Vegetation In Terrestrial Ecosystems Research Articles

Responses of vegetation photosynthetic processes to aerosol-induced direct radiative effect in China

Aerosols play an essential role in the energy cycle of land-atmosphere systems through interactions with radiation and clouds. Aerosol-induced direct radiative effect (ADRE) has a large effect on the photosynthetic processes of vegetation in terrestrial ecosystems. We used the Fu-Liou radiation transfer model integrated with the Community Land Model (CLM) to quantify ADRE and the responses of vegetation photosynthetic processes to ADRE in China from 2001 to 2014. The aerosols exhibited a positive effect on the diffuse fraction and it increased at first and decreased later. Positive impacts of ADRE on the leaf area index (LAI) of both sun (LAISUN) and shaded leaves (LAISHA) were captured in most areas of China, with increases of 0.01 and 0.09, respectively. The changes in LAI caused by ADRE were consistent with aerosol loading in northern and eastern China. In addition, due to the large decrease in total radiation caused by aerosols, ADRE reduced the photosynthetic rate of sun leaves. However, when the aerosol optical depth (AOD) ranged from 0.50 to 0.57, ADRE had positive effects on the photosynthetic rate of shaded leaves, and the AOD interval for positive impacts on the photosynthetic rate was different in each subregion of China. Mechanistic analysis found that ADRE could reduce the ribulose 1,5-bisphosphate (RuBP) carboxylase-limited rate of carboxylation and enhance the light-limited rate. When the AOD was around 0.47, the positive impacts of ADRE on the light-limited rate peaked throughout China (∼0.149 μmol m−2 s−1).

Analysis of Vegetation Environmental Stress and the Lag Effect in Countries along the “Six Economic Corridors”

Climate conditions have a significant impact on the growth of vegetation in terrestrial ecosystems, and the response of vegetation to climate shows different lag effects with the change in spatial pattern and category of the ecosystem. Exploring the interaction mechanism between climate and vegetation growth is helpful to promote the sustainable development of the regional ecological environment. Using normalized vegetation index (NDVI) and meteorological data, based on univariate linear regression and partial correlation analysis, this study explores the temporal and spatial pattern and change trend of vegetation cover in regions and node cities along the “six economic corridors”, and analyzes the environmental stress of vegetation growth and the lag effect of climate response. This study shows that there are great differences in the overall vegetation coverage along the “six economic corridors”. The vegetation coverage in Southeast Asia is the best and that in central and West Asia is the worst. The vegetation coverage in the study area shows an improvement trend, accounting for 39.6% of the total area. There are significant differences in the lag effect of vegetation response and the main climate factors affecting vegetation growth, which is related to the diversity of vegetation and climate characteristics. In this study, we selected regions along the “six economic corridors” that exhibit large latitude and altitude gradients, diverse climate types, and significant seasonal changes and spatial differences in climate conditions as our research areas. Additionally, we considered the impact of different regions and various types of vegetation on their response to climate change. This is of great significance for gaining a deeper understanding of the response mechanism of global climate change and vegetation ecology. Furthermore, our research can provide valuable information to support the ecological environment protection of different typical vegetation against extreme climates, ultimately contributing to the sustainable development of “the Belt and Road”.

Soil moisture content-based analysis of terrestrial ecosystems in China: Water use efficiency of vegetation systems

Water is a prerequisite for the formation of earth-biochemical-ecological systems. Differences in the spatial and temporal distribution of water resources are important factors in the formation of differences in the distribution of vegetation in terrestrial ecosystems and are key to the differences in vegetation productivity. Vegetation water use efficiency is calculated by the total amount of fixed biogenic carbon per unit mass of water consumed in photosynthesis and can be used to assess the intensity and capacity of an ecosystem to use water biomass. Based on remote satellite sensing data, this study proposes a new water use efficiency assessment model. The model was validated using flux site data, and we analyzed the relative contribution of climate factors to soil moisture use efficiency using a first-difference method. The results revealed the following: (1) The soil moisture use efficiencies (SUE) of remote sensing data inversions that were evaluated using flux site data based on correlation coefficients and Nash coefficients showed high reliability, and only the NMG (Inner Mongolia) station showed low correlation among the nine sites. (2) Among the nine agricultural sub-regions in China, only the SUE of the Qinghai-Tibet Plateau region showed a decreasing trend (−1.08 g C/m−2 kg H2O yr), while all other regions showed an increasing trend. (3) The highest vegetation soil moisture use efficiency (1.83 g C/m−2 kg H2O) was found in ferralisols, while the lowest vegetation SUE (0.17 g C/m−2 kg H2O) was found in arid soils. The SUE of different vegetation types showed the characteristics of forest > scrub > cultivated vegetation > wetland > grassland. (4) The relative contribution of gross primary productivity (GPP) to the change in SUE was 37.53%, while the relative contribution of soil moisture content to the change in SUE was −26.71%. Among the five climatic factors, temperature was the most dominant factor affecting the change in SUE, followed by precipitation, net radiation, leaf area index, and potential evapotranspiration. Revealing the relationship between terrestrial ecosystem GPP, soil moisture content, and their responses to climate factors is a prerequisite for understanding the adaptation strategies of regional terrestrial ecosystems to global climate change, which can help to inform decision-making for the sustainable development of ecosystems.

Investigating the accuracy of vegetation index-based models for estimating the fractional vegetation cover and the effects of varying soil backgrounds using in situ measurements and the PROSAIL model

ABSTRACTFractional vegetation cover (FVC) is an important variable for describing the quality and changes of vegetation in terrestrial ecosystems. The simplest and most widely used model for the estimation of FVC is the dimidiate pixel model. The normalized difference vegetation index (NDVI) is commonly used as a vegetation index (VI) in this model. A range of VIs is possible alternative to the use of NDVI in the dimidiate pixel model. In this article, six VI-based dimidiate pixel models were compared using in situ measurements and canopy reflectances simulated by the PROSAIL model over nine different soil backgrounds. A comparison with in situ measurements showed that the Gutman–Ignatov method overestimated FVC, with a mean root mean square error (RMSE) of 0.14. The mean RMSE had an intermediate value of 0.08 in the Carlson–Ripley method and was further reduced to 0.05 in the method proposed by Baret et al. The use of both modified soil-adjusted vegetation index (MSAVI) and a mixture of NDVI and the ratio vegetation index (RVI) to replace NDVI in the Gutman–Ignatov model reduced the RMSE to 0.06. The mean RMSE in the difference vegetation index (DVI)-based model was 0.08. The simulated results indicated that soil backgrounds have significant effects on these VI-based models. The sensitivity of the first three models and the NDVI plus RVI-based model to soil backgrounds decreased with an increase in soil reflectance. In contrast, the DVI-based model is sensitive to soil backgrounds with high reflectances. MSAVI, which is less sensitive to soil backgrounds, represents a feasible alternative to the use of NDVI in the Gutman–Ignatov model.

Comparison of fractional vegetation cover estimations using dimidiate pixel models and look-up table inversions of the PROSAIL model from Landsat 8 OLI data

Fractional vegetation cover (FVC) is an important variable for describing the quality and changes of vegetation in terrestrial ecosystems. Dimidiate pixel models and physical models are widely used to estimate FVC. Six dimidiate pixel models based on different vegetation indices (VI) and four look-up table (LUT) methods were compared to estimate FVC from Landsat 8 OLI data. Comparisons with in situ FVC of steppe and corn showed that the model proposed by Baret et al., which is based on the normalized difference vegetation index (NDVI), predicted FVC most accurately followed by Carlson and Ripley’s method. Gutman and Ignatov’s method overestimated FVC. Modified soil adjusted vegetation index (MSAVI) and the mixture of NDVI and RVI showed potential to replace NDVI in Gutman and Ignatov’s model, whereas the difference vegetation index (DVI) performed less well. At low vegetation cover, the LUT using reflectances to constrain the cost function performed better than LUTs using VI to constrain the cost function, whereas at high vegetation cover, the LUT based on NDVI estimated FVC most accurately. The applications of DVI and MSAVI to constrain the cost function also obtained improvement at high vegetation cover. Overall, the accuracies of LUT methods were a little lower than those of dimidiate pixel models.

Influence of development stage of spring oilseed rape and spring wheat on interception of wet-deposited radiocaesium and radiostrontium

The dry and wet deposition of radionuclides released into the atmosphere can be intercepted by vegetation in terrestrial ecosystems. The aim of this study was to quantify the interception of wet deposited 134Cs and 85Sr by spring oilseed rape (Brassíca napus L.) and spring wheat (Tríticum aestívum L.). The dependency of the intercepted fraction (f) on total above ground plant biomass, growing stage and the Leaf Area Index (LAI) was quantified. A trial was established in Uppsala (east central Sweden), with land management in accordance to common agricultural practices. The field trial was a randomised block design of 1 × 1 m2 parcels with three replicates. During the growing season of 2010, a rainfall simulator deposited 134Cs and 85Sr during six different growth stages. Two to 3 h after deposition, the biomass of the centre 25 × 25 cm2 area of each parcel was sampled and above ground biomass and LAI were measured. The radioactivity concentration and radioactivity of samples were measured by High Purity Germanium (HPGe)-detectors.For 134Cs, there was a correlation between f and LAI (r2 = 0.55, p < 0.05) for spring wheat, but not for spring oilseed rape (r2 = 0.28, p > 0.05). For 85Sr, there was a correlation between f and LAI for both crops (r2 = 0.41, p < 0.05 for spring oilseed rape and r2 = 0.48 p, <0.05 for spring wheat). There was no correlation between f and above ground plant biomass in spring oilseed rape for either 134Cs (r2 = 0.01, p > 0.05) or for 85Sr (r2 = 0.11, p > 0.05). For spring wheat, there was a correlation for both 134Cs (r2 = 0.36, p < 0.05) and 85Sr (r2 = 0.32, p < 0.05). For spring oilseed rape, f was highest at growth stage ‘stem elongation’ for 134Cs (0.32 ± 0.22) and 85Sr (0.41 ± 0.29). For spring wheat, f was highest at growth stage ‘ripening’ for both radionuclides (134Cs was 0.36 ± 0.14 and 85Sr was 0.48 ± 0.18). Thus, LAI can be used to quantify interception of both radionuclides for both crops, whereas, above ground plant biomass is a weak measure of interception of wet deposited radiocaesium and radiostrontium.

Carbon Sequestration in Arable Soils is Likely to Increase Nitrous Oxide Emissions, Offsetting Reductions in Climate Radiative Forcing

Strategies for mitigating the increasing concentration of carbon dioxide (CO2) in the atmosphere include sequestering carbon (C) in soils and vegetation of terrestrial ecosystems. Carbon and nitrogen (N) move through terrestrial ecosystems in coupled biogeochemical cycles, and increasing C stocks in soils and vegetation will have an impact on the N cycle. We conducted simulations with a biogeochemical model to evaluate the impact of different cropland management strategies on the coupled cycles of C and N, with special emphasis on C-sequestration and emission of the greenhouse gases methane (CH4) and nitrous oxide (N2O). Reduced tillage, enhanced crop residue incorporation, and farmyard manure application each increased soil C-sequestration, increased N2O emissions, and had little effect on CH4 uptake. Over 20 years, increases in N2O emissions, which were converted into CO2-equivalent emissions with 100-year global warming potential multipliers, offset 75–310% of the carbon sequestered, depending on the scenario. Quantification of these types of biogeochemical interactions must be incorporated into assessment frameworks and trading mechanisms to accurately evaluate the value of agricultural systems in strategies for climate protection.