Biodiv Sci ›› 2022, Vol. 30 ›› Issue (4): 21425. DOI: 10.17520/biods.2021425
Special Issue: 青藏高原生物多样性与生态安全
• Original Papers: Ecosystem Diversity • Previous Articles Next Articles
Wen Pan1, Yunhui Liu1, Zehao Wu1, Zengli Liu2, Wenxuan Han1,*(), Zhenrong Yu1
Received:
2021-10-25
Accepted:
2022-01-20
Online:
2022-04-20
Published:
2022-03-16
Contact:
Wenxuan Han
Wen Pan, Yunhui Liu, Zehao Wu, Zengli Liu, Wenxuan Han, Zhenrong Yu. Simulation of changes in land use distribution and biodiversity under different development scenarios in Qinghai Province[J]. Biodiv Sci, 2022, 30(4): 21425.
Fig. 1 Conception of scenario design in this study based on trade-offs between nature conservation and economic development. The “1:1” dashed line denotes the specific scenario under which nature conservation and economy development are kept in a strictly balanced way (i.e., the degrees of both parameters remain exactly identical). The solid parts of the four curves represent the possible change trajectories of natural conservation and economic development of the respective scenarios by 2030 and 2050, respectively; and the densely dashed lines with arrows represent their potential trends after 2050. The evolutional degree of certain scenario goal is limited; when the development of one goal is at or near its peak, it tends to develop another goal. The two dash-dotted red lines represent the isolines formed by the state points of (economic development, nature conservation) of all possible scenarios in 2030 or 2050. Gray, brown, blue and green lines stand for the possible pathways of the four scenarios: Baseline scenario, Intelligent Qinghai, Harmonious Qinghai and Beautiful Qinghai.
Box 1 四个发展情景的设计思路和相关描述 (1)基线情景 基本描述: 该情景反映青海省社会、经济和环境等的自然变化情况, 主要目标为对现有的土地利用方式不做任何改进, 维持已有的自然保护地面积不变, 并按照现有趋势(2015-2020年)发展下去。 实现途径: 根据2015-2020年的土地利用类型数据, 运用马尔科夫链算法, 递推模拟出2030年、2050年土地利用类型的像元数量; 土地利用转换矩阵、邻域权重设置与2015-2020年一致。 愿景: 人口持续增加, 经济快速发展, 由于不限制进一步的土地开发, 生物多样性的恢复速度缓慢。 (2)美丽青海 基本描述: 该情景主要目标是最大限度地恢复自然生态系统, 扩大自然保护地的面积, 强调生物多样性的保护和恢复, 故命名为美丽青海。 实现途径: 限制低、中干扰湿地向高干扰湿地转换, 增大其邻域权重, 从而逐步扩大天然湿地面积, 恢复湿地的生物多样性; 限制森林向其他类型转换, 增大其邻域权重, 加强森林保护, 扩大森林面积; 减小常规农田邻域权重, 逐步缩减常规农田面积, 将农田转换成为草地、林地、湿地等土地利用类型, 增大优质农田的邻域权重, 适度发展基于自然生态的特色有机种植业; 降低草地的利用强度, 减少高强度草地的邻域权重, 育林、育草与禁牧、休牧、轮牧相结合; 限制其他土地利用类型向建设用地转换, 部分建设用地可转换为草地、人工湿地、优质农田, 城市规模逐渐变小。 愿景: 自然环境、人居环境质量提升, 生物多样性显著提高, 建设成生态文明高度发达的美丽青海。 (3)智慧青海 基本描述: 该情景主要目标是充分利用最新科技成果, 高效和可持续地开发利用自然生态系统对人类的各项服务功能, 最大限度地提高资源利用效率和产业效益, 从而满足社会经济的飞速发展, 故命名为智慧青海。 实现途径: 与美丽青海情景相比, 限制优质农田向湿地、森林、草地的转换, 扩大优质农田面积, 发展集约农业, 大面积应用与推广集约化和智能化的粮食生产系统; 限制建设的转换, 城市布局以重点城市群为中心, 城区更加紧凑、城乡间的连通性趋于更高, 城市规模较其他情景略有扩大; 高干扰湿地的邻域权重增加, 这是由于科技创新、科技成果转化模式逐渐成熟, 城市湿地(高强度湿地)的建设加大, 从而净化城市污水、去除污染物。 愿景: 区域城市化加大, 发挥青海气候冷凉干燥、清洁能源丰富等优势, 集约式高科技农业、畜牧业获大面积推广。 (4)和谐青海 基本描述: 该情景主要目标是促进人与自然和谐发展, 实现各类资源的环境友好型优化利用, 故命名为和谐青海, 是折衷了美丽青海和智慧青海情景设计策略的一种规划方案。 实现途径: 与美丽青海情景相比, 限制优质农田向其他土地利用类型的转换, 限制建设用地向常规农田转换, 适度发展农业和城市经济; 与智慧青海相比, 允许部分建设用地向林地、草地转换, 减少零散建设用地的面积, 城市趋于紧凑, 建设用地面积少于和谐青海情景, 多于美丽青海情景; 不提倡农业集约化发展, 而是提倡基于民间传统农艺和地方知识来指导农牧业和渔业的土地利用和管理, 依托日照、气候、种质等优势, 发展高质量草原牧场和农田。 愿景: 生态系统可持续发展, 生态系统服务功能增强, 实现自然生态单元和人类社会管理单元、自然生态承载力和人类发展生产力的“两个协同”。 |
Box 1 四个发展情景的设计思路和相关描述 (1)基线情景 基本描述: 该情景反映青海省社会、经济和环境等的自然变化情况, 主要目标为对现有的土地利用方式不做任何改进, 维持已有的自然保护地面积不变, 并按照现有趋势(2015-2020年)发展下去。 实现途径: 根据2015-2020年的土地利用类型数据, 运用马尔科夫链算法, 递推模拟出2030年、2050年土地利用类型的像元数量; 土地利用转换矩阵、邻域权重设置与2015-2020年一致。 愿景: 人口持续增加, 经济快速发展, 由于不限制进一步的土地开发, 生物多样性的恢复速度缓慢。 (2)美丽青海 基本描述: 该情景主要目标是最大限度地恢复自然生态系统, 扩大自然保护地的面积, 强调生物多样性的保护和恢复, 故命名为美丽青海。 实现途径: 限制低、中干扰湿地向高干扰湿地转换, 增大其邻域权重, 从而逐步扩大天然湿地面积, 恢复湿地的生物多样性; 限制森林向其他类型转换, 增大其邻域权重, 加强森林保护, 扩大森林面积; 减小常规农田邻域权重, 逐步缩减常规农田面积, 将农田转换成为草地、林地、湿地等土地利用类型, 增大优质农田的邻域权重, 适度发展基于自然生态的特色有机种植业; 降低草地的利用强度, 减少高强度草地的邻域权重, 育林、育草与禁牧、休牧、轮牧相结合; 限制其他土地利用类型向建设用地转换, 部分建设用地可转换为草地、人工湿地、优质农田, 城市规模逐渐变小。 愿景: 自然环境、人居环境质量提升, 生物多样性显著提高, 建设成生态文明高度发达的美丽青海。 (3)智慧青海 基本描述: 该情景主要目标是充分利用最新科技成果, 高效和可持续地开发利用自然生态系统对人类的各项服务功能, 最大限度地提高资源利用效率和产业效益, 从而满足社会经济的飞速发展, 故命名为智慧青海。 实现途径: 与美丽青海情景相比, 限制优质农田向湿地、森林、草地的转换, 扩大优质农田面积, 发展集约农业, 大面积应用与推广集约化和智能化的粮食生产系统; 限制建设的转换, 城市布局以重点城市群为中心, 城区更加紧凑、城乡间的连通性趋于更高, 城市规模较其他情景略有扩大; 高干扰湿地的邻域权重增加, 这是由于科技创新、科技成果转化模式逐渐成熟, 城市湿地(高强度湿地)的建设加大, 从而净化城市污水、去除污染物。 愿景: 区域城市化加大, 发挥青海气候冷凉干燥、清洁能源丰富等优势, 集约式高科技农业、畜牧业获大面积推广。 (4)和谐青海 基本描述: 该情景主要目标是促进人与自然和谐发展, 实现各类资源的环境友好型优化利用, 故命名为和谐青海, 是折衷了美丽青海和智慧青海情景设计策略的一种规划方案。 实现途径: 与美丽青海情景相比, 限制优质农田向其他土地利用类型的转换, 限制建设用地向常规农田转换, 适度发展农业和城市经济; 与智慧青海相比, 允许部分建设用地向林地、草地转换, 减少零散建设用地的面积, 城市趋于紧凑, 建设用地面积少于和谐青海情景, 多于美丽青海情景; 不提倡农业集约化发展, 而是提倡基于民间传统农艺和地方知识来指导农牧业和渔业的土地利用和管理, 依托日照、气候、种质等优势, 发展高质量草原牧场和农田。 愿景: 生态系统可持续发展, 生态系统服务功能增强, 实现自然生态单元和人类社会管理单元、自然生态承载力和人类发展生产力的“两个协同”。 |
Fig. 3 Changes of spatial distribution of land use under different scenarios in Qinghai Province in 2030 (a-d) and 2050 (e-h). See Appendix 2 for the description of each land use type/disturbance intensity.
Fig. 4 Changes of land use types/disturbance intensities from 2020-2030 (a) and 2020-2050 (b) in Qinghai Province under different scenarios. See Appendix 2 for the description of each land use type/disturbance intensity.
情景 Scenarios | 年份 Year | MSA值 MSA value | |
---|---|---|---|
目标阈值 Target value | 模拟结果 Simulation result | ||
现状 Status quo | 2020 | - | 0.863 |
基线情景 Baseline scenario | 2030 | - | 0.881 |
2050 | - | 0.878 | |
美丽青海 Beautiful Qinghai | 2030 | 0.89 | 0.890 |
2050 | 0.91 | 0.910 | |
智慧青海 Intelligent Qinghai | 2030 | 0.89 | 0.886 |
2050 | 0.89 | 0.896 | |
和谐青海 Harmonious Qinghai | 2030 | 0.89 | 0.889 |
2050 | 0.89 | 0.900 |
Table 1 Provincial MSA values of different scenarios in Qinghai Province. MSA means mean species abundance. See Equation 2 for the definition of regional MSA.
情景 Scenarios | 年份 Year | MSA值 MSA value | |
---|---|---|---|
目标阈值 Target value | 模拟结果 Simulation result | ||
现状 Status quo | 2020 | - | 0.863 |
基线情景 Baseline scenario | 2030 | - | 0.881 |
2050 | - | 0.878 | |
美丽青海 Beautiful Qinghai | 2030 | 0.89 | 0.890 |
2050 | 0.91 | 0.910 | |
智慧青海 Intelligent Qinghai | 2030 | 0.89 | 0.886 |
2050 | 0.89 | 0.896 | |
和谐青海 Harmonious Qinghai | 2030 | 0.89 | 0.889 |
2050 | 0.89 | 0.900 |
Fig. 5 Patterns of MSA under different scenarios in Qinghai Province in 2030 (a-d) and 2050 (e-h). MSA means mean species abundance. See Equation 2 for the definition of regional MSA.
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