model runs, estimated anthropogenic land cover was spatially allocated to a 100-m grid based on a logistic regression model that relates contemporary land cover types to slope, soil characteristics, landforms and distance to rivers. Since the geomorphic model requires high thematic resolution, different scenarios for the ratio between cropland and pasture were simulated for both types of land cover maps, i.e. low- and high-resolution maps, thus also allowing to assess how land-cover accuracy affects geomorphic model results. The analyses were performed within the Scheldt River basin in Belgium and northern France (19,000 km2) and for several dates from the Neolithic onwards. Modeled soil erosion and sediment delivery rates for the Dijle subcatchment were subsequently confronted with a field-based, temporally explicit sediment budget for evaluation. Results indicate that application of low-resolution, non-allocated land cover information in a geomorphic model leads to largely overestimated sediment fluxes, whereas spatial allocation of land cover types to a high-resolution grid yields more accurate results. The large variability of model outcomes is related to differences in landscape connectivity between high- and low-resolution land cover. Moreover, geomorphic model results are non-linearly related to the area under cropland. This indicates that there is not only a need for land-cover reconstructions at high spatial resolution but also that thematic differentiation of anthropogenic land cover types is essential for accurate geomorphic modeling.

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[5]
de Vente Joris, Poesen Jean, Verstraeten Gertet al., 2013. Predicting soil erosion and sediment yield at regional scales: Where do we stand?Earth-Science Reviews, 127: 16-29.Assessments of the implications of soil erosion require quantification of soil erosion rates (SE) and sediment yield (SSY) at regional scales under present and future climate and land use scenarios. A range of models is available to predict SE and SSY, but a critical evaluation of these models is lacking. Here, we evaluate 14 models based on 32 published studies and over 700 selected catchments. Evaluation criteria include: (1) prediction accuracy, (2) knowledge gain on dominant soil erosion processes, (3) data and calibration requirements, and (4) applicability in global change scenario studies. Results indicate that modelling of SE and SSY strongly depends on the spatial and temporal scales considered. In large catchments (>10,000km2), most accurate predictions of suspended sediment yield are obtained by nonlinear regression models like BQART, WBMsed, or Pelletier's model. For medium-sized catchments, best results are obtained by factorial scoring models like PSIAC, FSM and SSY Index, which also support identification of dominant erosion processes. Most other models (e.g., WATEM EDEM, AGNPS, LISEM, PESERA, and SWAT) represent only a selection of erosion and sediment transport processes. Consequently, these models only provide reliable results where the considered processes are indeed dominant. Identification of sediment sources and sinks requires spatially distributed models, which, on average, have lower model accuracy and require more input data and calibration efforts than spatially lumped models. Of these models, most accurate predictions with least data requirements were provided by SPADS and WATEM EDEM. Priorities for model development include: (1) simulation of point sources of sediment, (2) balancing model complexity and the quality of input data, (3) simulation of the impact of soil and water conservation measures, and (4) incorporation of dynamic land use and climate scenarios. Prediction of the impact of global change on SE and SSY in medium sized catchments is one of the main challenges in future model development. No single model fulfils all modelling objectives; a further integration of field observations and different model concepts is needed to obtain better contemporary and future predictions of SE and SSY.

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[6]
Dias L C P, Pimenta F M, Santos A Bet al., 2016. Patterns of land use, extensification, and intensification of Brazilian agriculture.Global Change Biology, 22(8): 2887-2903.Abstract Sustainable intensification of agriculture is one of the main strategies to provide global food security. However, its implementation raises enormous political, technological, and social challenges. Meeting these challenges will require, among other things, accurate information on the spatial and temporal patterns of agricultural land use and yield. Here, we investigate historical patterns of agricultural land use (1940-2012) and productivity (1990-2012) in Brazil using a new high-resolution (approximately 1 km(2) ) spatially explicit reconstruction. Although Brazilian agriculture has been historically known for its extensification over natural vegetation (Amazon and Cerrado), data from recent years indicate that extensification has slowed down and was replaced by a strong trend of intensification. Our results provide the first comprehensive historical overview of agricultural land use and productivity in Brazil, providing clear insights to guide future territorial planning, sustainable agriculture, policy, and decision-making.

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[7]
Ellis Erle C, Kaplan Jed O, Fuller Dorian Qet al., 2013. Used planet: A global history.Proceedings of the National Academy of Sciences of the United States of America, 110(20): 7978-7985.Human use of land has transformed ecosystem pattern and process across most of the terrestrial biosphere, a global change often described as historically recent and potentially catastrophic for both humanity and the biosphere. Interdisciplinary paleoecological, archaeological, and historical studies challenge this view, indicating that land use has been extensive and sustained for millennia in some regions and that recent trends may represent as much a recovery as an acceleration. Here we synthesize recent scientific evidence and theory on the emergence, history, and future of land use as a process transforming the Earth System and use this to explain why relatively small human populations likely caused widespread and profound ecological changes more than 3,000 y ago, whereas the largest and wealthiest human populations in history are using less arable land per person every decade. Contrasting two spatially explicit global reconstructions of land-use history shows that reconstructions incorporating adaptive changes in land-use systems over time, including land-use intensification, offer a more spatially detailed and plausible assessment of our planet's history, with a biosphere and perhaps even climate long ago affected by humans. Although land-use processes are now shifting rapidly from historical patterns in both type and scale, integrative global land-use models that incorporate dynamic adaptations in human-environment relationships help to advance our understanding of both past and future land-use changes, including their sustainability and potential global effects.

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[8]
Feng Zhiming, Liu Baoqin, Yang Yanzhao, 2005. A study of the changing trend of Chinese cultivated land amount and data reconstructing: 1949-2003.Journal of Natural Resources, 20(1): 35-43. (in Chinese)Studies of cultivated land change in China have long been hampered by the lack of accurate and reliable data since 1949.By analyzing the cultivated land data from different sources in different phases after 1949,the paper considers the statistics with more errors happens during 1960-1985.According to the systematic data on land use gathered in the 1996 survey,based on reverse deduction of the cultivated land area from 1986 to 1996,and deduction of the cultivated land area from 1960 to 1985 by stages by employing yield of grain,this paper redescribed the actual changing trend and character of Chinese cultivated land and analyzed the driving force of the policy relative to cultivated land to cultivated land area change.The result indicated that the Chinese cultivated land amount has been fluctuating since the founding of New China in 1949.It increased as a whole before 1979,and decreased slowly since the 1980s.The cultivated land amount decreased rapidly after 1999 because of cultivated land conversion into land for ecological purpose,hence the problems of grain security and cultivated land security result from which need to be paid more attention to.In future,the pace of ecological cultivated land conversion will be slowed down gradually after a fast ecological rescue phase,the grain security and cultivated land security will become the main influencing factors which affect changes of Chinese cultivated land amount.With the strict implementation of cultivated land protecting policy,the Chinese cultivated land amount will keep steady after 2010.

[9]
Foley Jonathan A, DeFries Ruth, Asner Gregory Pet al., 2005. Global consequences of land use.Science, 309(5734): 570-574.Land use has generally been considered a local environmental issue, but it is becoming a force of global importance. Worldwide changes to forests, farmlands, waterways, and air are being driven by the need to provide food, fiber, water, and shelter to more than six billion people. Global croplands, pastures, plantations, and urban areas have expanded in recent decades, accompanied by large increases in energy, water, and fertilizer consumption, along with considerable losses of biodiversity. Such changes in land use have enabled humans to appropriate an increasing share of the planet's resources, but they also potentially undermine the capacity of ecosystems to sustain food production, maintain freshwater and forest resources, regulate climate and air quality, and amelio-rate infectious diseases. We face the challenge of managing trade-offs between immediate human needs and maintaining the capacity of the biosphere to provide goods and services in the long term.

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[10]
Frolking S, Qiu J J, Boles Set al., 2002. Combining remote sensing and ground census data to develop new maps of the distribution of rice agriculture in China.Global Biogeochemical Cycles, 16(4): 1091.1] Large-scale assessments of the potential for food production and its impact on biogeochemical cycling require the best possible information on the distribution of cropland. This information can come from ground-based agricultural census data sets and/or spaceborne remote sensing products, both with strengths and weaknesses. Official cropland statistics for China contain much information on the distribution of crop types, but are known to significantly underestimate total cropland areas and are generally at coarse spatial resolution. Remote sensing products can provide moderate to fine spatial resolution estimates of cropland location and extent, but supply little information on crop type or management. We combined county-scale agricultural census statistics on total cropland area and sown area of 17 major crops in 1990 with a fine-resolution land-cover map derived from 1995-1996 optical remote sensing (Landsat) data to generate 0.5degrees resolution maps of the distribution of rice agriculture in mainland China. Agricultural census data were used to determine the fraction of crop area in each 0.5degrees grid cell that was in single rice and each of 10 different multicrop paddy rice rotations (e. g., winter wheat/rice), while the remote sensing land-cover product was used to determine the spatial distribution and extent of total cropland in China. We estimate that there were 0.30 million km(2) of paddy rice cropland; 75% of this paddy land was multicropped, and 56% had two rice plantings per year. Total sown area for paddy rice was 0.47 million km(2). Paddy rice agriculture occurred on 23% of all cultivated land in China.

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[11]
Fu B, Wang Y K, Xu Pet al., 2014. Value of ecosystem hydropower service and its impact on the payment for ecosystem services.Science of the Total Environment, 472: 338-346.61Ecosystem hydropower service is irreplaceable due to high cost of dams.61Hydropower PES requires a transition from passive protection to active protection.61A differential PES standard should be implemented for cascade development.

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[12]
Future Earth, 2014. Future Earth 2025 Vision .

[13]
Gaillard M J, Sugita S, Mazier Fet al., 2010. Holocene land-cover reconstructions for studies on land cover-climate feedbacks.Climate of the Past, 6(4): 483-499.Abstract:The major objectives of this paper are: (1) to review the pros and cons of the scenarios of past anthropogenic land cover change (ALCC) developed during the last ten years, (2) to discuss issues related to pollen-based reconstruction of the past land-cover and introduce a new method, REVEALS (Regional Estimates of VEgetation Abundance from Large Sites), to infer long-term records of past land-cover from pollen data, (3) to present a new project (LANDCLIM: LAND cover - CLIMate interactions in NW Europe during the Holocene) currently underway, and show preliminary results of REVEALS reconstructions of the regional land-cover in the Czech Republic for five selected time windows of the Holocene, and (4) to discuss the implications and future directions in climate and vegetation/land-cover modeling, and in the assessment of the effects of human-induced changes in land-cover on the regional climate through altered feedbacks. The existing ALCC scenarios show large discrepancies between them, and few cover time periods older than AD 800. When these scenarios are used to assess the impact of human land-use on climate, contrasting results are obtained. It emphasizes the need for methods such as the REVEALS model-based land-cover reconstructions. They might help to fine-tune descriptions of past land-cover and lead to a better understanding of how long-term changes in ALCC might have influenced climate. The REVEALS model is demonstrated to provide better estimates of the regional vegetation/land-cover changes than the traditional use of pollen percentages. This will achieve a robust assessment of land cover at regional- to continental-spatial scale throughout the Holocene. We present maps of REVEALS estimates for the percentage cover of 10 plant functional types (PFTs) at 200 BP and 6000 BP, and of the two open-land PFTs 'grassland' and 'agricultural land' at five time-windows from 6000 BP to recent time. The LANDCLIM results are expected to provide crucial data to reassess ALCC estimates for a better understanding of the land suface-atmosphere interactions.

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[14]
Hamel Perrine, Chaplin-Kramer Rebecca, Sim Sarahet al., 2015. A new approach to modeling the sediment retention service (InVEST 3.0): Case study of the Cape Fear catchment, North Carolina, USA. Science of the Total Environment, 524-525: 166-177.61A new sediment model was developed for the ecosystem services software tool ‘InVEST’61The model allows spatially-explicit assessment of the sediment retention service61Uncertainty assessment was performed in the Cape Fear basin, North Carolina61Local knowledge on sediment dynamics increases confidence in total sediment exports

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[15]
He Fanneng, Li Shicheng, Zhang Xuezhen, 2015. A spatially explicit reconstruction of forest cover in China over 1700-2000.Global and Planetary Change, 131: 73-81.The spatially explicit reconstruction of historical forest plays an important role in understanding human modifications of land surfaces and its environmental effects. Based on an analysis of the forest change history of China, we devised a reconstruction method for the historical forest cover in China. The core idea of the method is that the lands with high suitability for cultivation will be cultivated and deforested first, spreading to marginal lands with lower suitability for cultivation. By determining the possible maximum distribution extent of the forest, as well as devising the land suitability for cultivation assessment model and provincial forest area allocation model, we created 10 km forest cover maps of China for the years 1700 to 2000 with 10 year intervals. By comparison with satellite-based data in 2000, we found that the grids within 25% differences account for as much as 66.07% of all grids. The comparison with the historical documents-based data in northeast China indicated that the number of counties within 30% relative differences is 99, accounting for 74.44% of all counties. Therefore, the forest area allocation model we devised can accurately reproduce the spatial patterns of historical forest cover in China. Our reconstruction indicates that from 1700 to the 1960s, the deforestation mainly occurred in southwest China, the hilly regions of south China, the southeast of Gansu province, and northeast China; from the 1960s to 2000, the reforestation occurred in most traditional forested regions of China, particularly in the Tibet Plateau, hilly regions of south China and the Greater Khingan Mountains. The spatially explicit forest cover data sets we reconstructed can be used in global or regional climatic models to study the impact of land cover change on climate change.

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[16]
He Fanneng, Li Shicheng, Zhang Xuezhenet al., 2013. Comparisons of cropland area from multiple datasets over the past 300 years in the traditional cultivated region of China.Journal of Geographical Sciences, 23(6): 978-990.陆地使用 / 盖住变化是在气候和生态的模拟的一个重要参数。尽管他们广泛地在社区，半自动地面防空系统数据集和 HYDE 数据集被使用了，二代表性的全球历史的陆地使用数据集，很少在地区性的规模关于他们的精确性被估计。这里，我们为中国(TCRC ) 的传统的栽培区域执行了一些评价在上持续 300 年，由把 SAGE2010 和 HYDE (v3.1 ) 与中国历史的农田数据集(CHCD ) 作比较。比较在三空间规模被执行：由 60 km 格子房间的全部学习区域，省的区域和 60 km。结果证明(1 ) 从 SAGE2010 的农田区域从 CHCD 是多于那的大部分；而且，以在 1950 以后的从 1700 ～ 1950 和 0.34% 的 0.51% 的率的生长从 CHCD 与那也不一致。(2 ) HYDE 数据集(v3.1 ) 在全部学习区域上比半自动地面防空系统数据集接近了 CHCD 数据集。然而，大偏爱能被 60 km 格子房间规模在省的规模和 60 km 检测。有比70%大的偏爱的格子房间的百分比(70%)并且90%(90%)当那些有的偏爱为仅仅5%6%从10%～10%并且从30%～30%报道 时，分别地说明了全部的格子房间的56%63%和40%45%并且17%全部的格子房间分别地。(3 ) 用本地历史的档案，有高精确性的历史的数据集将是改进气候和生态的模拟的精确性的一个珍贵方法重建。

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[17]
Institute of Geography, Chinese Academy of Sciences, 1997. Atlas of the Tibetan Plateau. (in Chinese)

[18]
Jantz S M, Barker B, Brooks T Met al., 2015. Future habitat loss and extinctions driven by land-use change in biodiversity hotspots under four scenarios of climate-change mitigation.Conservation Biology, 29(4): 1122-1131.Abstract Numerous species have been pushed into extinction as an increasing portion of Earth's land surface has been appropriated for human enterprise. In the future, global biodiversity will be affected by both climate change and land-use change, the latter of which is currently the primary driver of species extinctions. How societies address climate change will critically affect biodiversity because climate-change mitigation policies will reduce direct climate-change impacts; however, these policies will influence land-use decisions, which could have negative impacts on habitat for a substantial number of species. We assessed the potential impact future climate policy could have on the loss of habitable area in biodiversity hotspots due to associated land-use changes. We estimated past extinctions from historical land-use changes (1500-2005) based on the global gridded land-use data used for the Intergovernmental Panel on Climate Change Fifth Assessment Report and habitat extent and species data for each hotspot. We then estimated potential extinctions due to future land-use changes under alternative climate-change scenarios (2005-2100). Future land-use changes are projected to reduce natural vegetative cover by 26-58% in the hotspots. As a consequence, the number of additional species extinctions, relative to those already incurred between 1500 and 2005, due to land-use change by 2100 across all hotspots ranged from about 220 to 21000 (0.2% to 16%), depending on the climate-change mitigation scenario and biological factors such as the slope of the species-area relationship and the contribution of wood harvest to extinctions. These estimates of potential future extinctions were driven by land-use change only and likely would have been higher if the direct effects of climate change had been considered. Future extinctions could potentially be reduced by incorporating habitat preservation into scenario development to reduce projected future land-use changes in hotspots or by lessening the impact of future land-use activities on biodiversity within hotspots. 2015 Society for Conservation Biology.

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[19]
Jin Xiaobin, Pan Qian, Yang Xuhonget al., 2016. Reconstructing the historical spatial land use pattern for Jiangsu Province in mid-Qing Dynasty.Journal of Geographical Sciences, 26(12): 1689-1706.This study is proposed to reconstruct a high-resolution spatial distribution of historical land use pattern with all land use types to overcome low-accuracy and/or the monotonic land use type in current historical land use reconstruction studies. The year of 1820 is set as the temporal section and the administrative area of Jiangsu Province is the study area. Land use types being reconstructed include farmland, residential land(including both urban land and rural residential land), water body, and other land(including forest land, grassland, and unused land). Data sources mainly refer to historical documents, historical geographic research outcomes, contemporary statistics, and natural environmental data. With great considerations over regional natural resources and social and economic conditions, a few theoretical assumptions have been proposed to facilitate the adjustment on prefecture farmland, urban land, and rural residential land. Upholding the idea that the contemporary land use pattern has been inherently in sequence with the historical land use pattern as well as the land use pattern shall be consistent to its accessibility, this study reconstructs the land use pattern in Jiangsu Province in 1820 with 100 m*100 m grids based on accessibility analysis and comprehensive evaluation. The outcome has been tested as valid by regionalization and correlation analysis. The resulted spatial distribution shows that back in 1820 in Jiangsu Province:(1) farmland, urban land, rural residential land, water body, and other land take about 48.49%, 4.46%, 0.16%, 15.03%, and 31.86% of the total land area respectively;(2) the land use pattern features high proportion of land in farming while low-proportion land in non-farming uses while population, topography, and the density of water body lead to great spatial variations; and(3) the reconstruction methodology has been tested as reasonable based on significant positive correlations between 1820 data and 1985 for both farmland and rural residential land at the prefecture level.

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[20]
Kaplan Jed O, Krumhardt Kristen M, Ellis Erle Cet al., 2011. Holocene carbon emissions as a result of anthropogenic land cover change.Holocene, 21(5): 775-791.Abstract Humans have altered the Earth land surface since the Paleolithic mainly by clearing woody vegetation first to improve hunting and gathering opportunities, and later to provide agricultural cropland. In the Holocene, agriculture was established on nearly all continents and led to widespread modification of terrestrial ecosystems. To quantify the role that humans played in the global carbon cycle over the Holocene, we developed a new, annually resolved inventory of anthropogenic land cover change from 8000 years ago to the beginning of large-scale industrialization (ad 1850). This inventory is based on a simple relationship between population and land use observed in several European countries over preindustrial time. Using this data set, and an alternative scenario based on the HYDE 3.1 land use data base, we forced the LPJ DGVM in a series of continuous simulations to evaluate the impacts of ALCC on terrestrial carbon storage during the preindustrial Holocene. Our model setup allowed us to quantify the importance of land degradation caused by repeated episodes of land use followed by abandonment. By 3 ka BP, cumulative carbon emissions caused by anthropogenic land cover change in our new scenario ranged between 84 and 102 Pg, translating to c. 7 ppm of atmospheric CO2. By ad 1850, emissions were 325鈥357 Pg in the new scenario, in contrast to 137 189 Pg when driven by HYDE. Regional events that resulted in local emissions or uptake of carbon were often balanced by contrasting patterns in other parts of the world. While we cannot close the carbon budget in the current study, simulated cumulative anthropogenic emissions over the preindustrial Holocene are consistent with the ice core record of atmospheric d13CO2 and support the hypothesis that anthropogenic activities led to the stabilization of atmospheric CO2 concentrations at a level that made the world substantially warmer than it otherwise would be.

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[21]
Klein Goldewijk Kees, Beusen Arthur, van Drecht Gerardet al., 2011. The HYDE 3.1 spatially explicit database of human-induced global land-use change over the past 12,000 years.Global Ecology and Biogeography, 20(1): 73-86.ABSTRACT Aim68 This paper presents a tool for long-term global change studies; it is an update of the History Database of the Global Environment (HYDE) with estimates of some of the underlying demographic and agricultural driving factors. Methods68 Historical population, cropland and pasture statistics are combined with satellite information and specific allocation algorithms (which change over time) to create spatially explicit maps, which are fully consistent on a 5′ longitude/latitude grid resolution, and cover the period 10,000 bc to ad 2000. Results68 Cropland occupied roughly less than 1% of the global ice-free land area for a long time until ad 1000, similar to the area used for pasture. In the centuries that followed, the share of global cropland increased to 2% in ad 1700 ( c . 3 million km2) and 11% in ad 2000 (15 million km2), while the share of pasture area grew from 2% in ad 1700 to 24% in ad 2000 (34 million km2) These profound land-use changes have had, and will continue to have, quite considerable consequences for global biogeochemical cycles, and subsequently global climate change. Main conclusions68 Some researchers suggest that humans have shifted from living in the Holocene (emergence of agriculture) into the Anthropocene (humans capable of changing the Earth's atmosphere) since the start of the Industrial Revolution. But in the light of the sheer size and magnitude of some historical land-use changes (e.g. as result of the depopulation of Europe due to the Black Death in the 14th century and the aftermath of the colonization of the Americas in the 16th century) we believe that this point might have occurred earlier in time. While there are still many uncertainties and gaps in our knowledge about the importance of land use (change) in the global biogeochemical cycle, we hope that this database can help global (climate) change modellers to close parts of this gap.

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[22]
Klein Goldewijk Kees,Verburg Peter H, 2013. Uncertainties in global-scale reconstructions of historical land use: An illustration using the HYDE data set.Landscape Ecology, 28(5): 861-877.AbstractLand use and land-use change play an important role in global integrated assessments. However, there are still many uncertainties in the role of current and historical land use in the global carbon cycle as well as in other dimensions of global environmental change. Although databases of historical land use are frequently used in integrated assessments and climate studies, they are subject to considerable uncertainties that often are ignored. This paper examines a number of the most important uncertainties related to the process of reconstructing historical land use. We discuss the origins of different types of uncertainty and the sensitivity of land-use reconstructions to these uncertainties. The results indicate that uncertainties not only arise as result of the large temporal and spatial variation in historical population data, but also relate to assumptions on the relationship between population and land use used in the reconstructions. Improving empirical data to better specify and validate the assumptions about the relationship between population and land use, while accounting for the spatial and temporal variation, could reduce uncertainties in the reconstructions. Such empirical evidence could be derived from local case studies, such as those conducted in landscape ecology, environmental history, archeology and paleoecology.

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[23]
Lehnert L W, Wesche K, Trachte Ket al., 2016. Climate variability rather than overstocking causes recent large scale cover changes of Tibetan pastures.Scientific Reports, 6: 24367.The Tibetan Plateau (TP) is a globally important “water tower” that provides water for nearly 40% of the world’s population.

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[24]
Leite Christiane C, Costa Marcos H, Soares-Filho Britaldo Set al., 2012. Historical land use change and associated carbon emissions in Brazil from 1940 to 1995. Global Biogeochemical Cycles, 26: GB2011.ABSTRACT The evaluation of impacts of land use change is in general limited by the knowledge of past land use conditions. Most publications on the field present only a vague description of the earlier patterns of land use, which is usually insufficient for more comprehensive studies. Here we present the first spatially explicit reconstruction of historical land use patterns in Brazil, including both croplands and pasturelands, for the period between 1940 and 1995. This reconstruction was obtained by merging satellite imagery with census data, and provides a 5′ × 5′ yearly data set of land use for three different categories (cropland, natural pastureland and planted pastureland) for Brazil. The results show that important land use changes occurred in Brazil. Natural pasture dominated in the 1950s and 1960s, but since the beginning of 1970s it has been gradually replaced by planted pasture, especially in southeast and center west of Brazil. The croplands began its expansion in the 1960s reaching extensive areas in almost all states in 1980. Carbon emissions from historical land use changes were calculated by superimposing a composite biomass map on grids of a weighted average of the fractions of the vegetation types and the replacement land uses. Net emissions from land use changes between 1940 and 1995 totaled 17.2 ± 9.0 Pg-C (90% confidence range), averaging 0.31 ± 0.16 Pg-C yr611, but reaching up to 0.47 ± 0.25 Pg-C yr611 during the 1960s and through 1986–1995. Despite international concerns about Amazon deforestation emissions, 72% of Brazil's carbon emissions during the period actually came from deforestation in the Atlantic Forest and Cerrado biomes. Brazil's carbon emissions from land use change are about 11 times larger than its emissions from fossil fuel burning, although only about 18.1% of the native biomass has been lost due to agricultural expansion, which is similar to the global mean (17.7%).

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[25]
Li Beibei, Fang Xiuqi, Ye Yuet al., 2010. Accuracy assessment of global historical cropland datasets based on regional reconstructed historical data: A case study in Northeast China.Science in China Series D: Earth Sciences, 53(11): 1689-1699.

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[26]
Li Shicheng, He Fanneng, Zhang Xuezhen, 2016. A spatially explicit reconstruction of cropland cover in China from 1661 to 1996.Regional Environmental Change, 16(2): 417-428.Reconstruction of cropland cover is crucial for assessing human impact on the environment. In this study, based on existing studies concerning historical cropland, population data and government inventories, we obtained a provincial cropland area dataset of China for 1661–1996 via collection, revision and reconstruction. Then, the provincial cropland area was allocated into grid cells of 1002×021002km depending on the land suitability for cultivation. Our reconstruction indicates that cropland increased from ~55.502×0210 4 km 2 in 1661 to ~130.002×0210 4 km 2 in 1996. From 1661 to 1873, cropland expanded tremendously in the Sichuan Basin, and land reclamation was greatly enhanced in North China Plain. For 1873–1980, agricultural development occurred primarily in northeastern China. After 1980, most provinces in the traditionally cultivated region of China experienced decreases in cropland area. In comparison with satellite-based data for 2000, we found that our reconstruction generally captures the spatial distribution of cropland. Also, differences are mostly <2002% (6120 to 2002%). Compared with HYDE 3.1 dataset, which is designed for the global scale, our model is more suitable for reconstructing the historical crop cover of China at 1002×021002km grid scale. Our reconstruction can be used in climate models to study the impact of crop cover change on the climate and carbon cycle.

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[27]
Li Shicheng, Zhang Yili, He Fanneng, 2015. Reconstruction of cropland distribution in Qinghai and Tibet for the past one hundred years and its spatiotemporal changes.Progress in Geography, 34(2): 197-206. (in Chinese)Since numerical simulation has become a popular method for studying the effects of land use and land cover change on climate and environment, spatially explicit historical cropland datasets are increasingly required in regional and global climate change and carbon cycle research. In this study, using historical population data as a proxy, we estimated the provincial cropland area of Qinghai and Tibet in 1910. Based on the statistical data of the National Bureau of Statistics of China, the survey data of the Ministry of Land and Resources, and the results of some previous studies, we revised the cropland area of Qinghai and Tibet in 1950-2000. The relationship between altitude and surface slope and cropland distribution were quantified to develop the spatially explicit reconstruction model of historical cropland at a resolution of 1 km 1 km. Since the cropland area reached the maximum in the 1980 s, the satellite-observed cropland distribution extent of this time period was taken as the maximum distribution extent of historical cropland. The model developed in this research was used to reconstruct the spatial patterns of cropland in Qinghai and Tibet in 1910, 1960, 1980, and 2000. The reconstruction results show that:(1) in 1910-1950, cropland area of Qinghai-Tibet was stable, while in 1950-1980 cropland area increased rapidly, reaching 10583 km2, which is the maximum of the entire study period; in 1980-1990, cropland area decreased slightly; and in 1990-2000, cropland area increased slightly;(2) with regard to its spatial distribution, in1910- 1960, cropland expanded and land use activities intensified greatly in the Yellow River- Huangshui River Valley(YHV); in 1960-1980, cropland expansion and land use intensification occurred in the YHV, the Yarlung Zangbo River, the Nianchu River, and the Lhasa River valleys; in 1980-2000, the spatial pattern of cropland in Qinghai and Tibet remained unchanged. By comparing the reconstruction results of this study for 2000 with satellite- observed cropland distribution of the same year, we found that the correlation coefficient was 0.92 and the absolute difference followed normal distribution. The percentage of grid cells where the absolute difference is low(-10% to 10%) reached 73.29%, while the percentage of grid cells where the absolute difference is high(40% or -40%) was 1.94%. Incorporating more information on historical population and cropland of Qinghai and Tibet will help improve the accuracy of our reconstruction modeling. The reconstruction results of this research can be used in regional climate models to study the impact of cropland cover change on the climate and carbon cycle.

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[28]
Liu Bintao, Tao Heping, Shi Zhanet al., 2014a. Spatial distribution characteristics of soil erodibility K value in Qinghai-Tibet Plateau.Bulletin of Soil and Water Conservation, 34(4): 13-16. (in Chinese)Soil erodibility is an important index to measure soil susceptibility to water erosion,and an essential parameter needed for soil erosion evaluation and soil erosion prediction.Based on 1 255 typical soil profile data,the values of soil erodibility(Kvalues)of all the soil types on the Qinghai—Tibet Plateau were calculated by erosionprodutivity impact calculator(EPIC)mathematical model and GIS.On which the weighted averages of the areas with the different values of soil erodibility are derived,and the distribution of the values of soil erodibility is analyzed based on map(1∶1 000 000)of soil types in the Qinghai—Tibet Plateau.The results showed that the mean value of soil erodibility was 0.230 8,and the area of lower,less lower,moderate,less higher,higher erodibility soils occupied 5.60%,18.23%,24.35%,44.02% and 7.80% of the Qinghai—Tibet Plateau,respectively.The total area of moderate and less higher erodibility soils is 1.77×106 km2 which is 68.37%of the total research area.The less higher and higher erodibility soils distribute in the Qiangtang Plateau,the Qaidam Basin and the valley of the Hengduan Mountains.Soil erodibility vertical variations are obvious in the Qinghai—Tibet Plateau,and especially in the Hengduan Mountains.Soil erodibility shows a decreasing trend from lower altitude to higher altitude.The physical and chemical properties of soils are affected by the water and the heat condition along an elevational gradient,and then the vertical variations of the physical and chemical properties of soils determine the vertical variations of the soil erodibility.

[29]
Liu Jiyuan, Kuang Wenhui, Zhang Zengxianget al., 2014b. Spatiotemporal characteristics, patterns, and causes of land-use changes in China since the late 1980s.Journal of Geographical Sciences, 24(2): 195-210.Land-use/land-cover changes (LUCCs) have links to both human and nature interactions. China’s Land-Use/cover Datasets (CLUDs) were updated regularly at 5-year intervals from the late 1980s to 2010, with standard procedures based on Landsat TMETM+ images. A land-use dynamic regionalization method was proposed to analyze major land-use conversions. The spatiotemporal characteristics, differences, and causes of land-use changes at a national scale were then examined. The main findings are summarized as follows.Land-use changes (LUCs) across China indicated a significant variation in spatial and temporal characteristics in the last 20 years (1990–2010). The area of cropland change decreased in the south and increased in the north, but the total area remained almost unchanged. The reclaimed cropland was shifted from the northeast to the northwest. The built-up lands expanded rapidly, were mainly distributed in the east, and gradually spread out to central and western China. Woodland decreased first, and then increased, but desert area was the opposite. Grassland continued decreasing. Different spatial patterns of LUC in China were found between the late 20th century and the early 21st century. The original 13 LUC zones were replaced by 15 units with changes of boundaries in some zones. The main spatial characteristics of these changes included (1) an accelerated expansion of built-up land in the Huang-Huai-Hai region, the southeastern coastal areas, the midstream area of the Yangtze River, and the Sichuan Basin; (2) shifted land reclamation in the north from northeast China and eastern Inner Mongolia to the oasis agricultural areas in northwest China; (3) continuous transformation from rain-fed farmlands in northeast China to paddy fields; and (4) effectiveness of the “Grain for Green” project in the southern agricultural-pastoral ecotones of Inner Mongolia, the Loess Plateau, and southwestern mountainous areas. In the last two decades, although climate change in the north affected the change in cropland, policy regulation and economic driving forces were still the primary causes of LUC across China. During the first decade of the 21st century, the anthropogenic factors that drove variations in land-use patterns have shifted the emphasis from one-way land development to both development and conservation.The “dynamic regionalization method” was used to analyze changes in the spatial patterns of zoning boundaries, the internal characteristics of zones, and the growth and decrease of units. The results revealed “the pattern of the change process,” namely the process of LUC and regional differences in characteristics at different stages. The growth and decrease of zones during this dynamic LUC zoning, variations in unit boundaries, and the characteristics of change intensities between the former and latter decades were examined. The patterns of alternative transformation between the “pattern” and “process” of land use and the causes for changes in different types and different regions of land use were explored.

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[30]
Liu Jiyuan, Liu Mingliang, Tian Hanqinet al., 2005. Spatial and temporal patterns of China’s cropland during 1990-2000: An analysis based on Landsat TM data.Remote Sensing of Environment, 98(4): 442-456.There are large discrepancies among estimates of the cropland area in China due to the lack of reliable data. In this study, we used Landsat TM/ETM data at a spatial resolution of 30 m to reconstruct spatial and temporal patterns of cropland across China for the time period of 1990 2000. Our estimate has indicated that total cropland area in China in 2000 was 141.1 million hectares (ha), including 35.6 million ha paddy land and 105.5 million ha dry farming land. The distribution of cropland is uneven across the regions of China. The North-East region of China shows more cropland area per capita than the South-East and North regions of China. During 1990 2000, cropland increased by 2.79 million ha, including 0.25 million ha of paddy land and 2.53 million ha of dry farming land. The North-East and North-West regions of China gained cropland area, while the North and South-East regions showed a loss of cropland area. Urbanization accounted for more than half of the transformation from cropland to other land uses, and the increase in cropland was primarily due to reclamation of grassland and deforestation. Most of the lost cropland had good quality with high productivity, but most gained cropland was poor quality land with less suitability for crop production. The globalization as well as changing environment in China is affecting land-use change. Coordinating the conflict between environmental conservation and land demands for food will continue to be a primary challenge for China in the future.

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[31]
Liu Xiaodong, Chen Baode, 2000. Climatic warming in the Tibetan Plateau during recent decades.International Journal of Climatology, 20(14): 1729-1742.

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[32]
Luo Jing, Zhang Yili, Liu Fengguiet al., 2014. Reconstruction of cropland spatial patterns for 1726 on Yellow River-Huangshui River Valley in northeast Qinghai-Tibet Plateau.Geographical Research, 33(7): 1285-1296. (in Chinese)In this study, first we revised the taxes-cropland area data in historical documents and estimated the cropland area in 1726 (the fourth year of Emperor Yongzheng's Reign in the Qing Dynasty) of Yellow River-Huangshui River Valley (YHV) which is located in northeast of Qinghai-Tibet Plateau. Subsequently, the cropland area was allocated into grids with a resolution of 2 km by 2 km under the help of GIS technology. The results show that the cropland area of YHV in 1726 was 1.427 10km, among which, 64.7% was cultivated by the minority as well as 35.3% was cultivated by soldiers and chieftain. The arable land of YHV is little due to the harsh natural environment. Crops can be found in some 47% of all grids and these grids were distributed in the Huangshui River basin, Beichuan River basin, the mid-lower reaches of the Datong and Yellow River. In terms of intensity of land use, the YHV had a low reclamation index in 1726. The reclamation index of 68.3% of all grids was less than 10% and only 1.4% of all grids had a reclamation index greater than 40%, which was attributed to the harsh environment and governmental policy. In addition, the spatial difference of the land use intensity was obvious. The reclamation index of Xining County was great on the whole and the mean value reached 13.5% at grid scale.

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[33]
Miao Lijuan, Zhu Feng, He Binet al., 2013. Synthesis of China’s land use in the past 300 years.Global and Planetary Change, 100: 224-233.China's land use has undergone many changes over the past 300 years due to the significant transformations caused by natural and human factors and their impact on regional climate and the environment. This comprehensive review of recent state-of-the-art studies of China's land-use changes during that period concentrates on cropland, forest, grassland and urban areas. While most small-scale studies have reconstructed information from historical archive data and focused on a specific time period, large-scale studies have tended to rely on inverse modeling techniques to interpret land-use change dynamics based on remote-sensing data for example, the global land-use products of the History Database of the Global Environment (HYDE) and Center for Sustainability and the Global Environment (SAGE) datasets. All studies have shown that the cropland areas in China increased between 1700 and 1950, although they indicate different magnitudes and rates. A decrease in forest coverage was also reported in all studies. Little information was available on urban and grassland areas over the same period. Rapid urbanization in China has been particularly evident in the past 50 years. Meanwhile, spatially explicit reconstructions of historical land-use change in China since 1700 remain highly uncertain due to the lack of reliable data. Extensive work on primary data collection is required, including land-use records and drivers for future change.

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[34]
Miao Lijuan, Zhu Feng, Sun Zhanliet al., 2016. China’s land-use changes during the past 300 years: A historical perspective.International Journal of Environmental Research and Public Health, 13(9): 847.Understanding the processes of historical land-use change is crucial to the research of global environmental sustainability. Here we examine and attempt to disentangle the evolutionary interactions between land-use change and its underlying causes through a historical lens. We compiled and synthesized historical land-use change and various biophysical, political, socioeconomic, and technical datasets, from the Qing dynasty to modern China. The analysis reveals a clear transition period between the 1950s and the 1980s. Before the 1950s, cropland expanded while forested land diminished, which was also accompanied by increasing population; after the 1980s land-use change exhibited new characteristics: changes in cropland, and decoupling of forest from population as a result of agricultural intensification and globalization. Chinese political policies also played an important and complex role, especially during the 1950s 1980s transition periods. Overall, climate change plays an indirect but fundamental role in the dynamics of land use via a series of various cascading effects such as shrinking agricultural production proceeding to population collapse and outbreaks of war. The expected continuation of agricultural intensification this century should be able to support increasing domestic demand for richer diets, but may not be compatible with long-term environmental sustainability.

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[35]
Nelson Erik, Mendoza Guillermo, Regetz Jameset al., 2009. Modeling multiple ecosystem services, biodiversity conservation, commodity production, and tradeoffs at landscape scales.Frontiers in Ecology and the Environment, 7(1): 4-11.Nature provides a wide range of benefits to people. There is increasing consensus about the importance of incorporating these "ecosystem services" into resource management decisions, but quantifying the levels and values of these services has proven difficult. We use a spatially explicit modeling tool, Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST), to predict changes in ecosystem services, biodiversity conservation, and commodity production levels. We apply InVEST to stakeholder-defined scenarios of land-use/land-cover change in the Willamette Basin, Oregon. We found that scenarios that received high scores for a variety of ecosystem services also had high scores for biodiversity, suggesting there is little tradeoff between biodiversity conservation and ecosystem services. Scenarios involving more development had higher commodity production values, but lower levels of biodiversity conservation and ecosystem services. However, including payments for carbon sequestration alleviates this tradeoff. Quantifying ecosystem services in a spatially explicit manner, and analyzing tradeoffs between them, can help to make natural resource decisions more effective, efficient, and defensible.

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[36]
Newbold T, Hudson L N, Hill S L Let al., 2015. Global effects of land use on local terrestrial biodiversity.Nature, 520(7545): 45-50.Human activities, especially conversion and degradation of habitats, are causing global biodiversity declines. How local ecological assemblages are responding is less clear--a concern given their importance for many ecosystem functions and services. We analysed a terrestrial assemblage database of unprecedented geographic and taxonomic coverage to quantify local biodiversity responses to land use and related changes. Here we show that in the worst-affected habitats, these pressures reduce within-sample species richness by an average of 76.5%, total abundance by 39.5% and rarefaction-based richness by 40.3%. We estimate that, globally, these pressures have already slightly reduced average within-sample richness (by 13.6%), total abundance (10.7%) and rarefaction-based richness (8.1%), with changes showing marked spatial variation. Rapid further losses are predicted under a business-as-usual land-use scenario; within-sample richness is projected to fall by a further 3.4% globally by 2100, with losses concentrated in biodiverse but economically poor countries. Strong mitigation can deliver much more positive biodiversity changes (up to a 1.9% average increase) that are less strongly related to countries' socioeconomic status.

DOI PMID

[37]
Pan Tao, Wu Shaohong, Liu Yujie, 2015. Relative contributions of land use and climate change to water supply variations over Yellow River Source Area in Tibetan Plateau during the past three decades.PLoS One, 10(4): e0123793.There is increasing evidence of environmental change impacts on ecosystem processes and services, yet poor understanding of the relative contributions of land use and climate change to ecosystem services variations. Based on detailed meteorological, hydrological records and satellite data over the Yellow River Source Area (YRSA) in Tibetan Plateau from 1980s to 2008, together with a water-yield module of Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model and also a Residual Trends (RESTREND) method, we assessed the water supply variations in YRSA during the past three decades and disentangled the relative contributions of land use and climate change. Results show that water supply significantly decreased from 1980 to 2005 and then increased from 2005 to 2008. The quantity slightly decreased from 283.01mm in 1980 to 276.95mm in 1995, 270.12mm in 2000 and 267.97mm in 2005, and it then rebounded slightly to 275.26mm in 2008. The water supply variation ranged from 283.01mm to 267.97mm. Climate change contributed dominantly to water supply decrease from 1980 to 1995, which accounts for approximately 64% of the decrease. During 1995 to 2000, land use contributed more and about 58% to the water supply decrease as the intense human activities. From 2000 to 2005, climate change became a positive contribution to the water supply as the increased precipitation, but the land use still contributed negatively. From 2005 to 2008, both climate and land use have positive impacts, but land use contributed about 61% to the water supply increase. The implementation of the Three Rivers Source Area Ecological Protection Project has greatly improved the vegetation coverage conditions and the water retention ability during this period. We recommend that the implementation of ecological projects, grazing policies and artificial improvement of degraded grassland would help to conserve the water retention ability and increase water supply.

DOI PMID

[38]
Posner S, Verutes G, Koh Iet al., 2016. Global use of ecosystem service models.Ecosystem Services, 17: 131-141.61We analyze InVEST ecosystem service model usage over a 25-month period.61Models for regulating services were most commonly used.61Country-level variables related to capacity best explain usage.61Trainings had a significant and enduring effect on usage.61Analyzing model usage is vital for targeting support and increasing policy impact.

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[39]
Ramankutty N, Foley J A, 1999. Estimating historical changes in global land cover: Croplands from 1700 to 1992.Global Biogeochemical Cycles, 13(4): 997-1027.Human activities over the last three centuries have significantly transformed the Earth's environment, primarily through the conversion of natural ecosystems to agriculture. This study presents a simple approach to derive geographically explicit changes in global croplands from 1700 to 1992. By calibrating a remotely sensed land cover classification data set against cropland inventory data, we derived a global representation of permanent croplands in 1992, at 5 min spatial resolution [Ramankutty and Foley, 1998]. To reconstruct historical croplands, we first compile an extensive database of historical cropland inventory data, at the national and subnational level, from a variety of sources. Then we use our 1992 cropland data within a simple land cover change model, along with the historical inventory data, to reconstruct global 5 min resolution data on permanent cropland areas from 1992 back to 1700. The reconstructed changes in historical croplands are consistent with the history of human settlement and patterns of economic development. By overlaying our historical cropland data set over a newly derived potential vegetation data set, we analyze our results in terms of the extent to which different natural vegetation types have been converted for agriculture. We further examine the extent to which croplands have been abandoned in different parts of the world. Our data sets could be used within global climate models and global ecosystem models to understand the impacts of land cover change on climate and on the cycling of carbon and water. Such an analysis is a crucial aid to sharpen our thinking about a sustainable future.

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[40]
Renard K G, Foster G R, Weesies G Aet al., 1997. Predicting Soil Erosion by Water: A Guide to Conservation Planning with the Revised Soil Loss Equation. (RUSLE). United States Department of Agriculture, Agriculture Handbook, No.703, 1-367.The book provides guidelines for the selection of the best control methods for farms, ranches and other erosion-prone areas throughout USA. The prediction of soil loss founded on the Universal Soil Loss Equation (USLE) is revised using information available on monthly precipitation and temperature, front-free period, annual rain erosivity, below ground biomass, canopy cover and height at 15 days intervals, and soil cover disturbances associated with farming operations. The information is available on CITY, CROP and OPERATION databases.

[41]
Ryavec Karl, 2001. Land use/cover change in central Tibet, c. 1830-1990: Devising a GIS methodology to study a historical Tibetan land decree.Geographical Journal, 167(4): 342-357.Abstract In this study, historical Tibetan tax-related data pertaining to cultivated land in central Tibet are studied by means of GIS and compared with contemporary patterns. A Tibetan land decree from 1830 contains aggregated data on the amount of land-based tax units for estates in 57 districts of central Tibet. The purpose of this study is to devise a GIS methodology to study the potential utility of these data for historical geographical research, and to determine the approximate changes in cultivated land areas between 1830 and 1990. Traditional Tibetan tax data are significant for current efforts to construct historical land cover databases of the Tibetan Plateau region for the study of the human dimensions of global change.

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[42]
Sharp R, Tallis H T, Ricketts T Het al., 2015. InVEST 3.2.0 User’s Guide. The Natural Capital Project, Stanford University, University of Minnesota, The Nature Conservancy, and World Wildlife Fund.

[43]
Simmons C T, Matthews H D, 2016. Assessing the implications of human land-use change for the transient climate response to cumulative carbon emissions.Environmental Research Letters, 11(3): 035001.Recent research has shown evidence of a linear climate response to cumulative COemissions, which implies that the source, timing, and amount of emissions does not significantly influence the climate response per unit emission. Furthermore, these analyses have generally assumed that the climate response to land-use COemissions is equivalent to that of fossil fuels under the assumption that, once in the atmosphere, the radiative forcing induced by COis not sensitive to the emissions source. However, land-cover change also affects surface albedo and the strength of terrestrial carbon sinks, both of which have an additional climate effect. In this study, we use a coupled climate-carbon cycle model to assess the climate response to historical and future cumulative land-use COemissions, in order to compare it to the response to fossil fuel CO. We find that when we isolate the CO-induced (biogeochemical) temperature changes associated with land-use change, then the climate response to cumulative land-use emissions is equivalent to that of fossil fuel CO. We show further that the globally-averaged albedo-induced biophysical cooling from land-use change is non-negligible and may be of comparable magnitude to the biogeochemical warming, with the result that the net climate response to land-use change is substantially different from a linear response to cumulative emissions. However, our new simulations suggest that the biophysical cooling from land-use change follows its own independent (negative) linear response to cumulative net land-use COemissions, which may provide a useful scaling factor for certain applications when evaluating the full transient climate response to emissions. (letter)

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[44]
Smith M C, Singarayer J S, Valdes P Jet al., 2016. The biogeophysical climatic impacts of anthropogenic land use change during the Holocene.Climate of the Past, 12(4): 923-941.The first agricultural societies were established around 10 ka BP and had spread across much of Europe and southern Asia by 5.5 ka BP with resultant anthropogenic deforestation for crop and pasture land. Various studies (e.g. Joos et al., 2004; Kaplan et al., 2011; Mitchell et al., 2013) have attempted to assess the biogeochemical implications for Holocene climate in terms of increased carbon dioxide and methane emissions. However, less work has been done to examine the biogeophysical impacts of this early land use change. In this study, global climate model simulations with Hadley Centre Coupled Model version 3 (HadCM3) were used to examine the biogeophysical effects of Holocene land cover change on climate, both globally and regionally, from the early Holocene (8 ka BP) to the early industrial era (1850 CE). Two experiments were performed with alternative descriptions of past vegetation: (i) one in which potential natural vegetation was simulated by Top-down Representation of Interactive Foliage and Flora Including Dynamics (TRIFFID) but without land use changes and (ii) one where the anthropogenic land use model Kaplan and Krumhardt 2010 (KK10; Kaplan et al., 2009, 2011) was used to set the HadCM3 crop regions. Snapshot simulations were run at 1000-year intervals to examine when the first signature of anthropogenic climate change can be detected both regionally, in the areas of land use change, and globally. Results from our model simulations indicate that in regions of early land disturbance such as Europe and south-east Asia detectable temperature changes, outside the normal range of variability, are encountered in the model as early as 7 ka BP in the June-July-August (JJA) season and throughout the entire annual cycle by 2-3 ka BP. Areas outside the regions of land disturbance are also affected, with virtually the whole globe experiencing significant temperature changes (predominantly cooling) by the early industrial period. The global annual mean temperature anomalies found in our single model simulations were -0.22 at 1850 CE, -0.11 at 2 ka BP, and -0.03 C at 7 ka BP. Regionally, the largest temperature changes were in Europe with anomalies of -0.83 at 1850 CE, -0.58 at 2 ka BP, and -0.24 C at 7 ka BP. Large-scale precipitation features such as the Indian monsoon, the Intertropical Convergence Zone (ITCZ), and the North Atlantic storm track are also impacted by local land use and remote teleconnections. We investigated how advection by surface winds, mean sea level pressure (MSLP) anomalies, and tropospheric stationary wave train disturbances in the mid- to high latitudes led to remote teleconnections.

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[45]
Sturck J, Schulp C J E,Verburg P H, 2015. Spatio-temporal dynamics of regulating ecosystem services in Europe: The role of past and future land use change.Applied Geography, 63: 121-135.61We quantified land change impacts on two regulating ecosystem services (1900–2040).61We quantified (mis-)matches of ecosystem service supply and demand.61Future demands increase rapidly while potential to increase supply is modest under scenarios.

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[46]
Su Changhong, Fu Bojie, 2013. Evolution of ecosystem services in the Chinese Loess Plateau under climatic and land use changes.Global and Planetary Change, 101: 119-128.Due to the lengthy historic land use by humans and the climate change characterized by warming and drying, the Loess Plateau has been plagued by ecosystem degradation for a long time. A series of ecological conservation projects launched since the 1970s altered the land use pattern greatly, and exerted a profound influence on the ecosystem services. Based on the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) and Carnegie-Ames-Stanford Approach (CASA) models, we assessed the historical fluctuation of sediment control, water yield, and net primary production (NPP) in the Loess Plateau. The results showed that sediment retention was greatly consolidated indicated by the sharp decrease of sediment export. Water yield decreased at first and increased later. Both sediment export and water yield showed an increasing 'spatial homogenization' tendency during the period. NPP was steady between 1990 and 2000, and then increased greatly after 2000. Ecosystem services are interlinked closely and complexly. Correlation analyses indicated a positive relationship between the difference in sediment export and water yield (r(2)=0.776**) from 1975 to 2008, with negative correlations between the difference of NPP and water yield (r(2)=-0.422**)/sediment export (r(2)=-0.240*) from 1990 to 2008. This, to some extent, implies that there are tradeoffs between the services of water yield and sediment control/NPP, and there is synergy between sediment control and NPP. Climatic and land use changes are the major drivers on ecosystem services fluctuation. Correlation analyses showed that the decrease of precipitation significantly hindered water yield (r(2)=0.980**) and sediment export (r(2)=0.791**). The increase of temperature exerted a slight negative influence on water yield (r(2)=-0350**). A spatial concordance existing between the 'cropland to grass/woodland' area and the high sediment control (r(2)=0313**)/NPP (r(2)=0.488**) area indicated that the land use change from cropland to woodland/grassland significantly consolidated sediment control and NPP production. The observed spatio-temporal variation of ecosystem services and their correlations provide an operable criterion for land use management policies. (C) 2013 Elsevier B.V. All rights reserved.

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[47]
Sun Honglie, Zheng Du, Yao Tandonget al., 2012. Protection and construction of the national ecological security shelter zone on Tibetan Plateau.Acta Geographica Sinica, 67(1): 3-12. (in Chinese)The shelter function of Tibetan Plateau has an important effect on the ecological security in China, even in Asia. Under the joint influence of global change and human activities, ecosystem destabilizing and resources and environment pressure increasing emerge on the Tibetan Plateau, which have caused some problems, including significant glacier retreat, serious land degradation, aggravated soil erosion and water loss, increased threats to biodiversity along with decreased rare and specious biological resources, and natural disasters increasing. These problems have a great influence on regional ecological security shelter function on the plateau. Based on the relevant research and practical experience in ecological construction, some suggestions are proposed to strengthen ecological protection and construction of the national ecological security shelter zone on the Tibetan Plateau at present, namely, strengthening basic research on the Tibetan Plateau ecological shelter impacts and regional ecological security enhancement and climate change mitigation; developing the key technology of protection and construction of the national ecological security shelter zone on the plateau and demonstration; striving to set up a monitoring system of ecological shelter function, intensifying evaluation of protection and construction efficiency of ecological security shelter zone, perfecting evaluation systems and standards, and summarizing experience, so as to enhance the overall function of national ecological security shelter and to further take the initiative in dealing with global change.

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[48]
Wang Xiaodan, Zhong Xianghao, Fan Jianrong, 2004. Assessment and spatial distribution of sensitivity of soil erosion in Tibet.Journal of Geographical Sciences, 14(1): 41-46.

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[49]
Wang Yukun, Tao Juanping, Liu Fengguiet al., 2015. Reconstruction of cropland spatial pattern in 1830 in the middle reaches of Yarlung Zangbo River Valley.Geographical Research, 34(12): 2355-2367. (in Chinese)In this study, we collected and revised the cultivated land tax data from the Tie Hu List, which recorded the cultivated land tax of the Midstream Yarlung Zangbo River Valley of Tibet in 1830, the data were transformed to modern cropland land area. Then the gridding method was used to reconstruct the cropland spatial pattern with a resolution of 1 km by 1 km in the study area in 1830. The results show that: as a whole, the cropland area of this region in 1830 was 895 km2, among which, 39% was cultivated by the Government, 31% was cultivated by the Nobles, and 29% by Temples. In terms of the distribution pattern, the cultivated land was found in only 27.4% of the grids, and it was distributed dispersedly in the main stream basins of Yarlung Zangbo River Valley and its tributary basins. As for the intensity of land use,the lower level reclamation index reflects the situation of local lower level agricultural production. The average reclamation index of the whole study area was only 0.6%. However, the spatial difference of the reclamation index was obvious. The average reclamation index of Lhasa was 6.3%, which was the greatest in the study area. The average reclamation index of Shigatse, Gyangze, Nedong and Qonggyai is about 3%, while Gongbu and the western countieshas the lowest reclamation index, which was less than 1%.

[50]
Wei Xueqiong, Ye Yu, Zhang Qianet al., 2016. Reconstruction of cropland change over the past 300 years in the Jing-Jin-Ji area, China.Regional Environmental Change, 16(7): 2097-2109.Land-use and land-cover change (LUCC) has strongly influenced the global and regional climate and environmental change, especially over the last three centuries. Accurate reconstruction of historical

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[51]
Yang Xuhong, Jin Xiaobin, Du Xindonget al., 2016. Multi-agent model-based historical cropland spatial pattern reconstruction for 1661-1952, Shandong Province, China.Global and Planetary Change, 143: 175-188.To advance the research of global land use/cover change (LUCC), biodiversity, global carbon cycle, and other aspects of the earth system, it is essential to reconstruct changes in historical cropland cover with long time series and high-resolution grid. Currently, it is a general approach which is based on the view of combining the overall control of cropland area, selecting grid of high land suitability, and ‘top-down’ decision-making behaviors to reconstruct the historical cropland. Considering various factors that influenced cropland distribution, including behavioral agent's selection by itself and the limitation of nature and human factors, a spatiotemporal dynamical reconstruction model of historical cropland based on the multi-agent systems has been developed from the perspective of ‘bottom-up’, which combine macroscopic and microscopic decision-making behaviors of agents to simulate the government and farmer autonomously implementing the selection behaviors of farming area. Taking Shandong Province as the study area, this model was used to imitate its cropland spatiotemporal pattern with 102km grid-resolution from 1661 combining the contemporary pattern and reconstructed amount of historical cropland as a maximum potential scope and control variable of reconstruction model, respectively, furthermore, followed the accuracy valuation and comparative analysis. The reconstructed results show that: 1) It is properly suitable for Multi-Agent to simulate and reconstruct the spatial distribution of historical cropland; 2) compared with historical map datasets (1930s) from the view of point to point, the correctly classified producer accuracy, user accuracy and overall accuracy of reconstructed result totally up to 59.09%, 80.62% and 62.31%, respectively, and shows our reconstruction map achieved a better agreement with the historical maps; 3) from the view of grid-level or county-level, our reconstruction approach can effectively keep away from the grid with mountain-hilly and easily flooding probability, it showed a good similarity and higher consistency when compared with the research result based on archives and historical records in overall pattern and tendency of cultivation, and difference error decrease gradually, moreover, the cultivation ratios in county-level is more close to the historical situation.

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[52]
Ye Yu, Fang Xiuqi, Ren Yuyuet al., 2009. Cropland cover change in Northeast China during the past 300 years. Science in China Series D: Earth Sciences, 52(8): 1172-1182.Land use/cover change induced by human activities has emerged as a “global” phenomenon with Earth system consequences. Northeast China is an area where the largest land cultivation activities by migrants have happened in China during the past 300 years. In this paper, methods including documentary data calibration and multi-sourced data conversion model are used to reconstruct historical cropland cover change in Northeast China during the past 300 years. It is concluded that human beings have remarkably changed the natural landscape of the region by land cultivation in the past 300 years. Cropland area has increased almost exponentially during the past 300 years, especially during the past 100 years when the ratio of cropland cover changed from 10% to 20%. Until the middle of the 19th century, the agricultural area was still mainly restricted in Liaoning Province. From the late 19th century to the early 20th century, dramatic changes took place when the northern boundary of cultivation had extended to the middle of Heilongjiang Province. During the 20th century, three agricultural regions with high ratio of cropland cover were formed after the two phases of spatial expansion of cropland area in 1900s–1930s and 1950s–1980s. Since 1930s–1940s, the expansion of new cultivated area have invaded the forest lands especially in Jilin and Heilongjiang Provinces.

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[53]
Ye Yu, Wei Xueqiong, Li Fanet al., 2015. Reconstruction of cropland cover changes in the Shandong Province over the past 300 years.Scientific Reports, 5: 13642.To advance global change rssearch, it is essential to reconstruct changes in historical cropland coverage on a regional scale in China.

DOI PMID

[54]
Zhang Xuezhen, He Fanneng, Li Shicheng, 2013. Reconstructed cropland in the mid-eleventh century in the traditional agricultural area of China: Implications of comparisons among datasets.Regional Environmental Change, 13(5): 969-977.Reconstructions of historical cropland area and spatial distribution are necessary for studying human effects on the environment due to agricultural development. To understand the current status of reconstructions of cropland area and its spatial distribution in the mid-eleventh century in the traditional agricultural area of China, we compared three available datasets: the historic cropland inventories-based HE dataset, the population-based History Database of the Global Environment (HYDE) dataset, and the PJ dataset. The results indicate that the HYDE and PJ datasets estimated the regional mean cropland area fraction (a ratio of cropland area to total land area, hereafter, CAF) for the study area to be 0.12 and 0.09, respectively, both of which were lower than the HE estimation of 0.18. Moreover, both the HYDE and PJ datasets have a poor ability to capture the spatial distribution of the historical CAF. The HYDE dataset overestimated the cropland area in North China and underestimated the cropland area in the Yangtze River reach. The HYDE dataset also overestimated the cropland area along the great rivers in North China. The PJ dataset underestimated the cropland area in the old agricultural area and overestimated the cropland area in the relatively new agricultural area. These incorrect spatial distributions from the HYDE and PJ datasets mainly resulted from the underestimation of the historical population and an incorrect approach for the spatial allocation of cropland within China. The incorrect approach was mainly derived from a poor understanding of the historic spatial distribution of cropland. Using the expert knowledge of local historians may be an effective method to reduce the uncertainties in the global historic cropland reconstruction.

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[55]
Zhang Yili, Li Bingyuan, Zheng Du, 2002. A discussion on the boundary and area of the Tibetan Plateau in China.Geographical Research, 21(1): 1-8. (in Chinese)The Tibetan Plateau is a unique geomorphic unit composed of some basic geomorphic types, such as extreme high mountains,high mountains, hills, plains, and tablelands of high altitude or sub-high altitude. Different opinions for the exact scope of Tibetan Plateau exist. According to latest research achievement and the long time fieldwork, questions related to the area and boundary of the Plateau have been discussed in view of geography, and the principles taking geomorphic characters as the main rule and considering the integrity have been made to define the boundary. The 1∶1 000 000 geomorphological map was compiled based on 1∶100 000 aerial photographic map,1∶500 000 topographic map and interpretation of satellite images. By refering to the 1∶3 000 000 relief map, the boundary of the Plateau was delineated.The position of the boundary was quantitatively determined with GIS and GPS.The map of electronic version of the Tibetan Plateau was compiled. The main conclusion is that Tibetan Plateau starts from the southern edge of the Himalayan Range, abuts on India,Nepal and Bhutan,connects the northern edge of Kunlun, Altun and Qilian Mts., and joins Tarim Basin and Hexi Corridor in Central Asia.The west of it is the Pamirs and Karakorum Mts., bordering on Kirghizistan, Tajikistan, Afghanistan, Pakistan and Kashmir. The east of it is Yulongxueshan, Daxueshan, Jiajinshan and Qionglaishan Mts.as well as south or east piedmont of Minshan Mts. Tibetan Plateau joins the Qinling Mts.and Loess Plateau with its eastern and northeastern part. Tibetan Plateau in China's territory starts from the Pamirs in the west and reaches to Hengduanshan in the east. It bestrides a longitude of 31 degrees with a length of 2 945 km from east to west,and bestrides a latitude of 13 degrees with a length of 1 532 km from south to north. It ranges from 26°00′12" N to 39°46′50" N and from 73°18′52"E to 104°46′59"E, covering an area of 2 572.4×10 3 km 2. Administratively, it embraces 201 counties (cities) in 6 provinces, namely, the Tibet Autonomous Region (73 counties/cities,1 176.0×10 3 km 2, part of Cona, Mêdog and Zayü), the Qinghai Province(40 counties/cities,721.0×10 3 km 2, some counties only partially), Dêqen Tibetan Autonomous Prefecture in Northwest Yunnan Province(9 counties/cities,33.5×10 3 km 2), West Sichuan Province ( 46 counties/cities about 254.0×10 3 km 2 ,such as Garze Autonomous Prefecture, Aba Tibetan and Qiangzu Autonomous Prefecture,and Muli Autonomous County, etc.),Gansu Province(21 counties/cities, 74.9×10 3 km 2), and Southern Xinjiang Uygur Autonomous Region (about 12 counties/cities, 313.0×10 3 km 2).

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[56]
Zorrilla-Miras P, Palomo I, Gomez-Baggethun Eet al., 2014. Effects of land-use change on wetland ecosystem services: A case study in the Donana marshes (SW Spain).Landscape and Urban Planning, 122: 160-174.Land-use change is a major driver behind the loss of ecosystem services. We assessed changes in ecosystem services from land-use conversions during the period 1918 2006 in the Do ana marshland and estuary in southwestern Spain, one of the largest European wetlands. We contrasted those results with social perceptions of ecosystem services trends using two techniques (expert judgment by a multidisciplinary scientific panel and semi-structured interviews of locals and visitors). The results show that by 2006, (1) 70.5% of the natural or semi-natural land covers had been converted to intensive agriculture and other mono-functional uses, hampering the performance of regulating services and (2) 31% of the wetland area had been strictly protected, affecting cultural and provisioning services. Our results show that land-use changes have led to a polarized territorial matrix exhibiting fundamental trade-offs in ecosystem service supply, where provisioning services produced for exportation and sale in the market, such as cash crops and fiber, have been enhanced at the expense of regulating services, such as hydrological regulation, flood buffering, and habitats for species and specific cultural and provisioning services used traditionally by the locals.

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