Showing papers on "Leaf area index published in 2005"

A parameterization of leaf phenology for the terrestrial ecosystem component of climate models

Abstract: Leaf phenology remains one of the most difficult processes to parameterize in terrestrial ecosystem models because our understanding of the physical processes that initiate leaf onset and senescence is incomplete. While progress has been made at the molecular level, for example by identifying genes that are associated with senescence and flowering for selected plant species, a picture of the processes controlling leaf phenology is only beginning to emerge. A variety of empirical formulations have been used with varying degrees of success in terrestrial ecosystem models for both extratropical and tropical biomes. For instance, the use of growing degree-days (GDDs) to initiate leaf onset has received considerable recognition and this approach is used in a number of models. There are, however, limitations when using GDDs and other empirically based formulations in global transient climate change simulations. The phenology scheme developed for the Canadian Terrestrial Ecosystem Model (CTEM), designed for inclusion in the Canadian Centre for Climate Modelling and Analysis coupled general circulation model, is described. The representation of leaf phenology is general enough to be applied over the globe and sufficiently robust for use in transient climate change simulations. Leaf phenology is functionally related to the (possibly changing) climate state and to atmospheric composition rather than to geographical boundaries or controls implicitly based on current climate. In this approach, phenology is controlled by environmental conditions as they affect the carbon balance. A carbon-gain-based scheme initiates leaf onset when it is beneficial for the plant, in carbon terms, to produce new leaves. Leaf offset is initiated by unfavourable environmental conditions that incur carbon losses and these include shorter day length, cooler temperatures, and dry soil moisture conditions. The comparison of simulated leaf onset and offset times with observation-based estimates for temperate and boreal deciduous, tropical evergreen, and tropical deciduous plant functional types at selected locations indicates that the phenology scheme performs satisfactorily. Model simulated leaf area index and stem and root biomass are also compared with observational estimates to illustrate the performance of CTEM.

Effects of stand age and tree species on canopy transpiration and average stomatal conductance of boreal forests

Abstract: We quantified the effect of stand age and tree species composition on canopy transpiration ( E C ) by analysing transpiration per unit leaf area ( E L ) and canopy stomatal conductance ( G S ) for boreal trees comprising a five stand wildfire chronosequence. A total of 196 sap flux sensors were used on 90 trees consisting of Betula papyrifera Marsh (paper birch; present in the youngest stand), Populus tremuloides Michx (quaking aspen), Pinus banksiana Lamb. (jack pine), and Picea mariana (Mill.) (black spruce). While fine roots were positively correlated with stand E C ; leaf area index, basal area, and sapwood area were not. Stands less than 70 years old were dominated by Populus tremuloides and Pinus banksiana and stands greater than 70 years old were composed almost entirely of Picea mariana. As Populus tremuloides and Pinus banksiana increased in size and age, they displayed an increasing sapwood to leaf area ratio ( A S : A L ), a constant minimum leaf water potential (Y L ), and a constant proportionality between G S at low vapour pressure deficit ( DjG Sref ) and the sensitivity of G S to D (‐d ). In contrast, A S : A L , minimum Y L , and the proportionally between ‐d and G Sref decreased with height and age in Picea mariana . A G S model that included the effects of D , A S : A L , tree height, and for Picea mariana an increasing soil to leaf water potential gradient with stand age, was able to capture the effects of contrasting hydraulic properties of Picea mariana , Populus tremuloides and Pinus banksiana during stand development after wildfire.

Micrometeorological and canopy controls of fire susceptibility in a forested amazon landscape

Abstract: Fire is playing an increasing role in shaping the structure, composition, and function of vast areas of moist tropical forest. Within the Brazilian Amazon, cattle ranching and swidden agriculture provide abundant sources of ignition to forests that become sus- ceptible to fire through selective logging, severe drought and, perhaps, fragmentation. Our understanding of the biophysical factors that control fire spread through Amazon forests remains largely anecdotal, however, restricting our ability to model the Amazon fire regime, and to simulate the effects of trends in climate and land-use activities on future regimes. We used experimental fires together with measurements of micrometeorology (rainfall, vapor pressure deficit (VPD), wind velocity), canopy attributes (leaf area index (LAI), canopy height), and fuel characteristics (litter moisture content (LMC) and mass) to identify the variables most closely associated with fire susceptibility in the east-central Amazon. Fire spread rates (FSR, m/min) were measured in three common forest types: an 8-yr-old regrowth forest, a recently logged/burned forest, and a mature forest. One hundred fires were set in each study area during the last two months of the 2002 dry season. VPD, recent precipitation history, wind velocity, and LAI explained 57% of the variability in FSR. In combination, LAI, canopy height, and recent precipitation history accounted for ;65% of the variability in VPD, the single most important predictor of FSR, and approximately half of the total observed variability in FSR. Using logistic regression we were able to predict whether a fire would spread or die 72% of the time based on LAI, canopy height, and recent precipitation history. An approximate threshold in fire susceptibility was associated with a LMC of ;23%, somewhat higher than previously reported (15%). Fire susceptibility was highest under low, sparse canopies, which permitted greater coupling of relatively hot, dry air above the canopy with the otherwise cool, moist air near the forest floor. Fire susceptibility increased over time after rain events as the forest floor gradually dried. The most important determinants of fire susceptibility can be captured in ecosystem and climate models and through remotely sensed estimates of canopy structure, canopy water content, and microclimatic variables.

A phytolith index as a proxy of tree cover density in tropical areas: Calibration with Leaf Area Index along a forest-savanna transect in southeastern Cameroon

Abstract: The aim of the study is to calibrate the phytolith index of tree cover density, D/P (the ratio of ligneous dicotyledons phytoliths (D) over Poaceae phytoliths (P)) with Leaf Area Index (LAI) measurements LAI is the vertically integrated surface of leaves per unit of ground area (m(2) leaves/m(2) ground) Modern soil samples from southeastern Cameroon, collected along a continuous forest-savarina transect, have been analyzed for phytoliths Phytolith assemblages and D/P index clearly record the physiognomy of the forest and savanna communities and of the transition between both of them A highly significant relationship was obtained between D/P and LAI The relationship between phytolith data and the vegetation transect is also discussed and compared with existing palynological results obtained along the same transect (c) 2004 Elsevier BV All rights reserved

Analysis and optimization of the MODIS leaf area index algorithm retrievals over broadleaf forests

Abstract: Broadleaf forest is a major type of Earth's land cover with the highest observable vegetation density. Retrievals of biophysical parameters, such as leaf area index (LAI), of broadleaf forests at global scale constitute a major challenge to modern remote sensing techniques in view of low sensitivity (saturation) of surface reflectances to such parameters over dense vegetation. The goal of the performed research is to demonstrate physical principles of LAI retrievals over broadleaf forests with the Moderate Resolution Imaging Spectroradiometer (MODIS) LAI algorithm and to establish a basis for algorithm refinement. To sample natural variability in biophysical parameters of broadleaf forests, we selected MODIS data subsets covering deciduous broadleaf forests of the eastern part of North America and evergreen broadleaf forests of Amazonia. The analysis of an annual course of the Terra MODIS Collection 4 LAI product over broadleaf forests indicated a low portion of best quality main radiative transfer-based algorithm retrievals and dominance of low-reliable backup algorithm retrievals during the growing season. We found that this retrieval anomaly was due to an inconsistency between simulated and MODIS surface reflectances. LAI retrievals over dense vegetation are mostly performed over a compact location in the spectral space of saturated surface reflectances, which need to be accurately modeled. New simulations were performed with the stochastic radiative transfer model, which poses high numerical accuracy at the condition of saturation. Separate sets of parameters of the LAI algorithm were generated for deciduous and evergreen broadleaf forests to account for the differences in the corresponding surface reflectance properties. The optimized algorithm closely captures physics of seasonal variations in surface reflectances and delivers a majority of LAI retrievals during a phenological cycle, consistent with field measurements. The analysis of the optimized retrievals indicates that the precision of MODIS surface reflectances, the natural variability, and mixture of species set a limit to improvements of the accuracy of LAI retrievals over broadleaf forests.

Crop growth and yield

Abstract: The processes that determine tomato crop growth and yield are considered in detail, with emphasis on the influence of environmental factors such as light, CO2, temperature, humidity and salinity. The main topics are as follows: Biomass production (leaf area and light interception, leaf and crop photosynthesis); Crop and fruit growth; Biomass partitioning (source strength, transport path, sink strength, shoot:root ratio, and influence of growing conditions and cultural practices); Fruit dry matter content; and Crop growth models (describing the TOMSIM model for tomato growth, development and yield, and its use in 2 case studies on optimum fruit number/truss and mitigation of salinity effects on yield by improving LAI).

Time‐series validation of MODIS land biophysical products in a Kalahari woodland, Africa

Abstract: Monthly measurements of leaf area index (LAI) and the fraction of absorbed photosynthetically active radiation (f APAR) taken at approximately monthly intervals were collected along three 750 m transects in a Kalahari woodland near Mongu in western Zambia. These data were compared with MODIS NDVI (MOD13, Collection 3) and MODIS LAI and f APAR products (MOD15, Collection 3) over a 2 year period (2000–2002). MODIS and ground‐measured LAI values corresponded well, while there was a significant bias between MODIS and ground‐measured f APAR even though both MODIS variables are produced from the same algorithm. Solar zenith angle effects, differences between intercepted and absorbed photosynthetically active radiation, and differences in measurement of f APAR (photon counts versus energy) were examined and rejected as explanations for the discrepancies between MODIS and ground‐measured f APAR. Canopy reflectance model simulations produced different values of f APAR with the same LAI when canopy cover was varied...

Form-function analysis of the effect of canopy morphology on leaf self-shading in the seagrass Thalassia testudinum

Abstract: The variation in seagrass morphology and the magnitude of leaf self-shading within the canopy of Thalassia testudinum, were compared among nine sites in a fringing reef lagoon. We found a significant variation in the growth-form of T. testudinum reflected in a 5.4-fold variation in the attenuation coefficient (Kd) within the canopy. The largest morphological variation was observed in shoot density. Leaf biomass, leaf area index (LAI), and shoot density were positively associated with canopy-Kd and with the percentage of surface irradiance received by the top of the seagrass canopy (% Es). These results provide an explanation for the consistent pattern of depth reduction in seagrass leaf biomass and shoot density reported in the literature. Shoot density and shoot size are two descriptors of the growth-form of T. testudinum related to its clonal life-form. Shoot size was not significantly correlated with canopy-Kd, nevertheless, it showed a significant effect on the slope of the relationship between shoot density and canopy-Kd. According to this model, shoot size also contributes to light attenuation within the seagrass canopy by increasing the effect of shoot density. This form-function analysis suggests that light may have a relevant role in the regulation of the optimal plant balance between horizontal (variation in shoot density) and vertical (variation in shoot size) growth of seagrasses. Other environmental factors and interactions also need to be examined to fully understand the mechanistic bases of the morphological responses of seagrasses to the environment.

Parameterization of Canopy Structure and Leaf-Level Gas Exchange for an Eastern Amazonian Tropical Rain Forest (Tapajós National Forest, Pará, Brazil)

Abstract: Carbon flux of Amazonian primary forest vegetation has been shown to vary both spatially and temporally. Process-based models are adequate tools to understand the basis of such variation and can also provide projections to future scenarios. The parameterization of such process-based models requires information from the vegetation in question simply because ecosystem-level gas exchange is a direct result of the tightly coupled interaction between local vegetation and regional climate. In this study, data are presented concerning canopy structure [leaf area index (LAI), and the ratio of leaf dry mass to leaf area (LMA)], leaf chemistry [area-based foliar nitrogen content (Narea) and carbon isotope composition (δ13C)], and photosynthetic gas exchange [maximum carbon assimilation rates (Amax), stomatal conductance (gs@Amax), maximum carboxylation capacity (Vcmax), and respiration rates (Rd)] versus relative height from an extensive survey of primary forest vegetation of the Santarem region (eastern A...

Seasonal leaf dynamics across a tree density gradient in a Brazilian savanna.

Abstract: Interactions between trees and grasses that influence leaf area index (LAI) have important consequences for savanna ecosystem processes through their controls on water, carbon, and energy fluxes as well as fire regimes. We measured LAI, of the groundlayer (herbaceous and woody plants 1-m tall), in the Brazilian cerrado over a range of tree densities from open shrub savanna to closed woodland through the annual cycle. During the dry season, soil water potential was strongly and positively correlated with grass LAI, and less strongly with tree and shrub LAI. By the end of the dry season, LAI of grasses, groundlayer dicots and trees declined to 28, 60, and 68% of mean wet-season values, respectively. We compared the data to remotely sensed vegetation indices, finding that field measurements were more strongly correlated to the enhanced vegetation index (EVI, r 2=0.71) than to the normalized difference vegetation index (NDVI, r 2=0.49). Although the latter has been more widely used in quantifying leaf dynamics of tropical savannas, EVI appears better suited for this purpose. Our ground-based measurements demonstrate that groundlayer LAI declines with increasing tree density across sites, with savanna grasses being excluded at a tree LAI of approximately 3.3. LAI averaged 4.2 in nearby gallery (riparian) forest, so savanna grasses were absent, thereby greatly reducing fire risk and permitting survival of fire-sensitive forest tree species. Although edaphic conditions may partly explain the larger tree LAI of forests, relative to savanna, biological differences between savanna and forest tree species play an important role. Overall, forest tree species had 48% greater LAI than congeneric savanna trees under similar growing conditions. Savanna and forest species play distinct roles in the structure and dynamics of savanna–forest boundaries, contributing to the differences in fire regimes, microclimate, and nutrient cycling between savanna and forest ecosystems.

Calibration and assessment of seasonal changes in leaf area index of a tropical dry forest in different stages of succession

Abstract: A simple measure of the amount of foliage present in a forest is leaf area index (LAI; the amount of foliage per unit ground surface area), which can be determined by optical estimation (gap fraction method) with an instrument such as the Li-Cor LAI-2000 Plant Canopy Analyzer. However, optical instruments such as the LAI-2000 cannot directly differentiate between foliage and woody components of the canopy. Studies investigating LAI and its calibration (extracting foliar LAI from optical estimates) in tropical forests are rare. We calibrated optical estimates of LAI from the LAI-2000 with leaf litter data for a tropical dry forest. We also developed a robust method for determining LAI from leaf litter data in a tropical dry forest environment. We found that, depending on the successional stage of the canopy and the season, the LAI-2000 may underestimate LAI by 17% to over 40%. In the dry season, the instrument overestimated LAI by the contribution of the woody area index. Examination of the seasonal variation in LAI for three successional stages in a tropical dry forest indicated differences in timing of leaf fall according to successional stage and functional group (i.e., lianas and trees). We conclude that when calculating LAI from optical estimates, it is necessary to account for the differences between values obtained from optical and semi-direct techniques. In addition, to calculate LAI from litter collected in traps, specific leaf area must be calculated for each species rather than from a mean value for multiple species.

Large-Area Maize Yield Forecasting Using Leaf Area Index Based Yield Model

Abstract: Large-area yield prediction early in the growing season is important in agricultural decision-making. This study derived maize (Zea mays L.) leaf area index (LAI) estimates from spectral data and used these estimates witha simple LAI-based yield model to forecast yield under irrigated conditions in large areas in Sinaloa, Mexico. Leaf area index was derived from satellite data with the use of an equation developed with LAI measurements from farmers' fields during the 2001-2002 autumn-winter growing season. These measurements were correlated with the normalized difference vegetation index values from 2002 Landsat ETM+ (enhanced thematic mapper) data. The equation was then tested with 2003 Landsat imagery data. A yield model was validated with maximum LAI and yield data measured in farmers' fields in northern and central Sinaloa during three consecutive autumn-winter growing seasons (1999-2000, 2000-2001, and 2001-2002). The yield model was further validated with 2002-2003 autumn-winter ground LAI (gLAI) and satellite-derived LAI (sLAI) data from 71 farmers' fields in northern and central Sinaloa. Grain yield was predicted with a mean error of -9.2% with maximum gLAI and -11.2% with sLAI. Results indicate that the yield model using LAI can forecast yield in large areas in Sinaloa in the middle of the growing season with a mean absolute error of -1.2 Mg ha - 1 . The use of sLAI in place of ground measurements increased the mean absolute error by 0.3 Mg ha - 1 . Nevertheless, the use of sLAI would eliminate laborious LAI measurements for large-area yield prediction in Sinaloa.

Forest categorization according to dry‐canopy evaporation rates in the growing season: comparison of the Priestley–Taylor coefficient values from various observation sites

Abstract: Summarizing observed dry-canopy evaporation (hereafter, evaporation) data from earlier papers, we developed a scheme for forest categorization according to evaporation rates in the growing season. Evaporation rates were represented by the Priestley–Taylor coefficient α calculated for daytime. We examined relationships between forest properties (e.g. climatic regions, leaf types) and α values. We obtained α data for 67 forest sites from earlier papers. Based on these data, we found (i) a clear difference in α values between broad-leaved and coniferous forests, (ii) a greater variation in α values between individual coniferous forests than between individual broad-leaved forests, and (iii) a clear relationship between canopy height and α values for coniferous forests. These three results were supported by surface conductance data summarized from earlier papers. We concluded that forests should be primarily classified into broad-leaved and coniferous forests, and that coniferous forests should be further classified according to canopy height. This classification scheme is applicable only to forests with projected leaf area index (LAI) ≥3·0. Regardless of this LAI limitation, this classification will be useful because many forests satisfy this LAI limitation. This paper shows valuable results in the following two respects. First, this paper explicitly shows the difference in evaporation rates between broad-leaved and coniferous forests. Although this difference would have been implicitly recognized, this difference has not been shown based on adequate amounts of observed data. Second, it is shown that classifying coniferous forests according to canopy height is as important as classifying forests according to leaf type (broad-leaved or coniferous). Although studies have recognized the effect of canopy height on evaporation rates, the significant effect of canopy height on evaporation rates, compared with the effects of other factors on evaporation rates, has not previously been shown. Copyright © 2005 John Wiley & Sons, Ltd.