基于生态重要性与敏感性的六盘山区生态保护修复分区

doi:10.12118/j.issn.1000-6060.2023.053

Abstract

Abstract:

Establishing a benign, healthy, and high-quality territorial space through systematic, all-regions, all-elements, and whole-process ecological restoration is crucial from the perspective of the life community of mountains, rivers, forests, farmland, lakes, grass, and sand. However, identification and zoning of ecological conservation and restoration areas are prerequisites for adopting differentiated ecological restoration and constructing a high-quality ecological security pattern for the territorial space, which in turn ensures a stable and healthy development of the regional ecosystem. Currently, guidance and method support for territorial spatial zoning are urgent needs for implementing systematic ecological conservation and restoration in Ningxia, China. The Liupan Mountain area in Ningxia, with its key ecological position and rich ecological resources, plays an irreplaceable role in maintaining regional ecological security. In this study, taking the Liupan Mountain area as the research region, we construct a comprehensive indicator system that views ecosystems from a two-dimensional perspective of “service-problem”. This system optimizes and streamlines the dimensions, scales, and indicators previously used, addressing past simplifications. Based on this framework, we employ mainstream ecological restoration zoning methods, such as the InVEST model, spatial overlay mapping, and comprehensive index weighting. We apply a grid-based unit scale to quantitatively evaluate the importance and sensitivity of ecological services, ultimately completing ecological conservation and restoration zones and clarifying ecological restoration strategies. The key results of this study include the following: (1) The highly important areas of ecological services account for 33.4%, presenting a “south-north” corridor extending from Liupan Mountain to Nanhua Mountain, along with a centralized distribution within the “Yuanzhou-Pengyang” county territory. They serve as the main suppliers of ecological functions and present opportunities for optimization and upgrading within the region. (2) The highly sensitive area of the ecosystem accounts for 32.0%, which is concentrated in the “Haiyuan-Xiji” county territory and the eastern region of Yuanzhou County. They represent the main areas of ecological function demand and are the focus of conservation and restoration efforts in the region. (3) The proportion of ecological reserve zones is 15.7%, which requires strict ecological protection and monitoring management to promote structural optimization and functional upgrading within the ecosystem. Meanwhile, the proportion of ecological restoration zones and conservation zones accounted for 17.7% and 26.1%, respectively. They require comprehensive efforts to improve ecological benefits and control the risk of ecological degradation, which are guided by soil erosion control and land desertification prevention. The proportion of ecological regulation zones is 40.5%, exploring a transformation path for comprehensive optimization and coordination of the development and conservation pattern of the territorial space, particularly in the context of the “two mountains” initiative. The results of this study provide important spatial guidance for systematic and differentiated ecological conservation and restoration, as well as for the formulation of policies and project layout within the territorial space of the Liupan Mountain area.

Key words: territorial space, ecological restoration, spatial distance index, InVEST model, Liupan Mountain area

BAO Yubin,HUANG Tao,WANG Yaozong,HU Sheng,LYU Lintao,TANG Yijuan,GU Jisheng. Zoning for ecological conservation and restoration in Liupan Mountain area based on ecological importance and sensitivity evaluation[J].Arid Land Geography, 2023, 46(11): 1778-1791.

Figures/Tables 12

Fig. 1

Fig. 2

Tab. 1

Methods for evaluating the importance of ecosystems"

生态系统服务	权重	评估模型/方法	基本原理及计算公式
生境维持	0.417	InVEST-Habitat Quality model	$Q x j = H j 1 - D z x j D z x j + k z$ 式中：Q_xj为土地利用类型j中栅格x的生境质量;D_xj为土地利用类型j中栅格x所受胁迫水平;k为半饱和常数，通常取D_xj最大值的一半;H_j为土地利用类型j的生境适合性;z为归一化常量^[30]。
产水服务	0.316	InVEST-Water Yield model	$Y j x = 1 - A E T x j P x × P x$ ， $A E T x j P x = 1 + ω x × R x j 1 + ω x × R x j + 1 / R x j$ ， $R x j = k × E T 0 P x$ 式中：Y_jx为土地利用类型j中栅格x的年产水量（mm）;P_x为栅格单元x的年均降雨量（mm）;AET_xj为土地利用类型j中栅格x的年平均蒸散发量（mm）;R_xj为土地利用类型j中栅格x的干燥指数，表示潜在蒸发量与降雨量的比值;ω_x为修正植被年可利用水量与降水量的比值;k为植被系数，由植被叶面积指数计算^[29];ET₀为潜在蒸散发量（mm）^29]。植被年可利用水量利用土壤质地经验公式计算^[29]。
土壤保持	0.146	InVEST-Sediment Delivery Ratio model	$S C x = R x × K x × L S x × (1 - C x × P x) + S R x$ ， $S R x = E x ∑ y = 1 x - 1 S E y ∏ z = y + 1 x - 1 (1 - E z)$ 式中：SC_x和SR_x分别为栅格x的土壤保持量（t·hm^-2·a^-1）和泥沙持留量（t·hm^-2·a^-1）;SE_y为上坡栅格y产生的泥沙量（t·hm^-2·a^-1）;E_x为栅格x的泥沙持留率^[28];E_z为上坡栅格z的泥沙持留量（t·hm^-2·a^-1）;R_x、K_x、LS_x、C_x和P_x分别为栅格x的降雨侵蚀力因子（MJ·mm·hm^-2·h^-1·a^-1）、土壤可蚀性因子、坡度坡长因子、植被覆盖因子和水土保持措施因子。
固碳服务	0.082	CASA模型-NPP法	$N P P x, t = A P A R x, t × ξ x, t$ 式中：NPP(x, t)为栅格x的植被在t时段内的净初级生产力（g C·m^-2·a^-1）;APAR(x, t)为栅格x在t时段内植被所吸收的光和有效辐射;ξ(x, t)为栅格x的植被在t时段内的光能转化率^[27]。
粮食供给	0.038	NDVI配比法	$C r o p m n = (N D V I m n / N D V I s u m_n) × C r o p n$ 式中：Crop_mn为第n个县第m个栅格的粮食供给服务（t·a^-1）;NDVI_mn为该栅格全年中的NDVI最大值;NDVI_{sum_}_n为第n个县的NDVI全年最大值的和;Crop_n为第n个县的粮食年产量（t·a^-1）^[27]。

Tab. 1

Tab. 2

Evaluation methods of ecological sensitivity"

生态敏感性	评估模型/方法	基本原理及计算公式
地质灾害	综合因子权重法	$G H S I = G H 归一化 = ∑ i = 1 n W i × F i$ 式中：GHSI为地质灾害敏感性综合指数;GH_归一化为地质灾害加权叠加值;i为敏感性因子（i=1, 2, …, 10）;F_i为影响因子分值，本文选取断裂带距离（km）、土地利用类型、坡度（°）、地震核密度（个·km^-2）、距采矿地距离（km）、地形起伏度、距公路距离（km）、距河流湖库距离（km）、多年平均降水量（mm）、坡向共10个因子^[31,33];W_i为因子权重（由AHP法确定，λ_max=10.199，CI=0.022，RI=1.490，CR=0.015<0.1，通过一致性检验，权重值依次为0.140、0.129、0.121、0.110、0.101、0.093、0.086、0.079、0.073、0.068）^[31,33]。
水土流失	InVEST-Sediment Delivery Ratio model	$S E S I = U S L E 归一化 = R x × K x × L S x × C x × P x$ 式中：SESI为水土流失敏感性指数;USLE_归一化为栅格x的土壤侵蚀量（t·hm^-2·a^-1）;R_x、K_x、LS_x、C_x和P_x分别为栅格x的降雨侵蚀力因子（MJ·mm·hm^-2·h^-1·a^-1）、土壤可蚀性因子、坡度坡长因子、植被覆盖因子和水土保持措施因子^[28]。
土地荒漠化	NDVI植被指数法	$L D S I = V F 归一化 = (N D V I - N D V I m n) / (N D V I m x - N D V I m n)$ 式中：LDSI为土地荒漠化敏感性指数，参照已有研究^[32]，采用植被覆盖度VF_归一化表征（%）;NDVI为归一化植被指数;NDVI_mn和NDVI_mx分别为归一化植被指数的最小值和最大值。
生境退化	InVEST-Habitat Quality model	$H D S I = D x j 归一化 = ∑ r = 1 R ∑ y = 1 Y r w r / ∑ r = 1 R w r r y × i r x y × β x × S j r$ 式中：HDSI为生境退化敏感性指数;D_xj_归一化为生境类型j中栅格x的退化值;R为生境威胁因子;y为威胁因子r图层像元总数;Y_r为威胁因子所占像元数;w_r为威胁因子权重，取值0~1;r_y为像元y的威胁因子值（0或1）;i_rxy为像元y的威胁因子值r_y的生境胁迫水平，采用线性或指数距离衰减函数计算;β_x为像元x的可达性水平（0~1）;S_jr为生境类型j对胁迫因子r的敏感性（0~1）^[30]。
气候特征	InVEST-Water Yield model	$C S I = A E T x j P x 归一化 = 1 + ω x × R x j 1 + ω x × R x j + 1 / R x j$ 式中：CSI为气候敏感性指数，由地表年平均实际蒸散量与降水量的比值表征，经归一化获取^[29];各参数意义同表1产水服务公式。
综合生态敏感性	空间距离指数法	$C E S I = G H S I - G H S I m a x 2 + (S E S I - S E S I m a x) 2 + L D S I - L D S I m a x 2 + H D S I - H D S I m a x 2 + C S I - C S I m a x 2$ 式中：CESI为综合生态敏感性指数，其值越小，表示生态敏感性越高;GHSI、SESI、LDSI、HDSI、CSI为各生态敏感性指数;GHSI_max、SESI_max、LDSI_max、HDSI_max、CSI_max为各生态敏感性指数最大值^[32]。

Tab. 2

Tab. 3

Tab. 4

Fig. 3

Tab. 5

Fig. 4

Tab. 6

Fig. 5

Tab. 7

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等级分区	低度重要区	中度重要区	高度重要区
低度敏感区	低敏感低重要区（生态调节区）	低敏感中重要区（生态调节区）	低敏感高重要区（生态保护区）
中度敏感区	中敏感低重要区（生态调节区）	中敏感中重要区（生态保育区）	中敏感高重要区（生态修复区）
高度敏感区	高敏感低重要区（生态调节区）	高敏感中重要区（生态保育区）	高敏感高重要区（生态修复区）

生态重要性评价因子	统计类型	一般重要	较重要	中度重要	高度重要	极重要
生境质量	面积/km²	3641.5	3891.3	3863.4	3664.3	3619.6
生境质量	比重/%	19.5	20.8	20.7	19.6	19.4
产水服务	面积/km²	3666.1	3655.5	4173.2	3634.1	3551.2
产水服务	比重/%	19.6	19.6	22.3	19.5	19.0
土壤保持	面积/km²	847.3	8473.6	3336.8	3300.4	2722.0
土壤保持	比重/%	4.5	45.3	17.9	17.7	14.6
固碳服务	面积/km²	3693.8	3865.4	3843.6	3709.4	3567.9
固碳服务	比重/%	19.8	20.6	20.6	19.9	19.1
粮食供给	面积/km²	3547.0	4002.8	3844.1	3699.0	3587.2
粮食供给	比重/%	19.0	21.4	20.6	19.8	19.2
综合评价	面积/km²	3576.1	3940.2	3724.7	3762.0	3677.1
综合评价	比重/%	19.1	21.2	19.9	20.1	19.7

生态敏感性评价因子	统计类型	一般敏感	较敏感	中度敏感	高度敏感	极敏感
水土流失	面积/km²	806.6	14345.8	2202.9	879.8	445.1
水土流失	比重/%	4.3	76.8	11.8	4.7	2.4
地质灾害	面积/km²	3716.2	3874.6	3867.3	3636.1	3586.0
地质灾害	比重/%	19.9	20.7	20.7	19.5	19.2
土地荒漠化	面积/km²	3705.3	3725.0	3735.9	3767.3	3746.7
土地荒漠化	比重/%	19.8	19.9	20.0	20.2	20.1
生境退化	面积/km²	3682.3	3736.6	3835.1	3681.0	3745.2
生境退化	比重/%	19.7	20.0	20.6	19.7	20.0
气候敏感性	面积/km²	3682.1	3795.8	3618.9	3925.6	3657.8
气候敏感性	比重/%	19.7	20.3	19.4	21.0	19.6
综合评价	面积/km²	3680.2	3798.1	3815.4	3830.7	3555.8
综合评价	比重/%	19.7	20.3	20.4	20.5	19.1

类型	等级/分区	面积/km²	比重/%
生态重要性	高度重要	6238.7	33.4
	中度重要	6239.8	33.4
	低度重要	6201.7	33.2
生态敏感性	高度敏感	5970.7	32.0
	中度敏感	6473.0	34.7
	低度敏感	6236.5	33.3
生态修复分区	生态保护区	2930.2	15.7
	生态修复区	3307.4	17.7
	生态保育区	4881.5	26.1
	生态调节区	7561.1	40.5

土地利用类型		生态保护区		生态修复区		生态保育区		生态调节区		合计
一级	二级	面积/km²	比重/%	面积/km²	比重/%	面积/km²	比重/%	面积/km²	比重/%	面积/km²	比重/%
森林	阔叶林、针叶林、针阔混交林、稀疏林	361.6	12.3	10.4	0.3	-	-	-	-	372.0	2.0
灌丛	阔叶灌丛、稀疏灌丛	1070.7	36.5	543.1	16.4	124.5	2.5	15.7	0.2	1753.9	9.4
草地	草甸、草原、草丛、稀疏草地	1220.5	41.7	2714.1	82.1	3691.1	75.6	415.8	5.5	8041.4	43.0
湿地	沼泽、湖泊、河流、水库	11.4	0.4	29.8	0.9	28.2	0.6	3.9	0.1	73.2	0.4
农田	耕地、园地	258.2	8.8	10.1	0.3	1037.7	21.3	5862.4	77.5	7168.4	38.4
城镇	居住地、城市绿地、工矿交通	7.8	0.3	-	-	-	-	411.9	5.4	419.7	2.2
其他	裸地、荒漠	-	-	-	-	-	-	851.6	11.3	851.6	4.6
合计		2930.2	100.0	3307.5	100.0	4881.5	100.0	7561.2	100.0	18680.2	100.0

Zoning for ecological conservation and restoration in Liupan Mountain area based on ecological importance and sensitivity evaluation

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