Abstract
Precipitation change has significantly influenced annual net primary productivity (ANPP) at either annual or seasonal scales in desert steppes in arid and semi-arid regions. In order to reveal the process of precipitation driving ANPP at different time scales, responses of different ANPP levels to the inter-annual and intra-annual precipitation fluctuations were analyzed. ANPP was reversed by building a ground reflectance spectrum model, from 2000 to 2015, using the normalized differential vegetation index of the Moderate-Resolution Imaging Spectroradiometer (MODIS-NDVI) data at 250 m × 250 m spatial resolution. Since the description of the differently expressing forms of precipitation are not sufficient in former studies in order to overcome the deficiency of former studies, in this study, intra-annual precipitation fluctuations were analyzed not only with precipitation of May–August, June–August, July–August, and August, respectively, which have direct influence on vegetation productivity within the year, but quantitative description, vector precipitation (R), concentration ratio (Cd), and concentration period (D), were also used to describe the overall characteristics of intra-annual precipitation fluctuations. The concentration ratio and the maximum precipitation period of the intra-annual precipitation were represented by using monthly precipitation. The results showed that: (1) in the period from 1971 to 2015, the maximum annual precipitation is 3.76 times that of the minimum in the Urat desert steppe; (2) vector precipitation is more significantly related to ANPP (r = 0.7724, p = 0.000) compared to meteorological annual precipitation and real annual precipitation influence; and (3) annual precipitation is almost concentrated in 5–8 months and monthly precipitation accumulation has significantly effected ANPP, especially in the period of June–August, since the vegetation composition in the study area was mainly sub-shrubs and perennial grasses, which were more sensitive to precipitation accumulation. These findings suggest that: (1) In the desert steppe, the inter-annual fluctuation and the intra-annual distribution of precipitation have a direct impact on ANPP; (2) the annual vector precipitation showed an extremely significant regression relationship with ANPP; and (3) monthly precipitation fluctuations (May–August) possess the accumulative effect on ANPP during the growing period in the desert steppe, while precipitation accumulation from June to August shows the most significant impact.
Highlights
Precipitation, and its pattern changes, is a key point of shaping the regional annual net primary productivity (ANPP) [1,2,3] and to be the main driving factors, precipitation has significantly influenced various biological processes of the ecosystem, especially in arid and semi-arid grasslands [4,5,6,7]
In arid and semi-arid regions, vegetation pattern is mainly determined by precipitation distribution at different time scales [5,9]
The vegetation pattern directly affects the effectiveness of precipitation supply to vegetation, and the interrelationship between precipitation fluctuations and vegetation patterns is one of the current key research points of eco-hydrology [6,8,12,13,14]
Summary
Precipitation, and its pattern changes, is a key point of shaping the regional annual net primary productivity (ANPP) [1,2,3] and to be the main driving factors, precipitation has significantly influenced various biological processes of the ecosystem, especially in arid and semi-arid grasslands [4,5,6,7]. The impact of precipitation changes over 10 years can change the vegetation function types and species composition of an ecological system, and the precipitation change in annual and seasonal scales can change the vegetation phenology and ecosystem productivity [10,11]. The results achieved were mainly concentrated in the impact of precipitation seasonal distribution in larger spatial scales on productivity, water restriction, and vegetation function types of ecosystems, or in the role of precipitation and evapotranspiration shaping the vegetation pattern and the ecological process [14,16]. The relationship of vegetation indices and grassland biomass was studied, and many regression models Shuasvtaeinbabeielintye2s0t1a6,b8l,is1h24e5d, most of them being linear or non-linear, that improved the accuracy of bio3moaf s1s4 estimates and determined grassland ANPP patterns in different regions. MPaoteljraika.l,sAalnlidumMpeothlyorhdiszum Turcz. ex Regel, Heteropappus altaicus (Willd.) Novopokr., Potaninia mongolica Maxim., Salsola laricifolia Turcz. ex Litv., and so on
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