Increase In Leaf Area Index Research Articles

Performance of Cluster Bean (Cyamopsis tetragonoloba) under Varying Levels of Irrigation and Nitrogen

Background: Clusterbean (Cyamopsis tetragonoloba L.) is important commercial crop which belongs to family Leguminosae and has capacity to fix the atmospheric nitrogen. The nitrogen fixed by the legume crop is not enough to meet the demand of short duration crop like clusterbean. Besides, the experimental site falls under arid region where drought stress and poor distribution of rain during the crop growing cycle is common which affects the crop growth and productivity. Drawing on these insights, the study was planned to assess the performance of cluster bean with objectives to quantify water balance and to calculate suitable levels of irrigation and nitrogen. Methods: The experiment was conducted at research farm, Agricultural research sub-station, Hanumangarh, Swami Keshwanand Rajasthan Agricultural University, Bikaner during Kharif, 2016. Cluster bean variety RGC-1055 with seed rate of 16 kg ha-1 was planted with 3 levels of irrigation (100, 200 and 300 mm) and 4 levels of nitrogen (0, 20, 40 and 60 kg ha-1) and analyzed in split plot design with three replications. Result: Results showed by that the irrigation and nitrogen application rates significantly influenced the growth parameters, yield, nitrogen content and uptake by cluster bean. Irrigation level 200 mm significantly increased leaf area index at 60 DAS (2.62), dry matter accumulation (DMA) at 60 DAS and harvest (16.51 and 42.62 g plant-1), crop growth rate at 30-60 DAS and at harvest (0.36 and 0.62 g m-2 day-1), relative growth rate at 60- at harvest (1.59 g g-1 day-1), grain yield (1624 kg ha-1), straw yield (3645 kg ha-1) and biological yield (5270 kg ha-1) over irrigation level 100 mm, but statistically at par with irrigation level 300 mm. However, leaf area index at harvest (1.24) was highest at 300 mm irrigation level. Nitrogen level at 40 kg ha-1 significantly increased leaf area index at 30, 60 DAS and at harvest (0.19, 2.65 and 1.16), dry matter accumulation at 60 DAS and at harvest (19.62 and 49.58 g plant-1), crop growth rate at 30-60 DAS and 60- harvest (0.46 and 0.71 g m-2 day-1), relative growth rate at 30-60 DAS and 60-harvest (1.26 and 1.66 g g-1 day-1), grain yield (1668 kg ha-1), straw yield (3696 kg ha-1) and biological yield (5364 kg ha-1) over control. The highest nitrogen content and uptake in grain and straw was obtained with irrigation level at 300 mm and nitrogen level @ 60 kg ha-1.

Effects of row spacing on soil nitrogen availability, wheat morpho-physiological traits and radiation use efficiency

Optimizing row spacing is an important measure to exploit the full yield potential, achieve a continuous increase in wheat yield and green development without increasing input. The objective of this study was to compare the effects of wide–narrow row spacing pattern (12 cm-12 cm-12 cm-24 cm, R1) and conventional uniform row spacing mode (20 cm, CK; 12 cm. R2) on nitrogen (N) availability in soil, canopy structure, photosynthetic characteristics, radiation use efficiency (RUE) and yield. The results showed that R1 increased the relative abundance of ammonia-oxidizing bacteria and ammonia-oxidizing archaea in the rhizosphere compared to CK. Nitrate in soils treated R1 at post-anthesis and nitrogen use efficiency of the plant were 59.92% and 27.01% higher than those treated with CK, respectively. Above-ground growth of wheat showed that R1 increased leaf area index by 27.42%, specific leaf weight by 22.67% and leaf photosynthetic rate by 8.86%, respectively compared to CK. R2 had similar availability of N and plant growth as CK. Moreover, the ability of the plant to allocate more nitrogen to grains was enhanced at post-anthesis with R1 than it with CK and R2, which greatly improved the RUE by 10.13% and 2.27%. As the result, the yield for R1 increased by 27.54% and 21.46%, respectively, compared to CK and R2. Therefore, using wide–narrow row spacing pattern (R1) is a practically and environmentally feasible approach for wheat production without extra input in the straw-returning wheat-corn rotation system.

Seasonal variations of forest leaf area index and its thermal effect on water-eroded areas in 2000–2014 using remote sensing imageries

Aim: To analyze the spatiotemporal distribution of forest vegetation and its relationship with ground temperature in severe water erosion areas in Southern China. Methodology: The spatiotemporal variations of leaf area index (LAI) at a seasonal scale of the study area, Changting County in Fujian Province, China, were derived and compared with ground temperature (T) in 2000-2014 through remote sensing imageries. Results: Average seasonal LAI of central towns (< 2.3) were less than those of other towns, and negative correlations were found between LAI and T in 2000 and 2014. The R squares of the LAI–T relationship models were > 0.4 in 2000 and < 0.4 in 2014. Interpretation: This study demonstrated that more factors were involved in the thermal effect with the increase of LAI and the multi-year conservation management. Conservation measures should be prioritized in the central and south-eastern areas of the county with intense erosion. Key words: County, Leaf area index, Remote sensing, Seasonal variations, Soil erosion grade

Climate and management impacts on crop growth and evapotranspiration in the North China Plain based on long-term eddy covariance observation

Comprehensive understanding of how climate change and cropland management affect crop growth and water consumption is essential but unclear in the North China Plain (NCP) which is one of the major winter wheat and summer maize production regions. By combining an agro-hydrological model with 16-year eddy covariance observation, we quantified the impacts of climatic factors and key management (i.e., sowing date and irrigation) on the trend of key phenological stages, leaf area index (LAI), crop yield, evapotranspiration (ET), and water use efficiency (WUE) at a typical irrigated site in the NCP. We found that the advance of start and end of season was mainly caused by advanced sowing date and rising temperature which also shortened the reproductive phase; however, the growing season length (GSL) was remarkably shortened by advanced sowing date. Although LAI and yield of both crops were increasing, they were mainly negatively affected by rising temperature while slightly promoted by elevated CO2 concentration. LAI and yield of maize were also greatly improved by increasing radiation and irrigation, and wheat's growth was considerably hampered by excessive irrigation. Increasing ET was mainly ascribed to increasing radiation and decreasing humidity, but slightly inhibited by elevated CO2 concentration. Increasing WUE was mainly inhibited by the rising temperature and decreasing humidity while improved slightly by elevated CO2 concentration. Besides, we inferred that increase in LAI, yield, ET, and WUE of wheat is most likely to be attributed to the renewal of cultivars, the delay of key phenological stages, and prolongation of GSL for both crops was also possibly caused by the renewal of cultivars. Our study provided a first comprehensive insight into the long-term coupled variation of crop growth and evapotranspiration in this region.

Estimating hydrological consequences of vegetation greening

• LAI increased significantly up to 72.2% of the whole YRB area in 1981–2018. • Vegetation greening decreased SW and Q, but increased ET in selected catchments. • Sensitivities of the changes in Q and ET to the changes in LAI increased as LAI grows. • Sensitivity of ET and Q to LAI changes increased as the climate became drier. Large-scale afforestation program has alleviated environmental problems to some extent in China. However, the response of hydrological processes to vegetation greening at different catchments remains unclear. This study identified the impact of vegetation changes on runoff (Q), evapotranspiration (ET), and soil water storage (SW), as well as their relationships and sensitivities based on a coupled SWAT-PML model for 23 catchments from 2000 to 2018 in the Yellow River Basin (YRB). Results show that leaf area index (LAI) was significantly ( p < 0.05) increased in 72.2% of the YRB area. Vegetation greening decreased SW and Q, but increased ET in all catchments. The effects of vegetation greening on Q and ET were contrasting with axisymmetric fluctuation distribution. The changes in SW, ET, and Q were strongly correlated with the changes in LAI. Sensitivity of the changes in ET and Q to LAI changes increased when the climate becomes drier. Our study suggests that the vegetation greening followed by the afforestation policy implementation has caused gradually increasing impacts on Q and ET. However, such effects are spatially heterogeneous due to different degrees of increase in LAI and aridity conditions. Given the water crisis problem in the YRB, afforestation activity should be taken into consideration of the increasing water demand and the negative effects of vegetation greening on water resources in the future.

Growth Dynamics and Yield of Zero-Till Maize as Influenced by Microbial Consortia Treated Paddy Residue Incorporation

A field experiment was conducted at College farm, Professor Jayashankar Telangana State Agricultural University, Rajendranagar, Hyderabad during 2020-21 and 2021-22 to assess the influence of paddy residue management practices at different fertility levels on certain growth parameters and the yield of rabi maize succeeding kharif rice in a strip plot design. The growth analysis indicated that the leaf area index, crop growth rate, net assimilation rate and leaf area duration remained the same with residue management practices at 0-30 DAS and 30-60 DAS but between 60 DAS-harvest, maize leaf area index (LAI), crop growth rate (CGR), net assimilation rate (NAR) and leaf area duration (LAD) was significantly increased by incorporation of crop residues treated with microbial consortia and SSP. Different fertility levels affected leaf area index, crop growth rate and leaf area duration at all the growth intervals whereas net assimilation rate remained unaffected. Interaction effect of residue management practices and fertility levels on leaf area index, crop growth rate, net assimilation rate and leaf area duration was found non significant at 0-30 DAS and 30-60 DAS, while at 60 DAS-harvest integration of residues and microbial consortia along with chemical fertilizers resulted in a significant increase of LAI, CGR and LAD with no significant improvement in NAR. In 2020-21 and 2021-22, the grain yield and straw yield were higher in the incorporation of crop residues treated with microbial consortia and single super phosphate (SSP) in combination with 125 % recommended dose of fertilizers (RDF) which was on par with 100% RDF and 75 % RDF and was significantly superior over other treatments.

Contrasting Trends in Water Use Efficiency of the Alpine Grassland in Tibetan Plateau

AbstractAlpine grassland is the dominant land cover type of the Tibetan Plateau (TP). Previous studies suggested that TP's climate and vegetation condition have changed substantially in past few decades. However, the impacts of such changes on ecosystem water use efficiency (WUE), a vital index for depicting the tradeoff between water loss and carbon gain, of alpine grassland remain poorly understood. This study used a water‐carbon coupled model, Penman‐Monteith‐Leuning Version 2 (PML_V2), to investigate the variation in WUE of alpine grassland in the TP during 1982–2016 and its drivers. PML_V2 performs well in estimating WUE at nine eddy‐covariance flux sites, noticeably better than other main‐stream products. The long‐term mean WUE decreases from the southeastern to the northwestern TP, generally following the spatial pattens of surface greenness and climatic condition. During 1982–2016, WUE increased in most parts (71%) of alpine grassland but declined in certain regions of western TP. At the ecosystem scale, contrasting trends in WUE emerged between alpine meadow and alpine steppe over the last 35 years. The former's significant increasing WUE was primarily driven by increased leaf area index (LAI) and CO2 concentration (eCO2). While greening also occurred in the latter, its WUE remained stable because (a) the large negative effect of precipitation offset the positive effect of LAI on WUE, and; (b) the enhancement of photosynthesis resulted from elevated eCO2 was weaker because of low LAI. Our results are of importance for understanding the dynamics and mechanisms of water‐carbon coupling in high‐elevation ecosystems under a changing climate.

Amendment with Nanoparticulate Gypsum Enhances Spinach Growth in Saline-Sodic Soil

The use of nano-gypsum in low doses can be an innovative method to mitigate salinity-sodicity effects and enhance spinach growth in saline-sodic soil. We evaluated nano-gypsum in four low doses of 960, 480, 240, and 120 kg ha−1, in addition to the control and the recommended conventional gypsum dose (~ 30 t ha−1), in a randomized complete pot experiment. The pots of soil were incubated in a laboratory for 2 months and leached 5 times for another 2 months. Then, spinach was grown in the soil for 60 days. The nano-gypsum dose of 240 kg ha−1 with leaching was the best at improving the soil and spinach growth characteristics compared with the other doses and both control and conventional gypsum rate. Moreover, it was considered the critical nano-gypsum threshold rate. Compared to control after soil leaching, the critical rate increased the water-stable aggregate index and reduced bulk density by 57.39% and 16.30%, respectively; accordingly, the saturated hydraulic conductivity increased up to 2.34 times. Improved hydraulic conductivity led to a decrease in exchangeable Na ratio by 91% and reduced both soil salinity and pH by 83% and 1 unit, respectively. These great improvements in the soil properties favored the spinach growth indicators, which increased leaf area index, root hair index, and fresh yield by 2.20, 4.41, and 1.29 times, respectively, when compared to the recommended conventional gypsum rate. Accordingly, nano-gypsum in low doses is considered an innovative alternative to high doses of conventional gypsum to mitigate salinity-sodicity effects and enhance spinach growth in saline-sodic soil.

Estimation of Canopy Leaf Area Index of Tropical Rainforests of Sri Lanka from the Normalized Difference Vegetation Index along a Wide Altitudinal Gradient

The leaf area index (LAI) of a forest is a key determinant of its primary productivity. Estimation of LAI via remote sensing of forest canopies offers an alternative to direct measurement, which is difficult in tropical rainforests (TRFs). Our objectives were to determine the variation of LAI and Normalized Difference Vegetation Index (NDVI) of a range of TRFs of Sri Lanka across a wide altitudinal range (117-2,132 m above sea level) and develop a predictive model to estimate LAI from NDVI and canopy architectural properties. Ten permanent sampling plots (PSPs) of one hectare each were established in forest reserves of Kanneliya (117-174 m), Sinharaja-Pitadeniya (509-618 m), Sinharaja-Enasalwatte (1,042-1,065 m), Rilagala (1,668 m), Hakgala (1,804 m), Piduruthalagala (2,080 m) and Horton Plains (2,132 m). Canopy LAI and its architectural properties (i.e., Mean Leaf Angle (MLA) and leaf angle distribution) were computed by analysis of ‘fish-eye’ images obtained from September 2019 to July 2020, using hemispherical photography and HemiView software. Satellite images for March-April, 2020 were downloaded from Landsat 8 OLI/TIRS C2L1. NDVI (NDVI=λNIR-λRED/λNIR+λRED) was calculated from ENVI software, where λNIR and λRED are reflectances of near-infrared and red wavebands. ENVI software computed the maximum NDVI (NDVIMax) and minimum NDVI (NDVIMin) values among 30 m×30 m pixels within each PSP. Mean NDVI (NDVIMean) was computed by taking the mean of NDVI values of all pixels within a PSP. Canopy LAI ranged from 1.94 (Pidurutalagala) to 3.38 (Pitadeniya). The corresponding ranges for NDVIMax, NDVIMean and NDVIMin were 0.620-0.767, 0.594-0.764 and 0.429-0.747 respectively. Canopy LAI, NDVIMax and NDVIMean showed significant (p&lt;0.05) linear decreasing trends with increasing altitude. For every 1,000 m increase in altitude, LAI, NDVIMax and NDVIMean decreased by 0.396 (Adjusted-R2=0.407, AIC=-19.92), 0.066 (0.698,-66.72) and 0.058 (0.493,-61.27). In contrast, NDVIMin did not show a significant trend with altitude. Second-order polynomial functions showed greater explanatory power than the linear functions, in terms of adjusted-R2and AIC, in fitting the variation of LAI (Adj.-R2=0.492, AIC=-20.77) and NDVIMax with altitude (0.755,-68.15). The estimated maximum LAI and NDVIMax were at 637 and 329 m above sea level respectively. From among a range of multiple linear regression models using different combinations of NDVI, canopy architectural properties and altitude, the following two models were selected for predicting LAI, based on their adj-R2 and AIC values: LAI=1.269+[3.567.NDVIMax]–[1.598.NDVIMin]–[0.000215.Altitude] (Adj[1]R2=0.544, AIC=-21.41); LAI=-0.673+[5.887.NDVIMax]–[1.490.NDVIMin]–[0.000452.MLA] (0.489, -20.27).&#x0D; Keywords: Normalized Difference Vegetation Index, Leaf Area Index, Tropical rainforests, Altitude, Canopy architecture

Difference in seasonal peak timing of soybean far-red SIF and GPP explained by canopy structure and chlorophyll content

Recent advances in remotely sensed solar-induced chlorophyll fluorescence (SIF) have provided an exciting and promising opportunity for estimating gross primary production (GPP). Previous studies mainly focused on the linear correlation between SIF and GPP and the slope of the SIF-GPP relationship, both of which lack rigorous consideration of the seasonal trajectories of SIF and GPP. Here, we investigated the timing of seasonal peaks of far-red SIF and GPP in soybean fields by integrating tower data, satellite data, and process-based Soil Canopy Observation of Photosynthesis and Energy (SCOPE, v2.0) model simulations. We found inconsistency between the seasonal peak timing of far-red SIF and GPP in three of four soybean fields based on tower far-red SIF and eddy-covariance measurements. In particular, far-red SIF reached its seasonal maximum 14–17 days earlier than GPP. This far-red SIF-GPP difference in peak timing degraded the correlation between sunny-day far-red SIF and GPP at daily scale (Pearson r = 0.83–0.87 at the site with 14–17 days difference and Pearson r = 0.96 at the site with no difference), and it can be explained by a divergence in the seasonality between absorbed photosynthetic active radiation (APAR) and canopy chlorophyll content (ChlCanopy). We found that the seasonality of far-red SIF - a byproduct of the light reactions of photosynthesis - was primarily controlled by APAR, whereas GPP seasonality was dominated by ChlCanopy. Further, SCOPE model simulations showed that the seasonal patterns of leaf area index (LAI), leaf chlorophyll content (ChlLeaf) and leaf angle distribution (LAD) could affect the different peak timing of SIF and GPP and consequently the seasonal relationship between far-red SIF and GPP. A further increase in LAI after the fraction of light absorption (FPAR) saturates and a later peak of ChlLeaf compared to LAI results in a later peak of GPP compared to far-red SIF. More horizontal leaf angles can further exacerbate this difference. Our results advance mechanistic understanding of the SIF-GPP relationships and combining chlorophyll content information with SIF could potentially improve remote-sensing-based GPP estimation.

Land Management Explains the Contrasting Greening Pattern Across China‐Russia Border Based on Paired Land Use Experiment Approach

AbstractThe greening of the Earth over the last decades is predominantly indicated by the enhancements of leaf area index (LAI). Quantifying the relative contribution of multiple determinants, especially changes in climate and in land management changes (LMC), remains an arduous challenge. To solve this problem, we develop a simple yet novel data‐driven method, called the Paired Land Use Experiment (PLUE), for mesoscale analysis. Using PLUE, we analyze vegetation development of the Sanjiang Plain, a transboundary plain between China and Russia, with roughly homogeneous climate but with distinct land management practices across the border‐intensified agricultural development on China side (CNSP) versus largely little‐disturbed natural vegetation on Russia side (RUSP). Both CNSP and RUSP LAI show significant trends (p &lt; 0.05), with the annual variability reaching values of 9.8 × 10−3 yr−1 and 11.3 × 10−3 yr−1, respectively. However, in CNSP, the LAI increase is concentrated in the middle of the year, especially in five 8‐day periods from 26 June to 28 July. During this period, the LAI trend of CNSP is much higher than that of RUSP, at 92.7 × 10−3 yr−1 (p &lt; 0.01) and 43.8 × 10−3 yr−1 (p &lt; 0.01), respectively. Meanwhile, LAI decreased in CNSP at the begging and end of the growing season. The results show that different LMC practices lead to notably different seasonal variability in vegetation changes. The PLUE method offers a new potential tool in driver identification of vegetation greenness change based on observations. We argue for the necessity of parameterizing these different LMC in Earth system models.

Whether Increasing Maize Planting Density Increases the Total Water Use Depends on Soil Water in the 0–60 cm Soil Layer in the North China Plain

Increasing planting density generally increases total water use by maize (Zea mays L.), but there are contrasting conclusions as well. To determine whether increasing planting density would increase total water use by maize, a 3-year field experiment was conducted in the North China Plain. In 2018, maize was planted at the four densities of 57,100, 66,700, 80,000, and 100,000 plants ha−1. In 2019 and 2020, another four planting densities of 27,800, 41,700, 66,700, and 111,100 plants ha−1 were selected. The results showed that increasing planting density increased leaf area index but decreased leaf stomatal conductance; maize grain yield reached the maximum at about 80,000 plants ha−1. At the VE-V6 and R3-R6 stage, soil water use occurred mainly in the 0–60 cm soil layer, and planting density showed no effect on total soil water use by maize. At the V6-R3 stage, when soil water in the 0–60 cm soil layer was sufficient to meet the evapotranspiration demand, soil water use occurred mainly in the 0–60 cm soil layer; increasing planting density did not increase total soil water use. When soil water in the 0–60 cm soil layer was insufficient and could not meet the demand of evapotranspiration, soil water use in the 60–100 cm soil layer increased greatly and kept rising with increased planting density, resulting in elevated total soil water use. Therefore, we conclude that the effect of planting density on water use by maize varies with soil water content in the 0–60 cm soil layer in the North China Plain.

The sensitivities of ozone and PM2.5 concentrations to the satellite-derived leaf area index over East Asia and its neighboring seas in the WRF-CMAQ modeling system

Vegetation plays an important role as both a sink of air pollutants via dry deposition and a source of biogenic VOC (BVOC) emissions which often provide the precursors of air pollutants. To identify the vegetation-driven offset between the deposition and formation of air pollutants, this study examines the responses of ozone and PM2.5 concentrations to changes in the leaf area index (LAI) over East Asia and its neighboring seas, using up-to-date satellite-derived LAI and green vegetation fraction (GVF) products. Two LAI scenarios that examine (1) table-prescribed LAI and GVF from 1992 to 1993 AVHRR and 2001 MODIS products and (2) reprocessed 2019 MODIS LAI and 2019 VIIRS GVF products were used in WRF-CMAQ modeling to simulate ozone and PM2.5 concentrations for June 2019. The use of up-to-date LAI and GVF products resulted in monthly mean LAI differences ranging from −56.20% to 96.81% over the study domain. The increase in LAI resulted in the differences in hourly mean ozone and PM2.5 concentrations over inland areas ranging from 0.27 ppbV to −7.17 ppbV and 0.89 μg/m3 to −2.65 μg/m3, and the differences of those over the adjacent sea surface ranging from 0.69 ppbV to −2.86 ppbV and 3.41 μg/m3 to −7.47 μg/m3. The decreases in inland ozone and PM2.5 concentrations were mainly the results of dry deposition accelerated by increases in LAI, which outweighed the ozone and PM2.5 formations via BVOC-driven chemistry. Some inland regions showed further decreases in PM2.5 concentrations due to reduced reactions of PM2.5 precursors with hydroxyl radicals depleted by BVOCs. The reductions in sea surface ozone and PM2.5 concentrations were accompanied by the reductions in those in upwind inland regions, which led to less ozone and PM2.5 inflows. The results suggest the importance of the selective use of vegetation parameters for air quality modeling.

Integrated application of plant bioregulator and micronutrients improves crop physiology, productivity and grain biofortification of delayed sown wheat.

Delay sowing of wheat is a common problem in Punjab that exacerbates serious yield loss. To reduce yield loss and improve yield, different combinations of foliar-applied bioregulator and micronutrients, control (CK), zinc (Zn), boron (B), thiourea (TU), Zn + B (ZnB), Zn + TU (ZnTU), B + TU (BTU), Zn + B + TU (ZnBTU) were applied at booting and grain filling stages in delayed sown wheat in 2017-18 and 2018-19. The results showed that ZnBTU treatment significantly increased leaf area index by 25.06% and 23.21%, spike length by 15.11% and 19.65% in 2017 and 2018, respectively, compared to CK. The ZnBTU treatment also increased 1000-grain weight by 21.96% and 22.01% in 2017 and 2018, respectively, compared to CK. Similarly, higher Zn, B and N contents in straw and grain were recoded for ZnBTU treatment which was statistically similar to ZnB and ZnTU treatments. Overall, ZnBTU treatment also increased the photosynthetic rate, transpiration rate, stomatal conductance by 46.67%, 26.03%, 76.25% and decreased internal CO2 by 28.18%, compared to CK, respectively. Moreover, ZnBTU also recorded the highest grain yield in 2017-18 (25.05%) and 2018-19 (28.49%) than CK. In conclusion, foliar application of ZnBTU at the booting and grain filling stages of delayed sown wheat could be a promising strategy to increase grain yield.

Close‐spaced plant arrangement optimizes castor biomass and seed yields in tropical fall–winter conditions

AbstractThe high seed yield and optimum harvesting of short‐height castor (Ricinus communis L.) genotypes have enabled its large‐scale cultivation and introduction in the Brazilian cropping systems. Thus, studies to optimize plant density are essential to adequate plant population since this is the key management to influence castor biomass and seed production. This study aimed to evaluate the influence of plant density by altering plant arrangement (i.e., spacing between and within rows) on growth, biomass production and partitioning, and seed yield of a castor cultivar in fall–winter cropping season. Field experiments were conducted over two seasons in southeastern Brazil. Two close‐spaced (0.45 × 0.23 m and 0.45 × 0.44 m) and a traditional (0.90 × 0.44 m) plant arrangements were tested. Plant arrangements influenced plant growth, biomass production and partitioning, and seed yield. Compared to the traditional layout, close‐spaced plant arrangements resulted in thinner basal stems and lower leaf area per plant, but increased leaf area index. The plant arrangement with higher plant density increased per‐unit area production of stem plus leaf biomass (43–48%), which also resulted in increased (24%) seed yield, compared to traditional layout. Although a greater amount of biomass was partitioned to reproductive organs in close‐spaced plant arrangements, this allocation was not enough to influence the harvest index. Therefore, the adaptive performance of short‐height castor adjusting biomass partitioning to maximize stem plus leaf biomass production and seed yield at close‐spaced plant arrangement demonstrated this to be a suitable option to cultivate in the Brazilian fall–winter season.

Hyperspectral Reflectance Characteristics of Rice Canopies under Changes in Diffuse Radiation Fraction

To analyze the hyperspectral reflectance characteristics of rice canopies under changes in diffuse radiation fraction, experiments using different cover materials were performed in Nanjing, China, during 2016 and 2017. Each year, two treatments with different reduction ratios of diffuse radiation fraction but with similar shading rates were set in the field experiment: In T1, total solar radiation shading rate was 14.10%, and diffuse radiation fraction was 31.09%; in T2, total solar radiation shading rate was 14.42%, and diffuse radiation fraction was 39.98%, respectively. A non-shading treatment was included as a control (CK). Canopy hyperspectral reflectance, soil and plant analyzer development (SPAD), and leaf area index (LAI) were measured under shading treatments on different days after heading. The red-edge parameters (position, λ0; maximum amplitude, Dλ; area, α0; width, σ) were calculated, as well as the area, depth, and width of three absorption bands. The location of the first absorption band appeared in the range of 553–788 nm, and the second and third absorption bands appeared in the range of 874–1257 nm. The results show that the shading treatment had a significant effect on the rice canopy’s hyperspectral reflectance. Compared with CK, the canopy reflectance of T1 (the diffuse radiation fraction was 31.09%) and T2 (the diffuse radiation fraction was 39.98%) decreased in the visible light range (350–760 nm) and increased in the near-infrared range (800–1350 nm), while the red-edge parameters (λ0, Dλ, α0), SPAD, and LAI increased. On the other hand, under shading treatment, the increase in diffuse radiation fraction also had a significant impact on the hyperspectral spectra of the rice canopy, especially at 14 days after heading. Compared with T1, the green peak (550 nm) of T2 reduced by 16.12%, and the average reflectance at 800–900 nm increased by 10%. Based on correlation analysis, it was found that these hyperspectral reflectance characteristics were mainly due to the increase in SPAD (2.31%) and LAI (7.62%), which also led to the increase in Dλ (8.70%) and α0 (13.89%). Then, the second and third absorption features of T2 were significantly different from that of T1, which suggests that the change in diffuse radiation fraction could affect the process of water vapor absorption by rice.

淮河流域蒸散发时空变化与归因分析

PDF HTML阅读 XML下载 导出引用 引用提醒 淮河流域蒸散发时空变化与归因分析 DOI: 10.5846/stxb202104181005 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 科技部重大研发计划（2018YFC1506606）；淮河流域气象开放研究基金（HRM201804） Spatiotemporal changes and attribution analysis of evapotranspiration in the Huai River Basin Author: Affiliation: Fund Project: Major R&D program of Ministry of Science and Technology,Huai River Basin Meteorological Open Research Fund 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:蒸散发（Evapotranspiration，ET）是联结土壤-植被-大气过程的纽带，对理解地表水热平衡至关重要。因此，量化分析ET时空变化特征、揭示其主要控制因子对区域用水管理和农业生产十分重要。利用遥感数据和气象数据，基于BEPS模型估算了1981-2019年的淮河流域ET，分析了该区域ET时空分布特征，并通过敏感度系数和贡献率方法对该区域的ET多年变化特征进行了归因分析，最后借助数值实验方法深入探究影响特湿润年（2003年）ET较低的主要原因。结果表明：（1）1981-2019年淮河流域多年平均ET为549.83 mm，其中夏季ET占全年ET的比值达到47.63%；1981年以来区域ET整体呈极显著上升趋势（4.41 mm/a，P<0.01）；季节上，除冬季外，其他三个季节的ET增幅均呈显著性增加（P<0.05），四季增幅速率大小依次为：夏季>春季>秋季>冬季；空间上，中东部和南部ET较高，重心模型显示ET高值区域呈显著的由北向南的移动趋势；（2）归因分析结果表明，淮河流域ET对气温变化最敏感，其次为相对湿度、太阳总辐射、叶面积指数（LAI）和降水，但ET对LAI的正敏感性逐渐增强导致LAI的显著升高对流域ET年际变化贡献最大（44.5%），其次是气温的升高（25.93%）；同时，LAI是春、夏、秋三季ET变化的主导因素，气温是冬季ET变化的主导因素；（3）数值实验显示高相对湿度是引起特湿润年（2003年）ET明显偏低的最主要因素，这与导致长时间序列ET变化的原因不同。因此，建议今后加强极端气候条件下ET变化的归因分析，为更有效地应对全球气候变化提供决策服务。研究结果能够为认识淮河流域环境变化对水循环影响及合理分配区域水资源提供科学参考。 Abstract:Evapotranspiration (ET) is a link between soil-vegetation-atmosphere interactions, which is an essential process in understanding both water and energy balances of an ecosystem. Accurate quantitative analysis of its spatiotemporal changes with revealing sound underline forcing factors are of importance to promote the agricultural production and water management of a region. Based on the modified BEPS model, we used the remote sensing data and meteorological data to simulate ET in the Huai River Basin from 1981 to 2019 and analyzed its temporal and spatial changes. We further performed the attributional analysis to quantify its influencing factors with the help of the sensitivity index and contribution rate means. At last, we explored the main reasons for the lower ET in the special humid year of 2003 by numerical experimental methods. Results showed the following:(1) the long-term average annual ET of the Basin was 549.83 mm from 1981 to 2019, with the largest proportion in summer (47.63%). The evolution of the ET was an extremely significant increasing trend (4.41 mm/a, P<0.01) since 1981. Seasonally, the increase rates of ET in the other three seasons except winter exhibited obvious increasing trends (P<0.05). The increase rates of ET in the four seasons, in descending order, was summer, spring, autumn, and winter. Across the Basin, high ET values were observed in the central, eastern and southern regions. The center of gravity model showed that the area with high ET values moved significantly from north to south on the spatial scale. Attribution analysis showed that air temperature appeared the most sensitive driver for ET, followed by relative humidity and total solar radiation, leaf area index (LAI) and precipitation. However, the positive sensitivity of ET to the LAI gradually increased so that the significant increase in LAI contributed most to the interannual variabilities of ET (44.5%) in the Basin, followed by the increase of air temperature (25.93%). Correspondingly, we also found that LAI was the leading factor in ET of the spring, summer and autumn, while air temperature was the most significant variable for the winter ET. Finally, our numerical experiments indicated that the high relative humidity was the most important factor responsible for the Basin's low ET in 2003- a year with high humid, which is different from the attribution of the long-term ET changes. It is suggested to strengthen the attribution analysis of ET under extreme climate conditions in the future, so as to provide decision-making service for coping with global climate change more effectively. The results could provide scientific guide for understanding environmental influence to water cycle and the rational allocation of regional water resources in the Huai River Basin. 参考文献 相似文献 引证文献

Hydrological feedback from projected Earth greening in the 21st century

Earth satellites have observed continuous increasing vegetation growth during the past four decades, a phenomenon called Earth greening. Nearly all Earth System Models (ESMs) participating in Coupled Model Intercomparison Project (CMIP) for Intergovernmental Panel on Climate Change (IPCC) project a continuous greening of the planet during the 21st century. To investigate the hydrological feedback from the projected Earth greening, we prescribed the increase in leaf area index (LAI) in the 21st century as projected by CMIP5 ESMs into a state-of-the-art ESM (IPCLCM), and simulated equilibrium climates for current CO2 and LAI, an increase of CO2 alone, an increase of LAI alone, and increases of both CO2 and LAI, respectively. We find that the greening simultaneously intensifies evapotranspiration and precipitation over land. In terms of soil moisture content, the spatial difference between the responses of evapotranspiration and precipitation causes a hydrological response of the "dry gets drier, wet gets wetter" (DDWW) paradigm. Increasing LAI significantly decreases soil moisture content over dry regions, including the Western North America, Southern South America, East Siberia, Central Asia, South Asia, Northern China, Sahel, Southern Africa, and Australia. Over wet regions, such as the Amazon and Congo rainforests, the greening-induced increase of terrestrial evapotranspiration favors more convective precipitation, so that the new equilibrium does not decrease soil moisture content. The DDWW paradigm in terms of P-ET response does not hold over wet areas. To mitigate climate change with forestry, policymakers should prevent degradation of existing forests, support afforestation over wet regions, and avoid planting trees in dry regions.

EFFECT OF METHODS OF APPLICATION OF RHIZOBACTERIA AND PHOSPHATE FERTILIZER RATES ON GROWTH AND YIELD OF SOYBEAN [GLYCINE MAX (L). Merril] IN MAKURDI

Field experiment was carried out during the 2018 cropping season at the Teaching and Research Farm of Joseph Sarwuan Tarka University, Makurdi to determine the effect of methods of application of rhizobacteria and phosphate fertilizer rates on the growth and yield of soybean. Treatments were four rates of phosphate fertilizer (0, 20, 40, and 60 kg P2O5 ha-1) and three rhizobacteria inoculant application methods (zero, seed and soil). The crop was grown to maturity and harvested. Data collected were number of leaves, Leaf Area, Leaf Area Index, Net Assimilation Rate, Crop Growth Rate, Days to 50% flowering, Total Dry Matter, number of nodules, nodules weight, seed yield and 100 seed weight. The collected data were subjected to the analysis of variance (ANOVA) at 5 % level of probability using GenStat 17th Edition. Significant differences in means were separated using Fischers Least Significant Difference [FLSD (0.05)]. The results from the study showed that combined application of rhizobacteria and phosphate fertilizer at 60 kg P2O5 ha-1 increased leaf area index and total dry matter yield of soybean significantly (P&lt;0.05) with leaf area index of 10.19 and total dry matter of 72 g per plant as compared to leaf area index at 0 kg P2O5 ha-1, 20 kg P2O5 ha-1, 40 kg P2O5 ha-1 (7.97, 8.93 and 9.73) dry matter at 0 kg P2O5 ha-1, 20 kg P2O5 ha-1, 40 kg P2O5 ha-1 (16.6g, 59.4g and 65.2g) per plant. The result of this study showed combination application of rhizobacteria inoculation and phosphate significantly enhanced nodulation from 43 nodules in un-inoculated control to 156 and 175 nodules per plant in rhizobacteria inoculated and phosphate treatments. The result of the study showed that combined application method of seed inoculation of rhizobacteria at 100g per 15kg of seed at 60 kg P2O5 ha-1 phosphate was more economical and had more yield benefits than single application and therefore, stand recommended.

Hyperspectral Characteristics and Scale Effects of Leaf and Canopy of Summer Maize under Continuous Water Stresses

The scale effect problem is one of the most challenging issues in remote sensing studies. However, the research on the methodology and theory of the scale effect is scarcely applied in practice. To this end, in this study, 3 years of field experimental data of continuous water stresses on summer maize were used for this purpose. Furthermore, the Prospect and Sail models were employed to investigate the scale effects of reflectance characteristics and vegetation indexes. The results indicated that the spectral characteristics of canopy and leaf of summer maize were similar under continuous water stresses at various stages. The reflectance at the canopy level was distinct from that at the leaf level, considering the soil background differences. From leaf to canopy scales, with the increase in the leaf area index (LAI), the spectral reflectance of all treatments in the visible band decreased, but increased in the near-infrared band, and the reflectance was saturated when LAI increased to 5. The reflectance difference caused by LAI variation was enlarged as the drought stress intensified in the short-wave infrared band. The spectral reflectance in the near-infrared band was susceptible to leaf inclination angle (LIA) variation and changed significantly, especially in the closed canopy. With the increase in LAI, the difference vegetation index (DVI) and normalized difference vegetation index (NDVI) values under each treatment showed a gradually increasing trend. With the increase in LIA, the DVI value decreased gradually, and the DVI value under the saturated canopy was significantly higher than that under the unclosed canopy. However, the NDVI values of all treatments did not change with LIA, mostly under the closed canopy. Overall, the results demonstrated that LAI had a more significant influence on canopy reflectance than LIA. In addition, NDVI was not able to capture the LAI and LIA information when the canopy was closed, but DVI performed better.