多情景模拟下县域生境质量时空演变预测——以桃源县为例

doi:10.12302/j.issn.1000-2006.202212038

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南京林业大学学报（自然科学版） ›› 2024, Vol. 48 ›› Issue (6): 201-209.doi: 10.12302/j.issn.1000-2006.202212038

多情景模拟下县域生境质量时空演变预测——以桃源县为例

杨宇萍¹(), 陈彩虹¹^,^*(), 佘济云¹, 林楚璇², 肖芬¹, 陈楚琳³

1.中南林业科技大学林学院,湖南长沙 410004
2.华中农业大学公共管理学院,湖北武汉 430070
3.中南林业科技大学风景园林学院,湖南长沙 410004

收稿日期:2022-12-28 修回日期:2023-05-28 出版日期:2024-11-30 发布日期:2024-12-10
通讯作者: *陈彩虹(chencaihong056@163.com),教授。
作者简介:
杨宇萍(yangyuping0130@163.com)。
基金资助:
湖南省自然科学基金项目(2022JJ40875)

Prediction of the spatiotemporal evolution of county habitat quality under multi-scenario simulation: a case of Taoyuan County

YANG Yuping¹(), CHEN Caihong¹^,^*(), SHE Jiyun¹, LIN Chuxuan², XIAO Fen¹, CHEN Chulin³

1. School of Forestry, Central South University of Forestry and Technology, Changsha 410004, China
2. College of Public Administration, Huazhong Agricultural University, Wuhan 430070, China
3. School of Landscape Architecture, Central South University of Forestry and Technology, Changsha 410004, China

Received:2022-12-28 Revised:2023-05-28 Online:2024-11-30 Published:2024-12-10

1. 多情景模拟下县域生境质量时空演变预测——以桃源县为例.zip(12106KB)

摘要/Abstract

摘要：

【目的】探究不同发展情景下的县域生境质量分布格局,为区域生态保护和社会经济可持续发展提供保障。【方法】以湖南省常德市桃源县为例,结合GeoSOS-FLUS模型与InVEST模型预测耕地保护情景(CPS)、生态保护情景(EPS)和经济建设情景(ECS)下的土地利用和生境质量时空演变格局,并借助地理探测器探测生境质量空间差异的影响因素。【结果】①2000—2020年,桃源县土地利用变化总体表现为草地、耕地、林地规模逐渐减少,建设用地持续扩张;生境质量呈下降趋势,低生境质量面积占比逐年升高。②2035年桃源县在3种情景下的生境质量均值从大到小为EPS(0.818 7)>CPS(0.817 9)>ECS(0.817 3);在ECS下,林地面积实现正增长,高生境质量区域减少幅度放缓,建设用地扩张对生态的破坏得到最大程度遏制;在CPS下,较低生境质量面积占比达到28.07%;在ECS下,低生境质量区域面积占比2.07%,呈持续增长趋势。③地形因子是影响桃源县生境质量空间分布的主要因素,其次为GDP与人口密度。【结论】在县域未来发展中,可考虑优化生态用地空间布局,鼓励发展生态农业,合理控制建设用地增量,提高生态稳定性,促进国土空间高质量发展。

关键词: 多情景模拟, 生境质量, 碳储量, 土地利用, GeoSOS-FLUS模型, InVEST模型, 湖南桃源县

Abstract:

【Objective】This study aims to explore the distribution patterns of habitat quality in county-level areas under different development scenarios to support regional ecological protection and socio-economic sustainable development.【Method】Using Taoyuan County as a case study, we applied the GeoSOS-FLUS model and the InVEST model to simulate the spatial-temporal evolution of land use and habitat quality under three scenarios: cultivated land protection scenario (CPS), ecological protection scenario (EPS), and economic construction scenario (ECS). We also analyzed the factors influencing spatial variations in habitat quality using Geographic Detectors.【Result】From 2000 to 2020, land use changes in Taoyuan County included a gradual decrease in grassland, cultivated land, and woodland, while construction land expanded continuously. Habitat quality declined, with a yearly increase in the proportion of low habitat quality areas. By 2035, the average habitat quality values under the three scenarios were ranked as follows: EPS (0.818 7)>CPS (0.817 9)>ECS (0.817 3). Under EPS, woodland area increased positively, the reduction in high habitat quality areas slowed, and ecological damage from construction land expansion was minimized. Under CPS, 28.07% of the area had low habitat quality. Under ECS, 2.07% of the area had low habitat quality, which showed a continuous increase. Topographic factors were the primary determinants of habitat quality distribution in Taoyuan County, followed by GDP and population density.【Conclusion】Future county development should consider optimizing the spatial layout of ecological land, promoting ecological agriculture, controlling construction land expansion, improving ecological stability, and advancing high-quality land space development.

Key words: multi-scenario simulation, habitat quality, carbon storage, land use, GeoSOS-FLUS model, InVEST model, Taoyuan County of Hunan Province

中图分类号:

F301.2
X826

杨宇萍,陈彩虹,佘济云,等. 多情景模拟下县域生境质量时空演变预测——以桃源县为例[J]. 南京林业大学学报（自然科学版）, 2024, 48(6): 201-209.

YANG Yuping, CHEN Caihong, SHE Jiyun, LIN Chuxuan, XIAO Fen, CHEN Chulin. Prediction of the spatiotemporal evolution of county habitat quality under multi-scenario simulation: a case of Taoyuan County[J].Journal of Nanjing Forestry University (Natural Science Edition), 2024, 48(6): 201-209.DOI: 10.12302/j.issn.1000-2006.202212038.

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情景 scenarios	各地类权重weight of land use type
情景 scenarios	Ⅰ	Ⅱ	Ⅲ	Ⅳ	Ⅴ	Ⅵ
耕地保护情景CPS	1.0	0.6	0.6	0.2	0.6	0.2
生态保护情景EPS	0.4	0.7	0.7	0.6	0.2	0.2
经济建设情景ECS	0.7	0.6	0.3	0.2	0.8	0.2

地类 land use type	耕地保护情景CPS						生态保护情景EPS						经济建设情景ECS
地类 land use type	Ⅰ	Ⅱ	Ⅲ	Ⅳ	Ⅴ	Ⅵ	Ⅰ	Ⅱ	Ⅲ	Ⅳ	Ⅴ	Ⅵ	Ⅰ	Ⅱ	Ⅲ	Ⅳ	Ⅴ	Ⅵ
Ⅰ	1	0	0	0	1	0	1	1	1	1	1	1	1	1	1	1	1	1
Ⅱ	1	1	1	1	0	1	0	1	1	1	0	0	1	1	1	1	0	1
Ⅲ	1	1	1	1	1	1	0	1	1	1	0	0	1	1	1	1	1	1
Ⅳ	0	1	1	1	1	1	0	1	1	1	0	0	0	1	1	1	0	1
Ⅴ	0	0	0	0	1	1	0	0	0	0	1	1	0	0	0	0	1	1
Ⅵ	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1

威胁因子 threat factor	最大影响距离/km max_distance	权重 weight	模型 modle
耕地cultivated land	4	0.6	线性
道路road	3	0.6	线性
城镇用地town land	8	1.0	指数

地类 land use type	生境适宜度 habitat-like suitability	耕地 cultivated land	道路 roads	城镇用地 town land
林地woodland	1.00	0.70	0.60	0.70
草地meadow	0.70	0.50	0.35	0.60
耕地cultivated land	0.50	0.30	0.30	0.50
水域water body	0.90	0.70	0.60	0.80
建设用地construction land	0	0	0	0
未利用地unused land	0.30	0.10	0.10	0.20

2000	2020
2000	草地 meadow	耕地 cultivated land	建设用地 construction land	林地 woodland	水域 waterbody	未利用地 unused land	总计 total	转出总计 roll-out total
草地meadow	11 159.10	165.87	26.91	1 052.10	53.10	0	12 457.08	1 297.98
耕地cultivated land	153.81	119 213.91	2 421.63	5 622.30	1 242.90	0.09	128 654.64	9 440.73
建设用地construction land	0.90	489.24	3 281.94	90.90	51.30	0.00	3 914.28	632.34
林地woodland	518.13	5 199.30	1 578.33	281 312.37	720.63	1.80	289 330.56	8 018.19
水域water body	35.37	473.31	75.06	546.66	8 691.21	0.90	9 822.51	1 131.30
未利用地unused land	0	0	0	1.35	0.45	53.10	54.90	1.80
转入总计roll-in totals	708.21	6 327.72	4 101.93	7 313.31	2 068.38	2.79		20 522.34
总计total	11 867.31	125 541.63	7 383.87	288 625.68	10 759.59	55.89	444 233.97	-

多情景模拟下县域生境质量时空演变预测——以桃源县为例

Prediction of the spatiotemporal evolution of county habitat quality under multi-scenario simulation: a case of Taoyuan County

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生境质量等级 habitat quality grade	2000年		2010年		2020年
生境质量等级 habitat quality grade	面积/hm² area	比例/% proportion	面积/hm² area	比例/% proportion	面积/hm² area	比例/% proportion
低low	3 933.39	0.89	5 917.22	1.33	7 408.44	1.67
较低lower	128 671.27	28.96	126 627.70	28.50	125 551.50	28.26
中等medium	12 453.91	2.80	12 136.51	2.73	11 860.56	2.67
较高higher	53 111.85	11.96	54 097.80	12.18	52 005.44	11.71
高high	246 063.56	55.39	245 454.74	55.25	247 408.02	55.69

生境等级 habitat level	生态保护情景EPS	耕地保护情景CPS	经济建设情景ECS
低low	1.94	1.90	2.07
较低lower	27.95	28.07	28.00
中等medium	2.67	2.62	2.60
较高higher	12.50	12.56	12.49
高high	54.94	54.77	54.85

因子 factor	X₁	X₂	X₃	X₄	X₅	X₆	X₇	X₈
X₁	0.332 6
X₂	0.403 0	0.274 9
X₃	0.375 1	0.362 8^*	0.087 6
X₄	0.346 4	0.350 7	0.306 3	0.232 8
X₅	0.352 3^*	0.301 9^*	0.149 1^*	0.268 7^*	0.016 6
X₆	0.353 9^*	0.309 3	0.203 9	0.261 8	0.125 8^*	0.072 2
X₇	0.421 0	0.401 3	0.354 3	0.367 7	0.314 0^*	0.318 6	0.280 6
X₈	0.430 6	0.409 6	0.367 4	0.376 7	0.330 9^*	0.340 0	0.302 3	0.294 8

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