首页|Estimating the optimal vegetation coverage for the dominant tree and shrub species over China's northwest drylands

Estimating the optimal vegetation coverage for the dominant tree and shrub species over China's northwest drylands

扫码查看
Estimating the optimal vegetation coverage for the dominant tree and shrub species over China's northwest drylands
Anthropogenic revegetation is an effective way to control soil erosion and restore degraded ecosystems in China's northwest drylands(NWD).However,excessive vegetation cover expansion has long been known to increase evapo-transpiration,leading to reduced local water availability,which can in turn threaten the health and services of restored eco-systems.Determining the optimal vegetation coverage(OVC)is critical for balancing the trade-off between plant growth and water consumption in water-stressed areas,yet quantitative assessments over the entire NWD are still lacking.In this study,a modified Biome BioGeochemical Cycles(Biome-BGC)model was used to simulate the long-term(1961-2020)dynamics of actual evapotranspiration(ETa),net primary productivity(NPP),and leaf area index(LAI)for the dominant non-native tree(R.pseudoacacia and P.sylvestris)and shrub(C.korshinkii and H.rhamnoides)species at 246 meteorological sites over NWD.The modified model incorporated the Richards equation to simulate transient unsaturated water flow in a multilayer soil module,and both soil and eco-physiological parameters required by the model were validated using field-observed ETa data for each species.Spatial distributions of OVC(given by the mean maximum LAI,LAImax)for the dominant species were determined within three hydrogeomorphic sub-areas(i.e.,the loess hilly-gully sub-area,the windy and sandy sub-area,and the desert sub-area).The modified Biome-BGC model performed well in terms of simulating ETa dynamics for the four plant species.Spatial distributions of mean ETa,NPP,and LAImax generally exhibited patterns similar to mean annual precipitation(MAP).In the loess hilly-gully sub-area(MAP:210 to 710 mm),the OVC respectively ranged from 1.7 to 2.9 and 0.8 to 2.9 for R.pseudoacacia and H.rhamnoides.In the windy and sandy sub-area(MAP:135 to 500 mm),the OVC ranged from 0.3 to 3.3,0.5 to 2.6 and 0.6 to 2.1 for P.sylvestris,C.korshinkii and H.rhamnoides,respectively.In the desert sub-area(MAP:90 to 500 mm),the OVC ranged from 0.4 to 1.7 for H.rhamnoides.Positive differences between observed and simulated plant coverage were found over 51%of the forest-and shrub-covered area,especially in the loess hilly-gully sub-area,suggesting possible widespread overplanting in those areas.This study provides critical revegetation thresholds for dominant tree and shrub species to guide future revegetation activities.Further revegetation in areas with overplanting should be undertaken with caution,and restored ecosystems that exceed the OVC should be managed(e.g.,thinning)to maintain a sustainable ecohydrological environment in the drylands.

Optimal vegetation coverageWater balanceLeaf area indexBiome-BGC modelDryland

Zhongdian ZHANG、Xiaoxu JIA、Ping ZHU、Mingbin HUANG、Lidong REN、Ming'an SHAO

展开 >

School of Geographic Sciences,Xinyang Normal University,Xinyang 464000,China

Key Laboratory of Ecosystem Network Observation and Modeling,Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences,Beijing 100101,China

College of Resources and Environment,University of Chinese Academy of Sciences,Beijing 100190,China

Yellow River Delta Modern Agricultural Engineering Laboratory,Chinese Academy of Sciences,Beijing 100101,China

State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau,Institute of Soil and Water Conservation,Northwest A&F University,Yangling 712100,China

State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau,Institute of Soil and Water Conservation,Northwes

展开 >

Optimal vegetation coverage Water balance Leaf area index Biome-BGC model Dryland

2024

中国科学:地球科学(英文版)
中国科学院

中国科学:地球科学(英文版)

影响因子:1.002
ISSN:1674-7313
年,卷(期):2024.67(5)