Ecosystem Services Assessment, Trade-Off and Bundles in the Yellow River Basin, China

: 7 Understanding ecosystem services (ESs) and their interactions will help to formulate effective 8 and sustainable land use management programs.This paper evaluates the water yield (WY), soil 9 conservation (SC), carbon storage (CS) and habitat quality (HQ), taking the Yellow River Basin as 10 the research object, by adopting the InVEST (Integrated Valuation of Ecosystem Services and 11 Trade Offs) model. The Net Primary Productivity (NPP) was evaluated by CASA 12 (Carnegie - Ames - Stanford approach) model, and the spatial distribution map of five ESs were 13 drawn, the correlation and bivariate spatial correlation were used to analyze the trade - off synergy 14 relationships between the five ESs and express them spatially. The results show that NPP and HQ, 15 CS and WY are trade - offs relationship, and other ecosystem services are synergistic. The trade - off 16 synergy shows obvious spatial heterogeneity. Driven by different factors, the leading ecological 17 function services in the Yellow River Basin can be divided into three areas, and WY and SC 18 service leading functional areas are mainly distributed in HQ and CS service leading functional 19 areas and NPP service leading functional areas.The results of functional bundles are obviously 20 affected by natural conditions such as land use/cover types and climate in the Yellow River Basin, 21 which can provide the basis for the Yellow River Basin to regulate ESs and maximize benefits. 22


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ESs are the material basis and environmental conditions for the survival and development of 26 human, which can be divided into three categories: supply services, regulation services, and social 27 and cultural services. They are bridges to connect natural ecosystems and human well-being 28 (MEA,2005a). The sustainable supply is of great significance to the sustainable development of 29 districts, countries and even the whole world (Fu et al., 2014). In recent years, ESs have gradually functions such as water conservation, wind protection, sand fixation, and biological diversity 94 protection, which play a very significant role in maintaining regional ecological security. 95 Based on this, this study takes the year 2018 as a cross-section to analyze the spatial 96 trade-offs among the five ESs and their association with social ecosystems. First, it quantitatively 97 calculates the spatial distribution pattern of WY, CS, SC, HQ, and NPP, calculates the correlation 98 coefficient between ESs through correlation analysis and uses SOM to classify the spatial 99 distribution of ESs clusters. Then the random forest model is used to explore the impact of 100 social-ecological influencing factors on ESs, and the SOM method is used to classify the clusters 101 of social-ecological factors. Finally, it distinguishes the relationship between ES clustering and 102 social-ecological factor clustering through overlay analysis, to explore the response mechanism of 103 ESs to the social-ecological system. It is expected to lay the foundation for the ecology and 104 environmental protection of the basin. 105 2. Study area 106 The Yellow River originates from the Yogu Zonlie Basin at the northern foot of the Bayan 107 Har Mountain on the Qinghai-Tibet Plateau. It flows through Qinghai, Sichuan, Gansu, Ningxia, 108 Inner Mongolia, Shanxi, Shaanxi, Henan, and Shandong provinces, and injects into the Bohai Sea 109 in Kenli County, Shandong Province. The main stream has a total length of 5464 kilometers and a 110 drop of 4480 meters (Fig.1). The Yellow River Basin is located between 96°-119°east longitude 111 and 32°-42°north latitude, with a length of about 1,900 kilometers from the east to the west 112 and a width of about 1,100 kilometers from the north to the south. The area of the basin is 795,000 113 square kilometers (including the internal flow area of 42,000 square kilometers). Above Hekou 114 Town, it is the upper reaches of the Yellow River, with a river course of 3,472 kilometers and a 115 basin area of 428,000 square kilometers; from Hekou Town to Taohuayu, it is the middle reaches, 116 with a river course of 1,206 kilometers and a basin area of 344,000 square kilometers; below 117 Taohuayu, it is the lower reaches, with a river course of 786 kilometers and a basin area of only 118 23,000 square kilometers. In the Yellow River Basin, there is a vast area, numerous mountains, 119 great differences in height between the east and the west, and great differences in landforms 120 between regions. The climate of different regions in the basin differs significantly. In the Yellow 121 River Basin, the sunlight is sufficient and the solar radiation is strong, and the sunshine conditions 122 belong to sufficient areas across the country. The annual sunshine hours generally reach 123 2000-3300 hours. There are big seasonal differences in the Yellow River Basin. The annual 124 precipitation in most areas of the basin is between 200 and 650 mm, and that of the upper reaches 125 of the southern and lower reaches is more than 650 mm, especially the northern slope of the 126 Qinling Mountains in the south, which is heavily affected by topography. Generally, it can reach 127 700-1000 mm, and it gradually increases from the northwest to the southeast. The precipitation is 128 unevenly distributed, and the ratio of rainfall between the north and the south is greater than 5. 129 According to the national water resources distribution, the Yellow River basin can be divided into In this study, we use multi-source data sets to evaluate ESs in space, including land use/cover 136 data sets, satellite image data sets, meteorological data sets, soil data sets, statistical data sets and 137 related auxiliary data sets. Detailed descriptions of data sources are shown in Table 1  (4) 154 In the formula, NPP, APAP, ε respectively represent the net primary productivity of 156 vegetation (gc·m -2 ), the absorbed photosynthetically active radiation (MJ·m -2 ) and the actual light 157 utilization rate (g c·MJ -1 ). SOL and FPAR are respectively the total solar radiation (MJ·m -2 ) and 158 the absorption ratio of photosynthetically active radiation by vegetation; the constant 0.5 159 represents the solar radiation rate used by vegetation; SRmin is 1.08, and SRmax is related to  This study evaluates the water yield by adopting the InVEST model water production module, 166 which is based on the Budyko water-heat coupling balance hypothesis and the annual average 167 precipitation data, that is, the rainfall of each grid minus the actual evapotranspiration is the 168 annual water production Y(x) of each grid unit x in the study area (Sharp et al., 2018), the 169 calculation formula is: 170 In the formula, Yx is the average annual water production of grid x. Since the actual annual 176 evapotranspiration cannot be directly measured and obtained, the curve pair AETx/Px can be used 177 to approximate calculations. The Rx value is dimensionless and is the dryness index of grid x. It 178 can be calculated by potential evapotranspiration and rainfall. wx is an empirical parameter used to 179 describe climate-soil properties, and can be calculated by the available water content of vegetation 180 and annual rainfall. AWCx is the available water content of vegetation, which is determined by soil 181 texture and effective soil depth and is used to determine the total amount of water stored and 182 provided by the soil for plant growth. Z is called the Zhang coefficient (Zhang et al., 2001), which 183 is an empirical constant, which represents the parameters of seasonal rainfall distribution and 184 rainfall depth. For areas dominated by winter rainfall, the Z value is close to 10, while for humid 185 areas where rainfall is evenly distributed and areas dominated by summer rainfall, the Z value is 186 close to 1. According to the results of multiple simulations, the Z value is finally determined to be 187 3.6. ET0x is the internal potential evapotranspiration in grid x, which reflects the 188 evapotranspiration capacity determined by weather and climate conditions. Since the data of 189 potential evapotranspiration are difficult to obtain, so they are usually calculated by the 190 temperature method, the radiation method and the comprehensive method. InVEST model uses the  to calculate the carbon storage of the study area. The calculation formula for the total carbon 205 density of each land-use type is as follows: 206 In the formula: Ctot is the total carbon storage (t·hm -2 ). Cabove、Cbelow、Csoil、Cdead are the 208 above-ground biological carbon storage (t·hm -2 ), the underground biological carbon storage 209 (t·hm -2 ), the soil carbon storage (t·hm -2 ), and the dead organic carbon storage (t·hm -2 ). 210 Based on the carbon density and land use data of various regions, the formula for calculating 211 the carbon storage of the ecosystem in the basin is as follows: 212 Where: i is the average carbon density of each land use type. Ai is the area of the land-use  According to regional similarity, the desirability of results, and other principles, it can generate a 217 carbon pool table. 218

Soil Conservation (SC) 219
In this paper, the amount of soil conservation includes two parts: the amount of erosion 220 reduction and the amount of sediment interception based on the calculating principle of the soil 221 conservation module in the InVEST model. The former refers to the reduction of potential erosion 222 land of each block, expressed as the potential erosion and actual erosion difference. The latter 223 refers to the retention of sediment from the upslope by the block, which is expressed as the 224 product of the amount of sediment and the efficiency of sediment retention. The model calculation 225 formula is as follows: 226 In the formula: SEDRETx, RKLSx, USLEx, SEDRx and USLEy are respectively the soil 231 conservation amount of grid x, the potential soil erosion amount, the actual erosion amount after 232 considering management and engineering measures, the sediment retention amount, and the actual 233 In the formula: Qxj is equal to the habitat quality index of grid x in land use j. Hj refers to the 248 habitat suitability of habitat type j, with a value range of 0-1. Dxj refers to the habitat degradation 249 index. R is the number of threat factors. k is the half-saturation constant, which is generally 1/2 of 250 the maximum value of habitat degradation. z is the normalized constant, which is usually set to 2.5 251 (Sharp et al., 2018). 252 The parameters that need to be input in this module mainly include land-use type maps, 253 main habitat threat factors, weights of threat source factor and influence distances, and data such

Global spatial autocorrelation 285
Moran's I index shows the similarity ratio of unit attribute values in the spatial adjacent areas. 286 In this paper, it analyzed the spatial correlation between water yield and rainfall of each grid cell 287 in the Yellow River Basin by GeoDA. The formula is in the following: 288

SOM method 309
The SOM is an unsupervised neural network method based on competitive learning 310 (Kohonen et al., 1989). It is composed of an input layer and an output layer (also called a 311 competition layer). The input layer is used to receive input training samples, and the neurons in 312 the output layer are generally arranged in a two-dimensional array, and each neuron in the two 313 layers is bidirectionally connected. The SOM classifies the set of input patterns by finding the 314 optimal weight vector, that is, the best matching neuron. The steps of the SOM algorithm are: 315 initializing each weight vector, that is, assigning small random numbers to each weight vector in 316 the output layer and normalize it; finding the winning neuron of the input data; adjusting the 317 weight vector in the winning neighborhood; repeatedly searching for the input data of the winning 318 neuron and subsequent steps until the iteration termination condition is met. 319   Basin, Xiaheyan to Shizuishan, Shizuishan to the north bank of Hekou Town, Shizuishan to the 497 south bank of Hekou Town, internal flow area, the right bank above Wubao, and the right bank 498 below Wubao. The regional areas account for 35.18% of the total area of the Yellow River Basin. 499

Results and Analysis
This area is an important functional area for habitat maintenance and carbon storage. There are 500 many types of land use/cover, which mostly are grassland and woodland. However, bare land and 501 sandy land are also distributed in the central area. Due to the large area and the distribution of 502 vegetation types, having high carbon density such as woodland and grassland, the CS is higher. At 503 the same time, due to there is a lower degree of accessibility by human activities in these areas 504 which are also far away from threat sources such as cultivated land and construction land, so HQ 505 is higher than that of in downstream areas. However, the WY service is low and 506 evapotranspiration capacity is strong in the area. It has the largest annual evaporation in the region 507 in this area, which can exceed 2500 mm at most. The insufficient precipitation in the middle 508 reaches leads to the lack and uneven distribution of water resources. In addition, the service 509 function of NPP is also extremely lower than that of other areas. Because this area is located in the 510 hinterland of the inland, it forms a natural landscape with a dominant arid and semi-arid 511 ecosystem. The vegetation structure is simple relatively and the productivity is low in this area 512 which is an extremely poor biomass area in the terrestrial ecosystem of the Yellow River Basin. It distributes in the Fenhe River Basin, the Weihe River from Baoji to Xianyang and below. 515 The regional area accounts for 25.47% of the total area of the Yellow River Basin. Comparing 516 with various ESs, it is found that the NPP service in this area has obvious advantages, so it is the 517 dominant functional area of NPP service. The terrain is relatively flat in these areas, and the 518 mainstream of the Yellow River and many tributaries pass through them. It is a temperate 519 monsoon climate with sufficient water and heat conditions, which is beneficial to vegetation 520 growth and restoration. The woodland coverage is higher in the Qinling Mountains, so the NPP is 521 higher. However, other services are low in this area, especially HQ. Due to the concentrated 522 distribution of arable land and construction land in this area, the habitat is fragmented, the 523 connectivity is reduced, and the distance to the threat factor is relatively small, resulting in low 524 HQ. The population below Xiaolangdi Huayuankou is dense, the land for economic construction 525 is concentrated, the vegetation coverage is extremely low, so the SC is small. synergistic relationship, that is to say, a complete habitat with low interference can offer a superior 553 environment for various organic substances, thereby promoting some adjustment service functions 554 . 555 This conclusion affirms the support function of HQ, and HQ is in a trade-off relationship 556 with NPP. There are high altitude and low temperature in the places with high HQ, which is not 557 conducive to the photosynthesis of vegetation. In downstream areas with high NPP, frequent 558 human activities lead to lower habitat quality. There is a trade-off relationship between CS and 559 NPP. Although both of these are carbon-related services and share a similar carbon cycle, CS 560 represents the stock of carbon and NPP represents the rate of carbon sequestration. There is an 561 opposite relationship between the two. This result is supported by the findings of Zhang et al. 562 (2010). In the Yellow River Basin, there is a wide range of east-west and north-south spans. It is a 563 transitional bundles between the east and the west in our country. The transition has an impact on 564 the barrier and differentiation of the region, resulting in differences in topography, landforms, and 565 climate, which will affect the ecosystem and will promote the difference in ES relationships. The seeds and soil bioremediation should be adopted to accelerate the restoration and reconstruction of 648 severely degraded grasslands, strengthen the protection of biodiversity, ensure the connectivity of 649 habitat, and improve environmental carrying capacity and water conservation capacity. In bundle 2, 650 it encompasses the entire Loess Plateau. In this area, there is not only low rainfall and uneven 651 distribution, but also heavy rainstorms, coupled with the loose structure of loess, so it is easy to 652 form soil erosion. From 1950, our country began to adopt measures such as slope management, 653 joint management of slope and gully, comprehensive consolidation of small watersheds, and 654 returning farmland to forests and grasslands to control serious soil erosion problems in this area. 655 In general, the currently implemented soil erosion control measures and projects in the Loess 656 Plateau have achieved significant ecological benefits, and the overall regional ESs have developed 657 in a healthy direction; however, the overall fragile characteristics of the Loess Plateau's ecological 658 environment have not been changed. Therefore, people should not only consider reducing soil 659 erosion and increasing the area of arable land for the management of this area, more importantly, 660 they should also improve landscape varieties and the living environment, optimize the economic 661 and industrial structure, and boost regional social and economic growth. Guided by the concept of 662 landscape, forests, fields, lakes and grasses as a living community, people should practice the 663 idea of "reinforcing the ditch and protecting the plateau in plateau areas, returning farmland to 664 forests and grasses on slopes, blocking trenches for land preparation, and fixing sand and restoring 665 shrubs and grasses in sandy areas". A comprehensive protection system for the plateau and ditch 666 head with water systems and roads as the framework of fields, roads, forests, villages, shelter 667 forests, etc. on the plateau and ditch should be formed to prevent the development of erosion ditch 668 on the plateau. A ditch slope protection system that focuses on vegetation restoration, and 669 combines engineering measures with forest, grass, and plant measures on the sloped surface is 670 formed to reduce the water erosion of the ditch slope. The Saying Gully Scouring Forest has 671 formed a gully protection system combining trench engineering and forest, grass and vegetation 672 measures to prevent gravitational erosion such as collapses, landslides, and gully bank expansion. The spatial distribution of the 5 ESs not only shows spatial heterogeneity, but also reflects 689 certain regional laws. The upper reaches of the basin show higher ES, especially WY, SC and HQ 690 are significantly higher than that of in the middle reaches and lower reaches of the Yellow River 691 basin, however ESs is generally lower in the middle reaches. 692 NPP has a synergistic relationship with CS, SC, and WY, and a trade-off relationship with 693 HQ. CS has a synergistic relationship with SC and HQ, and a trade-off relationship with WY. The 694 trade-off synergy relationship shows obvious spatial heterogeneity in space. The vegetation, soil, 695 animals and plants in the Yellow River Basin all show significant latitude zonality differences, 696 longitude differentiation, and natural laws such as vertical zonality and slope differentiation, 697 which promotes the high complexity and diversity of ESs in the Yellow River Basin, more 698 importantly, promotes the heterogeneity of space. 699 According to the spatial distribution and related relationships of the five ESs, the dominant 700 ecological function services in the Yellow River Basin can be divided into 3 bundles. Bundle 1 is 701 the dominant function area for WY and SC services, Bundle 2 is the dominant function area for 702 HQ and CS services, and Bundle 3 is the NPP service dominate function area.