陕西省生境质量时空演变及驱动机制分析

doi:10.13866/j.azr.2022.05.32

摘要/Abstract

摘要：

生境质量是生物多样性保护和区域生态环境改善的重要基础,生态文明建设背景下研究生境质量时空演变及驱动机制具有重要意义。以陕西省为研究区,基于2000年、2010年和2020年的土地利用数据,利用InVEST模型、泰尔指数和地理探测器模型分析了三大地区（陕南、陕北、关中）生境质量的时空演变特征及驱动因子。结果表明：（1） 2000—2020年全省平均生境质量呈现稳定且略微上升趋势,空间分布差异明显,表现为陕南和陕北地区高于关中地区;（2）全省三大地区间和地区内的生境质量差异较大,陕南和关中地区差异性大于陕北地区;（3）受空间尺度影响,全省和三大地区的驱动因子有所不同,植被与地形因子对全省生境质量影响最大,土地利用因子是三大地区的主要影响因素,且随着时间推移影响程度逐渐加强,地形因子与植被因子对三大地区的影响各有不同;（4）除单因子影响外,社会经济与自然环境因素的协同作用对三大地区生境质量变化影响显著。

关键词: 生境质量, InVEST模型, 地理探测器, 驱动因子, 陕西省

Abstract:

Habitat quality is an important basis for biodiversity conservation and improvement of the regional ecological environment. With an ecological civilization construction as the background, the spatial-temporal adaptation and driving mechanism of habitat quality is significant to study. Based on land use data in Shaanxi Province in 2000, 2010, and 2020, the characteristics and driving factors in the spatial-temporal adaptations of the quality of habitat in three regions were analyzed using the InVEST model, Theil index model, and geographic detector model. The results showed the following: (1) from 2000 to 2020, the average quality of habitat showed a stable and slightly increasing trend, and the spatial distribution difference was obvious, with the average habitat quality in southern Shaanxi and northern Shaanxi being higher compared to Guanzhong; (2) the difference of habitat quality among the three regions was larger in southern and central Shaanxi compared to northern Shaanxi; (3) the province and the driving factors in the three different regions, vegetation and terrain factors for the habitat quality, and land utilization factor are the main influencing factors of the three major areas affected by the spatial scale. As time goes on, the influence degree gradually strengthens, and the terrain and vegetation factors have different effects on three areas; (4) In addition to single factors, significant impacts on habitat quality changes in the three regions produced cooperative effects on socioeconomic and natural environmental factors.

Key words: habitat quality, InVEST model, geographic detector, driving factor, Shaanxi Province

王琦琨,武玮,杨雪琪,桑国庆. 陕西省生境质量时空演变及驱动机制分析[J]. 干旱区研究, 2022, 39(5): 1684-1694.

WANG Qikun,WU Wei,YANG Xueqi,SANG Guoqing. Spatial-temporal changes and driving factors of habitat quality in Shaanxi Province during the past 20 years[J]. Arid Zone Research, 2022, 39(5): 1684-1694.

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一级指标	二级指标	三级指标	数据来源	数据处理
自然环境	地形因子	起伏度	DEM数据来自地理空间数据云(https://www.gscloud.cn/),精度为30 m	DEM填洼处理后使用Block Statistics提取
	地形因子	地形位	DEM数据来自地理空间数据云(https://www.gscloud.cn/),精度为30 m	地形位公式^[21]
	气候因子	年均气温年降水	中国科学院资源环境科学与数据中心(https://www.resdc.cn/) 陕西省87个国家气象站	克里金插值
	植被因子	净初级生产力（NPP）	美国NASA官网 (https://modaps.modaps.eosdis.nasa.gov/),时间分辨率为8 d,空间分辨率500 m	最大合成法^[22]
		归一化植被指数（NDVI）	美国NASA官网 (https://modaps.modaps.eosdis.nasa.gov),时间分辨率为30 d,空间分辨率500 m
		叶面积指数（LAI）	美国NASA官网 (https://modaps.modaps.eosdis.nasa.gov),时间分辨率为8 d,空间分辨率500 m
社会经济	交通区位	到市中心距离	北京大学城市与环境学院和open street官网(https://www.openhistoricalmap.org )	计算市中心欧氏距离
		到县中心距离		计算县中心欧氏距离
		道路密度		道路长度/总面积
	人口经济	县区GDP	《中国县域统计年鉴》	-
	人口经济	县区人口数	《中国县域统计年鉴》	-
	土地利用	土地利用强度	中国科学院资源环境科学与数据中心(https://www.resdc.cn/),精度为30 m	依据受人类活动干扰程度分为4级^[23]：1级为未利用地,2级为林、草地和水域,3级为耕地,4级为城镇工矿居民用地

土地类型	适宜度	城镇用地	农村用地	水田	旱地	交通工矿用地
水田	0.5	0.7	0.6	0.4	0.3	0.6
旱地	0.4	0.6	0.5	0.4	0.3	0.5
有林地	0.9	0.8	0.8	0.8	0.7	0.8
灌木林	0.85	0.8	0.7	0.7	0.6	0.7
疏林地	0.7	0.8	0.7	0.6	0.5	0.7
其他林地	0.6	0.75	0.7	0.6	0.5	0.7
高覆盖度草地	0.75	0.7	0.65	0.7	0.6	0.65
中覆盖度草地	0.7	0.6	0.6	0.6	0.55	0.6
低覆盖度草地	0.6	0.5	0.6	0.5	0.5	0.6
河渠	0.8	0.7	0.6	0.5	0.5	0.5
湖泊	0.8	0.7	0.6	0.5	0.5	0.5
水库坑塘	0.7	0.6	0.5	0.5	0.5	0.5
沼泽地	0.6	0.6	0.5	0.2	0.4	0.3
滩地	0.5	0.1	0.1	0.1	0.1	0.2
城镇用地	0	0	0	0	0	0
农村居民点	0	0	0	0	0	0
其他建设用地	0	0	0	0	0	0
沙地	0	0	0	0	0	0
戈壁	0	0	0	0	0	0
盐碱地	0	0	0	0	0	0
裸土地	0	0	0	0	0	0
裸岩石质地	0	0	0	0	0	0

胁迫因子	最大影响距离/km	权重	衰退方式
水田	3	0.6	线性
旱地	4	0.7	线性
城镇用地	8	1	指数
农村用地	6	0.8	指数
交通工矿用地	5	0.5	线性

地区	年份	低生境质量	较低生境质量	中等生境质量	较高生境质量	高生境质量	生境质量指数
全省	2000	4.80%	38.30%	21.70%	23.50%	11.70%	0.487
	2010	5.30%	40.10%	21.20%	22.00%	11.40%	0.477
	2020	5.00%	34.00%	19.60%	27.90%	13.50%	0.509
关中地区	2000	4.10%	45.54%	8.72%	20.15%	21.49%	0.381
	2010	3.56%	47.01%	9.02%	19.25%	21.16%	0.389
	2020	5.66%	41.76%	8.77%	22.19%	21.62%	0.34
陕南地区	2000	2.41%	23.16%	21.88%	36.14%	16.41%	0.551
	2010	2.75%	24.08%	22.42%	34.49%	16.26%	0.545
	2020	1.54%	21.53%	18.84%	37.68%	20.41%	0.573
陕北地区	2000	5.03%	54.53%	22.25%	12.06%	6.13%	0.456
	2010	6.12%	56.57%	20.41%	10.88%	6.01%	0.447
	2020	5.29%	47.25%	20.70%	20.08%	6.68%	0.495