Journal of Geographical Sciences ›› 2022, Vol. 32 ›› Issue (10): 1867-1885.doi: 10.1007/s11442-022-2027-0
• Research Articles • Next Articles
LI Jiahui1,2(), HUANG Lin1,*(
), CAO Wei1
Received:
2022-05-16
Accepted:
2022-06-27
Online:
2022-10-25
Published:
2022-12-25
Contact:
HUANG Lin
E-mail:lijh.19s@igsnrr.ac.cn;huanglin@igsnrr.ac.cn
About author:
Li Jiahui (1997-), Master Candidate, specialized in remote sensing of ecology and GIS. E-mail: lijh.19s@igsnrr.ac.cn
Supported by:
LI Jiahui, HUANG Lin, CAO Wei. An influencing mechanism for ecological asset gains and losses and its optimization and promotion pathways in China[J].Journal of Geographical Sciences, 2022, 32(10): 1867-1885.
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Table 1
Indexes and methods of ecological asset accounting at the county level
Asset category | Primary indicator | Secondary indicator | Accounting method | Indicator and parameter description |
---|---|---|---|---|
Stock assets | Area of ecological resource assets | Asset types | Ranking of the proportional area of forest, farmland, grassland, wetland, and desert ecological resource | Category I: Farmland, farmland-forest-wetland, farmland-forest-grassland, farmland-forest, farmland-grassland, farmland-wetland; Category II: Forest, forest-farmland-grassland, forest-farmland, forest-grassland; Category III: Grassland, grassland-farmland, grassland-forest, grassland-desert; Category IV: Desert; Category V: Others |
Quality of ecological resources | Quality index | | EQij is the ecological asset quality of the j-th pixel in the i-th ecosystem asset type, and NPPij is the NPP (kgC·ha-1) of it. MNPPi is the highest NPP nationwide of the i-th type ecological asset (kgC·ha-1). EAQIk is the ecological asset quality index of the k-th county. Ski is the area of the i-th type of ecological asset in the k-th county (ha). Sk is the total area of the ecological assets in the k-th county (ha). | |
Flow assets | Supply services | Food supply | | FS is the grain outputs (t·a-1). Pf is the unit price, and the average selling price of rice, wheat, and corn is 2194 yuan·t-1. |
Raw material supply | | PSj is the outputs of the j-th product (t·a-1), and Ppj is its unit price. The average selling prices of cotton and oil crops are 14,564 yuan·t-1 and 6452 yuan·t-1, respectively. | ||
Regulation services | Sedimentation reduction | | SC is the soil conservation amount (t·a-1). Msc is the soil water erosion amount under the actual surface cover condition (t·ha-1·a-1), while Msce is the soil water erosion amount under the extremely degraded state (t·ha-1·a-1). A is the area of the ecosystem (ha); ρs is the soil bulk density (t·m-3) (Han et al., (DB11/T 659-2018). | |
Dust pollution reduction | | SF is the amount of sand fixation (t·a-1). Msf is the amount of soil wind erosion under the actual surface cover condition (t·ha-1·a-1), and Msfe is the amount of soil wind erosion under the extremely degraded state (t·ha-1·a-1). A is the area of the ecosystem (ha). PSF is the cost of dust pollution reduction, which is 150 yuan·t-1 (DB11/T 659-2018). | ||
Soil fertility maintenance | & {{V}_{NR}}=\underset{i=1}{\overset{m}{\mathop \sum }}\,(SC+SF) \\ & \times {{C}_{i}}\times {{T}_{i}}\times {{P}_{ci}} \end{align}$ | Ci is the content (%) of soil nitrogen, phosphorus, potassium, and organic matter. Ti is the conversion factors for nitrogen, phosphorus, and potassium to urea, superphosphate, and potassium chloride, which are 2.164, 4.065, and 1.923, respectively (Han et al., yuan·t-1, respectively (DB11/T 659-2018). | ||
Water regulation | | WC is the precipitation stored by ecosystems (t·a-1). A is the area of the ecosystem (ha). J0 is the annual precipitation (mm). K is the ratio of runoff to the total precipitation. R0 is the runoff yield ratio of the bare land, and Rr is the runoff yield ratio of the ecosystem. PWR is the unit storage cost of the reservoir, which is 6.1107 yuan·m-3 (DB11/T 659-2018). | ||
Water purification | | PWP is the price of sewage purification, which is 0.95 yuan·t-1. |
Table 2
Identification criteria and calculation methods of the drivers and their impact degree of ecological asset gains and losses
slopeobs | slopecc | slopeha | Impact degree of climate change (%) | Impact degree of human activities (%) | Explanation |
---|---|---|---|---|---|
> 0 | > 0 | > 0 | | | The combined effect of climate change and human activities have led to the gains of an ecological asset |
> 0 | < 0 | 100 | 0 | Climate change has led to the gains of an ecological asset | |
< 0 | > 0 | 0 | 100 | Human activities have led to the gains of an ecological asset | |
< 0 | < 0 | < 0 | | | The combined effect of climate change and human activities have led to the losses of an ecological asset |
< 0 | > 0 | 100 | 0 | Climate change has led to the losses of an ecological asset | |
> 0 | < 0 | 0 | 100 | Human activities have led to the losses of an ecological asset |
Table 3
Classification methods of optimization and promotion pathways of ecological assets at the county level in China
Optimization and promotion type | Composition | Criteria |
---|---|---|
Climate change adaptation | IAb, IIAb, IIIAb, IVAb, ICb, IICb, IIICb | Counties dominated by farmland, forest and grassland ecological assets with balance or gain trend from 1990 to 2018, which were mainly driven by climate change |
Climate change mitigation | IBb, IIBb, IIIBb, IVBb | Counties dominated by farmland and forest ecological assets with loss trend from 1990 to 2018, which were mainly driven by climate change |
Ecological resource restoration | IBa, IIBa, IIIBa, IVBa | Counties dominated by farmland and forest ecological assets with loss trend from 1990 to 2018, which were mainly driven by human activities |
Ecological resource conservation | IAa, IIAa, IIIAa, IVAa | Counties dominated by farmland, forest and grassland ecological assets as the main asset types with gain trend, which were mainly driven by human activities |
Ecological resource management | ICa, IICa, IIICa | Counties dominated by farmland and forest ecological assets with balance trend from 1990 to 2018, which were mainly driven by human activities |
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