Minimum Leaf Area Index Research Articles

Impacts of Extreme Climates on Vegetation at Middle-to-High Latitudes in Asia

In this study, we investigated the synchronous responses of vegetation to extreme temperatures and/or precipitation at middle-to-high latitudes in Asia using semi-monthly observations of the GIMMS and GLASS leaf area index (LAI) from 1982 to 2016. The extreme vegetation and climate states were specified using standard anomalies of the annual cycle with removed variables. The results show that the area with the maximum or minimum LAI increased or decreased in correspondence with global warming. Both the GIMMS and GLASS LAI mostly reached their maximum in spring and autumn. The GIMMS LAI mostly reached its minimum in summer, while the GLASS LAI mostly reached its minimum in late spring or late summer. The GIMMS and GLASS datasets were generally consistent regarding the vegetation responses to extreme temperatures and precipitation, especially in the areas covered by trees. Extreme cold and/or wet conditions inhibited forest growth in the area south of 60 °N, particularly from October to November. Extreme hot and/or dry conditions promoted forest growth, particularly in the central and northern parts of Siberia from August to September. However, in some arid areas of Central Asia and the Mongolian Highlands, which are mostly covered by sparse vegetation and grasses, low temperature extremes and/or strong precipitation promoted vegetation growth, while high temperature extremes and/or low precipitation had adverse effects on vegetation growth. This was more apparent in the GIMMS LAI than it was in the GLASS LAI, since the GIMMS dataset supplied more values representing extreme states of vegetation. The compound extreme of hot-and-dry and cold-and-wet climates were more frequent than the combination of cold and dry climates and hot-and-wet climates were. The overall positive response of the vegetation was superior to the negative response. The results of this study suggest that a continuous increase in vegetation density and coverage will occur over the boreal region in the future if the warming trend persists. The consequent climate feedback in this area on the regional and global scales should be afforded more attention.

Effects of forest growth in different vegetation communities on forest catchment water balance

Forest ecosystems are critical for adjusting the dynamic balance of the hydrological cycle. This balance is affected by vegetation community types, phenology, and forest density. Previous long-term catchment-scale model studies have focused on changes in forest areas while ignoring the above factors. Since the 1980s, climate change caused by increases in atmospheric CO2 levels has enhanced forest growth. Moreover, amendments to forest management policies, including intermediate cuttings caused by economic factors, have yielded unprecedented changes in forest ecosystems. In this study, we designed a methodology and created a credible model using the Soil and Water Assessment Tool (SWAT) that can precisely reflect water balance variations caused by different ecosystem situations during long-term changes in forest density. We focused on the Yamato River catchment in Western Japan, which includes three planted forests and one primeval forest, each markedly different with respect to vegetation community composition and management policy. In the process, we examined the ratio of coniferous vegetation and broad-leaved vegetation in different forest areas, used remote sensing methods to quantify the maximum and minimum leaf area index (LAI) of each forest region over 40 years, and calibrated the model by comparing the LAI growth curve, evapotranspiration, and streamflow with observed data. Moreover, we separated the decadal canopy evaporation, transpiration, and soil evaporation from the SWAT output results. We found that (1) forest evapotranspiration has increased in recent decades because of the above reasons; (2) in young or well-managed forests, the forest water balance may have changed significantly with forest growth. For long-term studies, it is necessary to distinguish the growth characteristics of different forests during different periods, and a detailed definition of a mixed forest is required. The forest parameters and growth characteristics are critical for understanding forest ecosystems and cannot be ignored at catchment-scale.

Canopy management to improve fruit quality of Coe Red Fuji, Granny Smith and Spartan varieties of apple (Malus domestica)

Light management within apple ( Malus domestica Borkh.) canopies has been an invariable rationale of fruit tree architecture strategy during the development of training systems. This paper attempts to compare fruit quality characteristics of three apple cultivars Coe Red Fuji, Granny Smith and Spartan trained on three canopy architectural engineering (training) system, viz. Espalier, Vertical axis and Cordon were grafted on M 9 rootstock. The maximum fruit weight (210.11g) was observed in Granny Smith and maximum yield per tree (32.11 kg/cm2) and yield efficiency (0.69 kg/cm2) in Coe Red Fuji which may be due to higher crop density. Among training systems, maximum fruit weight (200.12 g), highest yield per tree (36.36 kg) and maximum yield efficiency (0.72 kg/cm2) was observed in espalier training system. The interaction study displayed maximum fruit weight in Granny Smith (210.55g), highest yield per tree in Coe Red Fuji (32.16 kg) and maximum yield efficiency in Spartan on Espalier system. Light interception demonstrated maximum photon flux density (237 µmolm-2 s-1) across the canopy of Spartan with minimum leaf area index (0.30) and among training systems maximum PPFD (221 µmolm-2s-1) was observed in Espalier system with minimum LAI (0.21). Fruit size, TSS and colour parameters of fruits in all varieties were significantly influenced by light intensity. Higher the light intensity, higher was the TSS and colour development in coloured varieties like Spartan and Coe Red Fuji. Therefore, espalier training system was found the best canopy management system allowing maximum PAR penetration and diffusion leading better fruit quality and productivity.

Effect of bio-regulators on vegetative parameters of Asiatic lily var Pavia under protected condition

An investigation on “Effect of bio-regulators on vegetative parameters of Asiatic lily var. Pavia under protected condition” was carried out at Department of Floriculture and Landscape Architecture, College of Horticulture, Mudigere (Under University of Agricultural and Horticultural sciences, Shivamogga), during 2018-19. The treatments comprised of, GA3 (100, 150 and 200 ppm), BA (150, 300 and 450 ppm), NAA (100,150 and 200 ppm) and CCC (1000, 1500 and 2000 ppm) and control. The results revealed that GA3 @ 200 ppm recorded minimum days to sprouting (3.33), maximum plant height (98.44 cm), number of leaves (80.93), leaf length (12.53 cm), leaf breadth (2.77 cm), leaf area (1704.60 cm2) and leaf area index (LAI) (5.68). The maximum number of days for sprouting (16.67), minimum plant height (21.93 cm), minimum number of leaves (31.77), minimum length of leaves (4.27 cm), breadth of leaves (1.37 cm), minimum leaf area (442.45 cm2) and minimum LAI (1.47) was recorded by BA @ 450 ppm. NAA @ 100 ppm recorded maximum chlorophyll-a, chlorophyll-b and total chlorophyll content (98, 0.50 and 1.48 mg per g fresh weight, respectively). Whereas BA @ 450 ppm was recorded minimum chlorophyll-a, chlorophyll-b and total chlorophyll content (0.63, 0.22 and 0.85 mg per g fresh weight, respectively).

The effect of satellite-derived surface soil moisture and leaf area index land data assimilation on streamflow simulations over France

Abstract. This study evaluates the impact of assimilating surface soil moisture (SSM) and leaf area index (LAI) observations into a land surface model using the SAFRAN–ISBA–MODCOU (SIM) hydrological suite. SIM consists of three stages: (1) an atmospheric reanalysis (SAFRAN) over France, which forces (2) the three-layer ISBA land surface model, which then provides drainage and runoff inputs to (3) the MODCOU hydro-geological model. The drainage and runoff outputs from ISBA are validated by comparing the simulated river discharge from MODCOU with over 500 river-gauge observations over France and with a subset of stations with low-anthropogenic influence, over several years. This study makes use of the A-gs version of ISBA that allows for physiological processes. The atmospheric forcing for the ISBA-A-gs model underestimates direct shortwave and long-wave radiation by approximately 5 % averaged over France. The ISBA-A-gs model also substantially underestimates the grassland LAI compared with satellite retrievals during winter dormancy. These differences result in an underestimation (overestimation) of evapotranspiration (drainage and runoff). The excess runoff flowing into the rivers and aquifers contributes to an overestimation of the SIM river discharge. Two experiments attempted to resolve these problems: (i) a correction of the minimum LAI model parameter for grasslands and (ii) a bias-correction of the model radiative forcing. Two data assimilation experiments were also performed, which are designed to correct random errors in the initial conditions: (iii) the assimilation of LAI observations and (iv) the assimilation of SSM and LAI observations. The data assimilation for (iii) and (iv) was done with a simplified extended Kalman filter (SEKF), which uses finite differences in the observation operator Jacobians to relate the observations to the model variables. Experiments (i) and (ii) improved the median SIM Nash scores by about 9 % and 18 % respectively. Experiment (iii) reduced the LAI phase errors in ISBA-A-gs but had little impact on the discharge Nash efficiency of SIM. In contrast, experiment (iv) resulted in spurious increases in drainage and runoff, which degraded the median discharge Nash efficiency by about 7 %. The poor performance of the SEKF originates from the observation operator Jacobians. These Jacobians are dampened when the soil is saturated and when the vegetation is dormant, which leads to positive biases in drainage and/or runoff and to insufficient corrections during winter, respectively. Possible ways to improve the model are discussed, including a new multi-layer diffusion model and a more realistic response of photosynthesis to temperature in mountainous regions. The data assimilation should be advanced by accounting for model and forcing uncertainties.

Studying Maize Growth Indices in Different water Stress Conditions and the use of Humic Acid

An experiment was conducted in split plots in a completely randomized block design with three replications to evaluate the impact of drought stress on physiological indices of maize growth and the effect of humic acid fertilizer on alleviating drought stress. The main factor included three irrigation levels of 100%, 75%, and 50% and sub-factor was the use and non-use of humic acid. The results showed that in all different levels of irrigation and humic acid treatments, the index of leaf area index (LAI), crop growth rate (CGR) and dry matter accumulation are sigmoid. The highest LAI was (4.5) and biological yield was (15.5 ha) in full irrigation treatment with humic acid, and minimum LAI was (3) with biological yield (8.8 tons per hectare) in 50% irrigation treatment and non-use of humic acid. The results showed that LAI and receiving light were the most important factor affecting the growth indices. Moreover, the highest and lowest CGR CGR, relative growth rate (RGR) RGR and net absorption rate (NAR) were related to full irrigation + consumption of humic acid and 50% irrigation and non-use of humic acid respectively. Overall, the results showed that in without stress treatment (irrigation 100%), the use of humic acid compared to non-use increased RGR, CGR, NAR and LAI at 1.3%, 21%, 8% and 12.5% respectively. This is while in water stress (irrigation 50%), humic acid consumption increased these indices 7%, 25%, 14% and 30% respectively representing a reduction drought stress by humic acid. In general, it could be argued that the use of humic acid, due to adjusting the drought, could have a positive role in water stress to reduce the use of chemical fertilizers, reducing environmental pollution, and to mitigate drought stress, and as is suggested a stable source of supplying nutrients in drought conditions for maize.

Sward Structure and Herbage Accumulation of Massai Guineagrass Pastures Managed According to Pre-Grazing Heights, in the Northeast of Brazil

The forage sward height measurement is a practical and potential tool for grazing management. Thus, the objective of this study was to evaluate the structure of pasture and forage accumulation related to sward pre-grazing height of Panicum maximum cv. Massai, before being grazed by sheep. The study was conducted in the Federal University of Rio Grande do Norte, Macaíba, Brazil. The treatments were the pre-grazing sward heights at: 35, 40, 45 and 50 cm. The post-grazing height was 15 cm for all treatments. The interaction between the pre-grazing sward heights and grazing cycles was only statistically significant for light interception (LI) and leaf area index (LAI). The LI had linear and positive effect to the pre-grazing heights in only one of three grazing cycles, with approximately 1% increase in LI for each centimeter grown in the sward. The total forage mass had linear regression, every centimeter increased in height, there was a correspondent dry matter (DM) increase of 187 kg ha-1 in forage mass. There was a linear response between leaf blade mass and dead material with sward height. The post-grazing lowest LI was 29.42% at 42.05 cm high. The lowest amount of LI was 29.42% at 42.05 cm high. The minimum LAI was 0.69. The top DM and mineral matter (MM) accumulation rate were linear and had 58.32 and 20.46 kg ha-1 day-1 MS, respectively. Massai guineagrass grazed by sheep must be handled between 35 and 40 cm high at pre-grazing when associated with post-grazing height of 15 cm.

Space-time LAI variability in Northern Puglia (Italy) from SPOT VGT data.

The vegetation space–time variability during 1999–2010 in the North of the Apulian region (Southern Italy) was analysed using SPOT VEGETATION (VGT) sensor data. Three bands of VEGETATION (RED, NIR and SWIR) were used to implement the vegetation index named reduced simple ratio (RSR) to derive leaf area index (LAI). The monthly average LAI is an indicator of biomass and canopy cover, while the difference between the annual maximum and minimum LAI is an indicator of annual leaf turnover. The space–time distribution of LAI at the catchment scale was analysed over the examined period to detect the consistency of vegetation dynamics in the study area. A diffuse increase of LAI was observed in the examined years that cannot be directly explained only in terms of increasing water availability. Thus, in order to explain such a general behaviour in terms of climatic factors, the analysis was performed upon stratification of land cover classes, focusing on the most widespread species: forest and wheat. An interesting ascending–descending behaviour was observed in the relationship between inter-annual increments of maximum LAI and rainfall, and in particular, a strong negative correlation was found when the rainfall amount in January and February exceeded a critical threshold of about 100 mm.

Satellite‐derived estimates of forest leaf area index in southwest Western Australia are not tightly coupled to interannual variations in rainfall: implications for groundwater decline in a drying climate

There is increasing concern that widespread forest decline could occur in regions of the world where droughts are predicted to increase in frequency and severity as a result of climate change. The average annual leaf area index (LAI) is an indicator of canopy cover and the difference between the annual maximum and minimum LAI is an indicator of annual leaf turnover. In this study, we analyzed satellite-derived estimates of monthly LAI across forested coastal catchments of southwest Western Australia over a 12year period (2000-2011) that included the driest year on record for the last 60years. We observed that over the 12year study period, the spatial pattern of average annual satellite-derived LAI values was linearly related to mean annual rainfall. However, interannual changes to LAI in response to changes in annual rainfall were far less than expected from the long-term LAI-rainfall trend. This buffered response was investigated using a physiological growth model and attributed to availability of deep soil moisture and/or groundwater storage. The maintenance of high LAIs may be linked to a long-term decline in areal average underground water storage and diminished summer flows, with an emerging trend toward more ephemeral flow regimes.

ANALYSIS OF SPATIO-TEMPORAL PATTERNS OF LEAF AREA INDEX IN DIFFERENT FOREST TYPES OF INDIA USING HIGH TEMPORAL REMOTE SENSING DATA

Abstract. Knowledge of temporal variations of Leaf Area Index (LAI) aids in understanding the climate-vegetation interaction of different vegetative systems. This information is amenable from high temporal remote sensing data. India has around 78.37 million hectare, accounting for 23.84% of the geographic area of the country under forest/tree cover. India has a diverse set of vegetation types ranging from tropical evergreen to dry deciduous. We present a detailed spatio-temporal and inter-seasonal analysis of LAI patterns in different forest types of India using MODIS 8-day composites global LAI/fPAR product for the year 2005 at 1-km spatial resolution. A forest cover mask was generated using SPOT 1-km landuse/landcover classification over the Indian region. The range of estimated LAI varied from 0.1–6.9 among the different forest types. Maximum LAI was observed in tropical evergreen forests in North-Eastern region and Western Ghats. Low LAI was observed in Central Indian region due to predominance of dry deciduous forests. The spatial patterns of seasonal variations detected that for most of the forest types, the peak LAI values were observed during September and October months of the autumn season in contrast to minimum LAI during summer season. The mean LAI and standard deviation for each 8-day LAI composite were also computed and mean monthly LAI profiles were derived for each forest type classified on the basis of their geographical locations. These results are useful indicators for detailed understanding of phenological sequence and may also serve as important inputs for deriving bioclimatic indices for different forest types of India.

Herbicide Effects on Visible Injury, Leaf Area, and Yield of Glyphosate-Resistant Soybean (Glycine max)1

The failure of glyphosate to control all weeds throughout the entire growing season has sometimes prompted growers to use herbicides other than glyphosate on glyphosate-resistant soybean. Field studies were conducted in 1999 and 2000 to investigate potential crop injury by several herbicides in glyphosate-resistant soybean and to determine the relationships between soybean maturity group, planting date, and herbicide treatment on soybean injury, leaf area index (LAI), and yield. Glyphosate-resistant soybean generally recovered from early-season herbicide injury and LAI reductions; however, some treatments reduced yield. Yield reductions were more common in double-crop soybean than in full-season soybean. In full-season soybean, most yield reductions occurred in the early-maturing ‘RT-386’ cultivar. These yield reductions may be attributed to reduced developmental periods associated with early-maturing cultivars and double-crop soybean that often lead to reduced vegetative growth and limited LAI. Reductions in LAI by some herbicide treatments were not necessarily indicative of yield loss. Further yield reductions associated with herbicide applications occurred, although soybean sometimes produced leaf area exceeding the critical LAI level of 3.5 to 4.0, which is the minimum LAI needed for soybean to achieve maximum yield. Therefore, LAI response to herbicide treatments does not always accurately indicate the response of glyphosate-resistant soybean yield to herbicides.Nomenclature: Glyphosate; soybean, Glycine max (L.) Merr.Additional index words: Double-crop soybean, full-season soybean, soybean maturity group.Abbreviations: EPSPS, 5-enolpyruvylshikimate-3-phosphate synthase (EC 2.5.1.19); fb, followed by; LAI, leaf area index; PRE, preemergence; POST, postemergence; WAP, weeks after planting.

Evaluation of the Utility of Satellite-Based Vegetation Leaf Area Index Data for Climate Simulations

Abstract In this study the utility of satellite-based leaf area index (LAI) data in improving the simulation of near-surface climate with the NCAR Community Climate Model, version 3 (CCM3), GCM is evaluated. The use of mean LAI values, obtained from the Advanced Very High Resolution Radiometer Pathfinder data for the 1980s, leads to notable warming and decreased precipitation over large parts of the Northern Hemisphere lands during the boreal summer. Such warming and decreased rainfall reduces discrepancies between the simulated and observed near-surface temperature and precipitation fields. The impact of interannual vegetation extremes observed during the 1980s on near-surface climate is also investigated by utilizing the maximum and minimum LAI values from the 10-yr LAI record. Surface energy budget analysis indicates that the dominant impact of interannual LAI variations is modification of the partitioning of net radiant energy between latent and sensible heat fluxes brought about through changes in th...

Seasonal changes of leaf area index (LAI) in a tropical deciduous forest in west Mexico

Light canopy transmittance and the Beer-Lambert equation were utilized to assess monthly leaf area index (LAI) of a tropical deciduous forest ecosystem on the west coast of Mexico. The light transmittance coefficient ( k) was obtained by analyzing vertical leaf and light distribution in the forest canopy. An independent LAI estimate was obtained using litterfall data. The calculated k value was 0.610 ± 0.035 (standard error). Average maximum LAI obtained with litterfall data was 4.2 ± 0.4 m 2m −2. There was a significant correlation ( P < 0.001, r = 0.98) between litter-LAI estimations and those obtained with the Beer-Lambert equation. The regression explained 95% of the variation; however, light-LAI overestimated litter-LAI by a constant of 0.87 ± 0.12 m 2 m −2 (the slope was 1.03 and Y intercept was 0.87). The discrepancy is partially attributed to leaf retention of the few evergreen species, and perhaps leaf retention of a few deciduous species beyond the end of the litterfall collection. Maximum annual LAI was similar in both study years (4.5 ± 0.3 m 2 m −2 in 1990 and 4.9 ± 0.4 in 1991). Minimum LAI showed considerable variation between years with similar values in the dry seasons of 1990 and 1991 (1.0 ± 0.1 m 2 and 0.9 ± 0.1 m 2 m −2, respectively), but much higher values in 1992 (2.7 ± 0.2 m 2 m −2). The difference is probably attributed to an atypical rainfall event in January 1992 (644 mm), which retarded leaf abscission.

Remote Sensing of Seasonal Leaf Area Index Across the Oregon Transect

Remotely sensed data acquired from four remote—sensing instruments on three different aircraft platforms over a transect of coniferous forest stands in Oregon were analyzed with respect to seasonal leaf area index (LAI). Data from the four instruments were corrected for the varying seasonal and geographic atmospheric conditions present along the transect. Strong logarithmic relationships were observed between seasonal maximum and minimum LAI and the simple ratio (SR) (near infrared/red reflectance) calculated from the broad—spectral—band Thematic Mapper Simulator (TMS), as well as from the narrow—spectral—band Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), the Compact Airborne Spectrographic Imager (CASI), and the Spectrom SE590 spectro—radiometer (R2 = 0.82—0.97). The TMS SR reached an asymptote at an LAI of °7—8. However, the SE590 and the CASI SR continued to increase up to the maximum LAI of 10.6. The variability of the relationship between the AVIRIS SR and LAI increased at stands with LAIs &gt;7, making a trend in the AVIRIS SR—LAI relationship at LAIs &gt;7 difficult to discern. The SRs of the coniferous forest stands measured by the narrow—spectral—band instruments were higher than they were from the broad—spectral—band TMS. This is attributed partially to the integration of the TMS over a broad wavelength region in the red and more strongly to calibration differences between the sensors. Seasonal TMS SR trends for four time periods for some of the stands deviated from the expected seasonal LAI trends, possibly because of smoke and very low sun angles during some of the acquisition periods. However, the expected SR differences for the seasonal minimum and maximum LAI were observed for all of the sensors for nearly all of the forest stands. This study demonstrates that remotely sensed data from both broad— and narrow—spectral—band instruments can provide estimates of LAI for use in forest ecosystem simulation models to estimate evapotranspiration, photosynthesis, canopy turnover, and net primary production over large areas.

EFFECTS OF CLIPPING AND NITROGEN ON COMPETITION BETWEEN THREE PASTURE SPECIES

In three herbage mixtures comprised of different combinations of orchardgrass, Dactylis glomerata L., creeping red fescue, Festuca rubra L., and common white clover, Trifolium repens L., highest yields of the grasses were obtained when 1) harvesting was delayed until only 2 per cent of the incident light near mid-day penetrated to the base of the sward rather than at 10 per cent penetration, 2) a 2-inch rather than a 4-inch stubble was left after cutting, and 3) nitrogen fertilizer was applied. The same cutting treatments gave maximum yields of the associated clover without nitrogen fertilization, but when nitrogen was applied higher clover yields were obtained when cutting was at 10 per cent light penetration. Yields of the two grasses were approximately the same when grown with clover only, but in the two-grass association orchardgrass held the fescue to a low proportion in the mixture.Results did not support the concept of maintaining a specified minimum leaf area index (LAI) for maximum yield of the herbage mixture.