973 resultados para canopy height


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The tendency of trees to grow taller with increasing water availability is common knowledge. Yet a robust, universal relationship between the spatial distribution of water availability and forest canopy height (H) is lacking. Here, we created a global water availability map by calculating an annual budget as the difference between precipitation (P) and potential evapotranspiration (PET) at a 1-km spatial resolution, and in turn correlated it with a global H map of the same resolution. Across forested areas over the globe, Hmean increased with P-PET, roughly: Hmean (m) = 19.3 + 0.077*(P-PET). Maximum forest canopy height also increased gradually from ~ 5 to ~ 50 m, saturating at ~ 45 m for P-PET > 500 mm. Forests were far from their maximum height potential in cold, boreal regions and in disturbed areas. The strong association between forest height and P-PET provides a useful tool when studying future forest dynamics under climate change, and in quantifying anthropogenic forest disturbance.

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Recent empirical studies have shown that multi-angle spectral data can be useful for predicting canopy height, but the physical reason for this correlation was not understood. We follow the concept of canopy spectral invariants, specifically escape probability, to gain insight into the observed correlation. Airborne Multi-Angle Imaging Spectrometer (AirMISR) and airborne Laser Vegetation Imaging Sensor (LVIS) data acquired during a NASA Terrestrial Ecology Program aircraft campaign underlie our analysis. Two multivariate linear regression models were developed to estimate LVIS height measures from 28 AirMISR multi-angle spectral reflectances and from the spectrally invariant escape probability at 7 AirMISR view angles. Both models achieved nearly the same accuracy, suggesting that canopy spectral invariant theory can explain the observed correlation. We hypothesize that the escape probability is sensitive to the aspect ratio (crown diameter to crown height). The multi-angle spectral data alone therefore may not provide enough information to retrieve canopy height globally.

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A Canopy Height Profile (CHP) procedure presented in Harding et al. (2001) for large footprint LiDAR data was tested in a closed canopy environment as a way of extracting vertical foliage profiles from LiDAR raw-waveform. In this study, an adaptation of this method to small-footprint data has been shown, tested and validated in an Australian sparse canopy forest at plot- and site-level. Further, the methodology itself has been enhanced by implementing a dataset-adjusted reflectance ratio calculation according to Armston et al. (2013) in the processing chain, and tested against a fixed ratio of 0.5 estimated for the laser wavelength of 1550nm. As a by-product of the methodology, effective leaf area index (LAIe) estimates were derived and compared to hemispherical photography-derived values. To assess the influence of LiDAR aggregation area size on the estimates in a sparse canopy environment, LiDAR CHPs and LAIes were generated by aggregating waveforms to plot- and site-level footprints (plot/site-aggregated) as well as in 5m grids (grid-processed). LiDAR profiles were then compared to leaf biomass field profiles generated based on field tree measurements. The correlation between field and LiDAR profiles was very high, with a mean R2 of 0.75 at plot-level and 0.86 at site-level for 55 plots and the corresponding 11 sites. Gridding had almost no impact on the correlation between LiDAR and field profiles (only marginally improvement), nor did the dataset-adjusted reflectance ratio. However, gridding and the dataset-adjusted reflectance ratio were found to improve the correlation between raw-waveform LiDAR and hemispherical photography LAIe estimates, yielding the highest correlations of 0.61 at plot-level and of 0.83 at site-level. This proved the validity of the approach and superiority of dataset-adjusted reflectance ratio of Armston et al. (2013) over a fixed ratio of 0.5 for LAIe estimation, as well as showed the adequacy of small-footprint LiDAR data for LAIe estimation in discontinuous canopy forests.

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The aim of this study was to model light interception and distribution in the mixed canopy of Common cocklebur (Xanthium stramarium) with corn. An experiment was conducted in factorial arrangement on the basis of randomized complete blocks design with three replications in Gonabad in 2006-2007 and 2007-2008 seasons. The factors used in this experiment include corn density of 7.5, 8.5 and 9.5 plants per meter of row and density of Common cocklebur of zero, 2, 4, 6 and 8 plants per meter of row. INTERCOM model was used through replacing parabolic function with triangular function of leaf area density. Vertical distribution of the species' leaf area showed that corn has concentrated the most leaf area in layer of 80 to 100 cm while Common cocklebur has concentrated in 35-50 cm of canopy height. Model sensitivity analysis showed that leaf area index, species' height, height where maximum leaf area is seen (hm), and extinction coefficient have influence on light interception rate of any species. In both species, the distribution density of leaf area at the canopy length fit a triangular function, and the height in which maximum leaf area was observed was changed by change in density. There was a correlation between percentage of the radiation absorbed by the weed and percentage of corn seed yield loss (r² = 0.89). Ideal type of corn was determined until the stage of tasseling in competition with weed. This determination indicates that the corn needs more height and leaf area, as well as less extinction coefficient to successfully fight against the weed.

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This paper presents an open-source canopy height profile (CHP) toolkit designed for processing small-footprint full-waveform LiDAR data to obtain the estimates of effective leaf area index (LAIe) and CHPs. The use of the toolkit is presented with a case study of LAIe estimation in discontinuous-canopy fruit plantations. The experiments are carried out in two study areas, namely, orange and almond plantations, with different percentages of canopy cover (48% and 40%, respectively). For comparison, two commonly used discrete-point LAIe estimation methods are also tested. The LiDAR LAIe values are first computed for each of the sites and each method as a whole, providing “apparent” site-level LAIe, which disregards the discontinuity of the plantations’ canopies. Since the toolkit allows for the calculation of the study area LAIe at different spatial scales, between-tree-level clumpingcan be easily accounted for and is then used to illustrate the impact of the discontinuity of canopy cover on LAIe retrieval. The LiDAR LAIe estimates are therefore computed at smaller scales as a mean of LAIe in various grid-cell sizes, providing estimates of “actual” site-level LAIe. Subsequently, the LiDAR LAIe results are compared with theoretical models of “apparent” LAIe versus “actual” LAIe, based on known percent canopy cover in each site. The comparison of those models to LiDAR LAIe derived from the smallest grid-cell sizes against the estimates of LAIe for the whole site has shown that the LAIe estimates obtained from the CHP toolkit provided values that are closest to those of theoretical models.

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The objective of this study was to assess the sward canopy structure of Brachiaria brizantha cv. Marandu pastures maintained in three grazing intensities under continuous stocking system during the rainy season, along with the behavior and performance of grazing beef heifers supplemented with mineral salt or an energy/protein supplement. Three levels of forage allowance were assessed: 2.0, 2.5 and 3.0 kg of forage/kg of live weight, combined with two supplements (ad libitum mineral salt, and an energy/protein supplement at 0.3% of live weight/day, supplied daily). The experiment was designed as a randomized block study with two replications. The supplements did not influence the variables related to the canopy structure. Canopy height was greater at higher forage allowances during the late summer and early fall. Similarly, the stem mass was greater in pastures with higher forage allowances. Animals fed protein supplement spent less time grazing than animals supplemented with mineral salt. Stocking rate was higher in pastures with lower forage allowance levels, which increased the live weight gain per grazing area. Daily weight gain did not vary according to the forage allowance levels. The use of an energy/protein supplement did not affect the stocking rate; however, it increased individual live weight gain and live weight gain per grazing area compared with mineral salt supplementation. The use of energy/protein supplements is an efficient alternative to enhance animal performance and production under grazing systems during the rainy season

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The objective of this study was to evaluate the Brachiaria brizantha cv. Marandu canopy structure maintained at different grazing heights under a continuous stocking rate and with a dietary supplementation strategy for the animals during the rainy season. This study also intended to observe the relationships of these variables with the grazing behaviors of the heifers. The effects of three canopy heights (15, 25 and 35 cm) were evaluated in association with three types of supplements: one mineral and two protein/energy supplements, the first with a high rumen degradable protein and energy and the others with a low ratio. Both the protein/energy supplements were provided at 0.3% of body weight/day. The experimental design was completely randomized, with two replications and repeated measures, and took place during the period from January to April 2008. The supplementation strategies did not affect any variable related to the canopy structure. Total and green herbage masses and the ratio of green/dead material increased with canopy height. The leaf/stem ratio was higher in the lowest canopy height: 15 cm. Changes in the canopy structure caused variations in the grazing behavior of the animals. Animals maintained in the 15-cm-tall pasture grazed for a longer time, increasing the time for each meal, but the number of meals was lower than that of the animals grazing within the 35-cm-tall pasture. The grazing time of animals receiving the energy/protein supplement was lower only in the period of the day during which it was supplied. Canopy structure is affected by sward height, and changes animal behavior. Supplementation does not affect the canopy structure of the pastures with similar heights.

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Understanding how biodiversity spatially distribute over both the short term and long term, and what factors are affecting the distribution, are critical for modeling the spatial pattern of biodiversity as well as for promoting effective conservation planning and practices. This dissertation aims to examine factors that influence short-term and long-term avian distribution from the geographical sciences perspective. The research develops landscape level habitat metrics to characterize forest height heterogeneity and examines their efficacies in modelling avian richness at the continental scale. Two types of novel vegetation-height-structured habitat metrics are created based on second order texture algorithms and the concepts of patch-based habitat metrics. I correlate the height-structured metrics with the richness of different forest guilds, and also examine their efficacies in multivariate richness models. The results suggest that height heterogeneity, beyond canopy height alone, supplements habitat characterization and richness models of two forest bird guilds. The metrics and models derived in this study demonstrate practical examples of utilizing three-dimensional vegetation data for improved characterization of spatial patterns in species richness. The second and the third projects focus on analyzing centroids of avian distributions, and testing hypotheses regarding the direction and speed of these shifts. I first showcase the usefulness of centroids analysis for characterizing the distribution changes of a few case study species. Applying the centroid method on 57 permanent resident bird species, I show that multi-directional distribution shifts occurred in large number of studied species. I also demonstrate, plain birds are not shifting their distribution faster than mountain birds, contrary to the prediction based on climate change velocity hypothesis. By modelling the abundance change rate at regional level, I show that extreme climate events and precipitation measures associate closely with some of the long-term distribution shifts. This dissertation improves our understanding on bird habitat characterization for species richness modelling, and expands our knowledge on how avian populations shifted their ranges in North America responding to changing environments in the past four decades. The results provide an important scientific foundation for more accurate predictive species distribution modeling in future.

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Carbon and nitrogen biogeochemical cycles in savannas are strongly regulated by the seasonal distribution of precipitation and pulses of nutrients released during the wetting of the dry soil and are critical to the dynamics of microorganisms and vegetation. The objective of this study was to investigate the spatial and temporal variability of C and N isotope ratios as indicators of the cycling of these elements in a cerrado sensu stricto area, within a protected area in a State Park in the state of São Paulo, Brazil. The foliar δ13C and δ15N values varied from -33.6 to -24.4 ‰ and -2.5 to 4.5 ‰, respectively. The δ13C values showed a consistent relationship with canopy height, revealing the importance of structure of the canopy over the C isotopic signature of the vegetation. Carbon isotopic variations associated with the length of the dry season indicated the importance of recent fixed C to the integrated isotopic signature of the leaf organic C. The studied Cerrado species showed a depleted foliar δ15N, but a wide range of foliar Nitrogen with no difference among canopy heights. However, seasonal variability was observed, with foliar δ15N values being higher in the transition period between dry and rainy seasons. The variation of the foliar C and N isotope ratios presented here was consistent with highly diverse vegetation with high energy available but low availability of water and N.

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The use of remote sensing is necessary for monitoring forest carbon stocks at large scales. Optical remote sensing, although not the most suitable technique for the direct estimation of stand biomass, offers the advantage of providing large temporal and spatial datasets. In particular, information on canopy structure is encompassed in stand reflectance time series. This study focused on the example of Eucalyptus forest plantations, which have recently attracted much attention as a result of their high expansion rate in many tropical countries. Stand scale time-series of Normalized Difference Vegetation Index (NDVI) were obtained from MODIS satellite data after a procedure involving un-mixing and interpolation, on about 15,000 ha of plantations in southern Brazil. The comparison of the planting date of the current rotation (and therefore the age of the stands) estimated from these time series with real values provided by the company showed that the root mean square error was 35.5 days. Age alone explained more than 82% of stand wood volume variability and 87% of stand dominant height variability. Age variables were combined with other variables derived from the NDVI time series and simple bioclimatic data by means of linear (Stepwise) or nonlinear (Random Forest) regressions. The nonlinear regressions gave r-square values of 0.90 for volume and 0.92 for dominant height, and an accuracy of about 25 m(3)/ha for volume (15% of the volume average value) and about 1.6 m for dominant height (8% of the height average value). The improvement including NDVI and bioclimatic data comes from the fact that the cumulative NDVI since planting date integrates the interannual variability of leaf area index (LAI), light interception by the foliage and growth due for example to variations of seasonal water stress. The accuracy of biomass and height predictions was strongly improved by using the NDVI integrated over the two first years after planting, which are critical for stand establishment. These results open perspectives for cost-effective monitoring of biomass at large scales in intensively-managed plantation forests. (C) 2011 Elsevier Inc. All rights reserved.

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The collection of spatial information to quantify changes to the state and condition of the environment is a fundamental component of conservation or sustainable utilization of tropical and subtropical forests, Age is an important structural attribute of old-growth forests influencing biological diversity in Australia eucalypt forests. Aerial photograph interpretation has traditionally been used for mapping the age and structure of forest stands. However this method is subjective and is not able to accurately capture fine to landscape scale variation necessary for ecological studies. Identification and mapping of fine to landscape scale vegetative structural attributes will allow the compilation of information associated with Montreal Process indicators lb and ld, which seek to determine linkages between age structure and the diversity and abundance of forest fauna populations. This project integrated measurements of structural attributes derived from a canopy-height elevation model with results from a geometrical-optical/spectral mixture analysis model to map forest age structure at a landscape scale. The availability of multiple-scale data allows the transfer of high-resolution attributes to landscape scale monitoring. Multispectral image data were obtained from a DMSV (Digital Multi-Spectral Video) sensor over St Mary's State Forest in Southeast Queensland, Australia. Local scene variance levels for different forest tapes calculated from the DMSV data were used to optimize the tree density and canopy size output in a geometric-optical model applied to a Landsat Thematic Mapper (TU) data set. Airborne laser scanner data obtained over the project area were used to calibrate a digital filter to extract tree heights from a digital elevation model that was derived from scanned colour stereopairs. The modelled estimates of tree height, crown size, and tree density were used to produce a decision-tree classification of forest successional stage at a landscape scale. The results obtained (72% accuracy), were limited in validation, but demonstrate potential for using the multi-scale methodology to provide spatial information for forestry policy objectives (ie., monitoring forest age structure).

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The objective of this study was to determine the effects of weather, predators and parasitoids, canopy height and plant age, leaf chemical composition, levels of leaf N and K and leaf trichomes on the intensity of Bemisia tabaci attack on Solanum melongena. A higher density of nymph and whitefly adults was recorded at the base and medium of the plant compared to the apex. A higher number of eggs was observed on the medium part than on the apical and base part of the plants dossel. An increase in the density of whitefly is associated with an increase in temperature.

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The control of whitefly Bemisia tabaci (Gennadius) biotype B (Hemiptera: Aleyrodidae) on okra (Abelmoschus esculentus L.) consists primarily in the use of insecticides, due to the lack of information on other mortality factors. The objective of this study was to evaluate the spatial and temporal population dynamics of the whitefly B. tabaci biotype B on two successive A. esculentus var. "Santa Cruz" plantations. Leaf chemical composition, leaf nitrogen and potassium contents, trichome density, canopy height, plant age, predators, parasitoids, total rainfall and median temperature were evaluated and their relationships with whitefly on okra were determined. Monthly number estimates of whitefly adults, nymphs (visual inspection) and eggs (magnifying lens) occurred on bottom, middle and apical parts of 30 plants/plantation (one leaf/plant). Plants senescence and natural enemies, mainly Encarsia sp., Chrysoperla spp. and Coccinellidae, were some of the factors that most contributed to whitefly reduction. The second okra plantation, 50 m apart from the first, was strongly attacked by whitefly, probably because of the insect migration from the first to the second plantation. No significant effects of the plant canopy on whitefly eggs and adults distribution were found. A higher number of whitefly nymphs was found on the medium part than on the bottom part.

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The objective of this study was to evaluate the meteorological variables, water deficiency, growth, and agro-industrial yield of sugarcane varieties: RB72454, RB863129, RB867515, RB92579, RB93509, RB931003, RB951541, and RB971755, in rainfed crop in two harvests in the Rio Largo-AL region. The meteorological variables were obtained in an automatic station and water balance was done by Thornthwaite & Mather method. During the study period, the air temperature ranged from 16.6 to 35.9 ºC. In the first production cycle rained 1,806 mm and the crop evapotranspiration was 1,775 mm. In the second cycle, the rainfall totaled 1,632 mm and the crop evapotranspiration was 1,290 mm. The average water excess of two production cycles was 689 mm and the water deficit totaled 665 mm. The average agricultural productivity in the plant was 86.8 t ha-1, in the first ratoon was 75.2 t ha-1 and the agro-industrial yield average was 12.9 and 10.9 tons of sugar per hectare in the plant and first ratoon, respectively. The air temperature was not limiting to the growth of sugarcane and the rainfall was higher than the crop evapotranspiration, but due to poor distribution of the rains there was water deficit. The most productive varieties were RB93509, RB92579, and RB863129.