Relationships between physiological traits and productivity of sugarcane in response to water deficit

The relationships between physiological variables and sugarcane productivity under water deficit conditions were investigated in field studies during 2005 and 2006 in Weslaco, Texas, USA. A total of 78 genotypes and two commercial varieties were studied, one of which was drought-tolerant (TCP93-4245) and the other drought-sensitive (TCP87-3388). All genotypes were subjected to two irrigation regimes: a control well-watered treatment (wet) and a moderate water-deficit stress (dry) treatment for a period of 90 days. Maximum quantum efficiency of photosystem II (F (v)/F (m)), estimated chlorophyll content (SPAD index), leaf temperature (LT), leaf relative water content (RWC) and productivity were measured. The productivity of all genotypes was, on average, affected negatively; however, certain genotypes did not suffer significant reduction. Under water deficit, the productivity of the genotypes was positively and significantly correlated with F (v)/F (m), SPAD index and RWC, while LT had a negative correlation. These findings suggest that genotypes exhibiting traits of high RWC values, high chlorophyll contents and high photosynthetic radiation use efficiency under low moisture availability should be targeted for selection and variety development in programmes aimed at improving sugarcane for drought prone environments.

Response of nutrient cycles of an old-growth montane forest in Ecuador to experimental low-level nutrient amendments

Atmospheric nitrogen (N) and phosphorus (P) depositions are expected to increase in the tropicsrnas a consequence of increasing human activities in the next decades. Furthermore, a possiblernshortened El Niño Southern Oscillation cycle might come along with more frequent calcium (Ca)rndepositions on the eastern slope of the Ecuadorian Andes originating from Saharan dust. It isrncrucial to understand the response of the old-growth montane forest in Ecuador to increasedrnnutrient deposition to predict the further development of this megadiverse ecosystem.rnI studied experimental additions of N, P, N+P and Ca to the forest and an untreatedrncontrol, all in a fourfold replicated randomized block design. These experiments were conductedrnin the framework of a collaborative research effort, the NUtrient Manipulation EXperimentrn(NUMEX). I collected litter leachate, mineral soil solution (0.15 and 0.30 m depths), throughfallrnand fine litterfall samples and determined N, P and Ca concentrations and fluxes. This approachrnalso allowed me to assess whether N, P and/or Ca are limiting nutrients for forest growth.rnFurthermore, I evaluated the response of fine root biomass, leaf area index, leaf area and specificrnleaf area, tree diameter growth and basal area increment contributed from a cooperating group inrnthe Ca applied and control treatments.rnDuring the observation period of 16 months after the first fertilizer application, less thanrn10, 1 and 5% of the applied N, P and Ca, respectively, leached below the organic layer whichrncontained almost all roots but no significant leaching losses occurred to the deeper mineral soil.rnDeposited N, P and Ca from the atmosphere in dry and wet form were, on balance, retained in therncanopy in the control treatment. Retention of N, P and Ca in the canopy in their respectiverntreatments was reduced resulting in higher concentrations and fluxes of N, P and Ca inrnthroughfall and litterfall. Up to 2.5% of the applied N and 2% of the applied P and Ca werernrecycled to the soil with throughfall. Fluxes of N, P and Ca in throughfall+litterfall were higher inrnthe fertilized treatments than in the control; up to 20, 5 and 25% of the applied N, P and Ca,rnrespectively, were recycled to the soil with throughfall+litterfall.rnIn the Ca-applied plots, fine root biomass decreased significantly. Also the leaf area of thernfour most common tree species tended to decrease and the specific leaf area increasedrnsignificantly in Graffenrieda emarginata Triana, the most common tree species in the study area.rnThese changes are known plant responses to reduced nutrient stress. Reduced aluminium (Al)rntoxicity as an explanation of the Ca effect was unlikely, because of almost complete organocomplexationrnof Al and molar Ca:Al concentration ratios in solution above the toxicity threshold.rnThe results suggest that N, P and Ca co-limit the forest ecosystem functioning in thernnorthern Andean montane forests in line with recent assumptions in which different ecosystemrncompartments and even different phenological stages may show different nutrient limitationsrn(Kaspari et al. 2008). I conclude that (1) the expected elevated N and P deposition will bernretained in the ecosystem, at least in the short term and hence, quality of river water will not bernendangered and (2) increased Ca input will reduce nutrient stress of the forest.

Modelling agro-forestry scenarios for ammonia abatement in the landscape

Ammonia emissions from livestock production can have negative impacts on nearby protected sites and ecosystems that are sensitive to eutrophication and acidification. Trees are effective scavengers of both gaseous and particulate pollutants from the atmosphere making tree belts potentially effective landscape features to support strategies aiming to reduce ammonia impacts. This research used the MODDAS-THETIS a coupled turbulence and deposition turbulence model, to examine the relationships between tree canopy structure and ammonia capture for three source types?animal housing, slurry lagoon, and livestock under a tree canopy. By altering the canopy length, leaf area index, leaf area density, and height of the canopy in the model the capture efficiencies varied substantially. A maximum of 27% of the emitted ammonia was captured by tree canopy for the animal housing source, for the slurry lagoon the maximum was 19%, while the livestock under trees attained a maximum of 60% recapture. Using agro-forestry systems of differing tree structures near ?hot spots? of ammonia in the landscape could provide an effective abatement option for the livestock industry that complements existing source reduction measures.

The potential for increasing rubber production by matching tapping intensity to leaf area index

Understanding resource capture can help design appropriate species combinations, planting designs and management. Leaf area index (LAI) and its longevity are the most important factors defining dry matter production and thus growth and productivity. The ecophysiological modifications and yield of rubber (Hevea spp.) in an agroforestry system (AFS) with beans (Phaseolus vulgaris L.) were studied. The experiment was established in Southeast-Brazil, with three rubber cultivars: IAN 3087, RRIM 600 and RRIM 527. The AFS comprised double rows of rubber trees along with beans sown in autumn and winter seasons in 1999. There was about 50% higher rubber yield per tree in the AFS than the rubber monoculture. Trees within the AFS responded to higher solar radiation availability with higher LAI and total foliage area, allowing its greater interception. All three cultivars had higher LAI in the AFS than monoculture, reaching maximum values in the AFS between April and May of 3.17 for RRIM 527; 2.83 for RRIM 600 and 2.28 for IAN 3087. The maximum LAI values for monocrop rubber trees were: 2.65, 2.62 and 1.99, respectively, for each cultivar. Rubber production and LAI were positively correlated in both the AFS and monoculture but leaf fall of rubber trees in the AFS was delayed and total phytomass was larger. It is suggested that trees in the AFS were under exploited and could yield more without compromising their life cycle if the tapping system was intensified. This shows how knowledge of LAI can be used to manage tapping intensity in the field, leading to higher rubber yield.

Leaf area index estimation with MODIS reflectance time series and model inversion during full rotations of Eucalyptus plantations

The leaf area index (LAI) of fast-growing Eucalyptus plantations is highly dynamic both seasonally and interannually, and is spatially variable depending on pedo-climatic conditions. LAI is very important in determining the carbon and water balance of a stand, but is difficult to measure during a complete stand rotation and at large scales. Remote-sensing methods allowing the retrieval of LAI time series with accuracy and precision are therefore necessary. Here, we tested two methods for LAI estimation from MODIS 250m resolution red and near-infrared (NIR) reflectance time series. The first method involved the inversion of a coupled model of leaf reflectance and transmittance (PROSPECT4), soil reflectance (SOILSPECT) and canopy radiative transfer (4SAIL2). Model parameters other than the LAI were either fixed to measured constant values, or allowed to vary seasonally and/or with stand age according to trends observed in field measurements. The LAI was assumed to vary throughout the rotation following a series of alternately increasing and decreasing sigmoid curves. The parameters of each sigmoid curve that allowed the best fit of simulated canopy reflectance to MODIS red and NIR reflectance data were obtained by minimization techniques. The second method was based on a linear relationship between the LAI and values of the GEneralized Soil Adjusted Vegetation Index (GESAVI), which was calibrated using destructive LAI measurements made at two seasons, on Eucalyptus stands of different ages and productivity levels. The ability of each approach to reproduce field-measured LAI values was assessed, and uncertainty on results and parameter sensitivities were examined. Both methods offered a good fit between measured and estimated LAI (R(2) = 0.80 and R(2) = 0.62 for model inversion and GESAVI-based methods, respectively), but the GESAVI-based method overestimated the LAI at young ages. (C) 2010 Elsevier Inc. All rights reserved.

An assessment of the MODIS collection 5 leaf area index product for a region of mixed coniferous forest

Canopy leaf area index (LAI), defined as the single-sided leaf area per unit ground area, is a quantitative measure of canopy foliar area. LAI is a controlling biophysical property of vegetation function, and quantifying LAI is thus vital for understanding energy, carbon and water fluxes between the land surface and the atmosphere. LAI is routinely available from Earth Observation (EO) instruments such as MODIS. However EO-derived estimates of LAI require validation before they are utilised by the ecosystem modelling community. Previous validation work on the MODIS collection 4 (c4) product suggested considerable error especially in forested biomes, and as a result significant modification of the MODIS LAI algorithm has been made for the most recent collection 5 (c5). As a result of these changes the current MODIS LAI product has not been widely validated. We present a validation of the MODIS c5 LAI product over a 121 km2 area of mixed coniferous forest in Oregon, USA, based on detailed ground measurements which we have upscaled using high resolution EO data. Our analysis suggests that c5 shows a much more realistic temporal LAI dynamic over c4 values for the site we examined. We find improved spatial consistency between the MODIS c5 LAI product and upscaled in situ measurements. However results also suggest that the c5 LAI product underestimates the upper range of upscaled in situ LAI measurements.

Preliminary leaf area index estimates from airborne small footprint full-waveform LiDAR data

This study has compared preliminary estimates of effective leaf area index (LAI) derived from fish-eye lens photographs to those estimated from airborne full-waveform small-footprint LiDAR data for a forest dataset in Australia. The full-waveform data was decomposed and optimized using a trust-region-reflective algorithm to extract denser point clouds. LAI LiDAR estimates were derived in two ways (1) from the probability of discrete pulses reaching the ground without being intercepted (point method) and (2) from raw waveform canopy height profile processing adapted to small-footprint laser altimetry (waveform method) accounting for reflectance ratio between vegetation and ground. The best results, that matched hemispherical photography estimates, were achieved for the waveform method with a study area-adjusted reflectance ratio of 0.4 (RMSE of 0.15 and 0.03 at plot and site level, respectively). The point method generally overestimated, whereas the waveform method with an arbitrary reflectance ratio of 0.5 underestimated the fish-eye lens LAI estimates.

Specific leaf area and leaf area index in developing stands of Fagus sylvatica L. and Picea abies Karst

European beech (Fagus sylvatica L.) and Norway spruce (Picea abies Karst.) are two of the most ecologically and economically important forest tree species in Europe. These two species co-occur in many locations in Europe, leading to direct competition for canopy space. Foliage characteristics of two naturally regenerated pure stands of beech and spruce with fully closed canopies were contrasted to assess the dynamic relationship between foliage adaptability to shading, stand LAI and tree growth. We found that individual leaf size is far more conservative in spruce than in beech. Individual leaf and needle area was larger at the top than at the bottom of the canopy in both species. Inverse relationship was found for specific leaf area (SLA), highest SLA values were found at lowest light availability under the canopy. There was no difference in leaf area index (LAI) between the two stands, however LAI increased from 10.8 to 14.6 m2m-2 between 2009 and 2011. Dominant trees of both species were more efficient in converting foliage mass or area to produce stem biomass, although this relationship changed with age and was species-specific. Overall, we found larger foliage plasticity in beech than in spruce in relation to light conditions, indicating larger capacity to exploit niche openings.

An improved estimate of leaf area index based on the histogram analysis of hemispherical photographs

Leaf area index (LAI) is a key parameter that affects the surface fluxes of energy, mass, and momentum over vegetated lands, but observational measurements are scarce, especially in remote areas with complex canopy structure. In this paper we present an indirect method to calculate the LAI based on the analyses of histograms of hemispherical photographs. The optimal threshold value (OTV), the gray-level required to separate the background (sky) and the foreground (leaves), was analytically calculated using the entropy crossover method (Sahoo, P.K., Slaaf, D.W., Albert, T.A., 1997. Threshold selection using a minimal histogram entropy difference. Optical Engineering 36(7) 1976-1981). The OTV was used to calculate the LAI using the well-known gap fraction method. This methodology was tested in two different ecosystems, including Amazon forest and pasturelands in Brazil. In general, the error between observed and calculated LAI was similar to 6%. The methodology presented is suitable for the calculation of LAI since it is responsive to sky conditions, automatic, easy to implement, faster than commercially available software, and requires less data storage. (C) 2008 Elsevier B.V. All rights reserved.

TANZANIA GRASS STRUCTURE GRAZED BY GOATS MANAGED WITH DIFFERENT RESIDUAL LEAF AREA INDEX UNDER INTERMITTENT STOCKING

The objective of this study was to evaluate the structure of Tanzania grassland grazed by goats managed with different residue leaf area index (RLAI) under intermittent stocking. The experiment was carried out from February to August, 2008. The treatments consisted of three different targets RLAI (0.8, 1.6 and 2.4) and 95% light interception (LI) criterion determined the rest period. Forage samples were collected at average height sampling points and weighed. Subsequently, a smaller sample was removed to separate the morphological components (leaf, stem and dead material) and to determine the structural and productive features. The canopy architecture was evaluated by the method of inclined point quadrat. The pre-grazing height in the paddocks were significantly different among treatments. RLAI influenced dry matter contents of green forage, leaf, stem and total, with the exception of dry matter of dead material, where the lowest values were observed for 0.8 RLAI. Thus, RLAI modifies canopy structure and is sensitive to canopy height changes throughout the year. Pasture regrowth is not compromised by residual leaf area indexes between 0.8 and 2.4, when climatic factors are not limiting.

Seed quality, chlorophyll content index and leaf nitrogen levels in maize inoculated with Azospirillum brasilense

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Calibration of a Species-Specific Spectral Vegetation Index for Leaf Area Index (LAI) Monitoring: Example with MODIS Reflectance Time-Series on Eucalyptus Plantations

The leaf area index (LAI) is a key characteristic of forest ecosystems. Estimations of LAI from satellite images generally rely on spectral vegetation indices (SVIs) or radiative transfer model (RTM) inversions. We have developed a new and precise method suitable for practical application, consisting of building a species-specific SVI that is best-suited to both sensor and vegetation characteristics. Such an SVI requires calibration on a large number of representative vegetation conditions. We developed a two-step approach: (1) estimation of LAI on a subset of satellite data through RTM inversion; and (2) the calibration of a vegetation index on these estimated LAI. We applied this methodology to Eucalyptus plantations which have highly variable LAI in time and space. Previous results showed that an RTM inversion of Moderate Resolution Imaging Spectroradiometer (MODIS) near-infrared and red reflectance allowed good retrieval performance (R-2 = 0.80, RMSE = 0.41), but was computationally difficult. Here, the RTM results were used to calibrate a dedicated vegetation index (called "EucVI") which gave similar LAI retrieval results but in a simpler way. The R-2 of the regression between measured and EucVI-simulated LAI values on a validation dataset was 0.68, and the RMSE was 0.49. The additional use of stand age and day of year in the SVI equation slightly increased the performance of the index (R-2 = 0.77 and RMSE = 0.41). This simple index opens the way to an easily applicable retrieval of Eucalyptus LAI from MODIS data, which could be used in an operational way.