44 resultados para broadleaf


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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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There are strong uncertainties regarding LAI dynamics in forest ecosystems in response to climate change. While empirical growth & yield models (G&YMs) provide good estimations of tree growth at the stand level on a yearly to decennial scale, process-based models (PBMs) use LAI dynamics as a key variable for enabling the accurate prediction of tree growth over short time scales. Bridging the gap between PBMs and G&YMs could improve the prediction of forest growth and, therefore, carbon, water and nutrient fluxes by combining modeling approaches at the stand level.Our study aimed to estimate monthly changes of leaf area in response to climate variations from sparse measurements of foliage area and biomass. A leaf population probabilistic model (SLCD) was designed to simulate foliage renewal. The leaf population was distributed in monthly cohorts, and the total population size was limited depending on forest age and productivity. Foliage dynamics were driven by a foliation function and the probabilities ruling leaf aging or fall. Their formulation depends on the forest environment.The model was applied to three tree species growing under contrasting climates and soil types. In tropical Brazilian evergreen broadleaf eucalypt plantations, the phenology was described using 8 parameters. A multi-objective evolutionary algorithm method (MOEA) was used to fit the model parameters on litterfall and LAI data over an entire stand rotation. Field measurements from a second eucalypt stand were used to validate the model. Seasonal LAI changes were accurately rendered for both sites (R-2 = 0.898 adjustment, R-2 = 0.698 validation). Litterfall production was correctly simulated (R-2 = 0.562, R-2 = 0.4018 validation) and may be improved by using additional validation data in future work. In two French temperate deciduous forests (beech and oak), we adapted phenological sub-modules of the CASTANEA model to simulate canopy dynamics, and SLCD was validated using LAI measurements. The phenological patterns were simulated with good accuracy in the two cases studied. However, IA/max was not accurately simulated in the beech forest, and further improvement is required.Our probabilistic approach is expected to contribute to improving predictions of LAI dynamics. The model formalism is general and suitable to broadleaf forests for a large range of ecological conditions. (C) 2014 Elsevier B.V. All rights reserved.

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We begin the 2001 Master Conservationist program with honorees in production agriculture from District A which includes the Panhandle of Nebraska. I would like to ask Leon and Cheryl Burkhart-Kriesel (Kresel) of Gurley who are unable to be present. They operated the family farm in partnership with Fred and Viola Kriesel until 1984 when Leon and Cheryl become sole owners/operators. The Kriesels produce certified wheat, millet, oats, and barley seed on 3200 dryland acres that are owned, rented, or contracted. Since 1984, 45,000 feet of terraces have been installed. Their holistic conservation plan also includes over 57,000 feet of windbreaks of mixed evergreen and broadleaf trees and shrubs. This mixture of plant species is unique in the Panhandle. They built an earthen dam with 11 acre-feet of permanent storage and 70.5 acre-feet of detention storage. Results include reduced soil erosion by wind and water, and increased productivity and wildlife populations. Local and international groups tour the farm. Congratulations to the Kriesels.

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Rainfall, throughfall and stemflow were monitored on an event basis in an undisturbed open tropical rainforest with a large number of palm trees located in the southwestern Amazon basin of Brazil. Stemflow samples were collected from 24 trees with a diameter at breast height (DBH) > 5 cm, as well as eight young and four full-grown babassu palms (Attalea speciosa Mart.) for 5 weeks during the peak of the wet season. We calculated rainfall, throughfall and stemflow concentrations and fluxes of Na+, K+, Ca2+, Mg2+,, Cl-, SO42-, NO3- and H+ and stemflow volume-weighted mean concentrations and fluxes for three size classes of broadleaf trees and three size classes of palms. The concentrations of most solutes were higher in stemflow than in rainfall and increased with increasing tree and palm size. Concentration enrichments from rainfall to stemflow and throughfall were particularly high (81-fold) for NO3-. Stemflow fluxes of NO3- and H+ exceeded throughfall fluxes but stemflow fluxes of other solutes were less than throughfall fluxes. Stemflow solute fluxes to the forest soil were dominated by fluxes on babassu palms, which represented only 4% of total stem number and 10% of total basal area. For NO3-, stemflow contributed 51% of the total mass of nitrogen delivered to the forest floor (stemflow + throughfall) and represented more than a 2000-fold increase in NO3- flux compared what would have been delivered by rainfall alone on the equivalent area. Because these highly localized fluxes of both water and NO3- persist in time and space, they have the potential to affect patterns of soil moisture, microbial populations and other features of soil biogeochemistry conducive to the creation of hotspots for nitrogen leaching and denitrification, which could amount to an important fraction of total ecosystem fluxes. Because these hotspots occur over very small areas, they have likely gone undetected in previous studies and need to be considered as an important feature of the biogeochemistry of palm-rich tropical forest. (C) 2011 Elsevier B.V. All rights reserved.

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The global population of the Neotropical migrant Golden-winged Warbler (Vermivora chrysoptera) has declined steadily over the past fifty years. While factors influencing this decline have been well researched on the breeding grounds, little is known about the distribution and habitat requirements of this warbler on its stationary non-breeding range. Recent efforts to quantify the non-breeding habitat requirements of this warbler have focused on Colombia and Costa Rica, though the species ranges as far north as the Yucatan Peninsula, Mexico. To address the gap in knowledge from the northern portion of the non-breeding range, I conducted 80 serial point-count surveys targeting Goldenwinged Warblers at eight field sites in Honduras, Central America. I found that Goldenwinged Warblers occupy a greater variety of habitats than previously recognized, including pine-oak forest and semi-deciduous broadleaf forest. I also documented habitat associations that have not been observed in other parts of the non-breeding range with respect to elevation, rainfall, and spatial segregation by sex. These results demonstrate the need to consider the entire non-breeding range in conservation planning, as Goldenwinged Warbler habitat associations appear to vary regionally.

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Tropical trees have been shown to be more susceptible to warming compared to temperate species, and have shown growth and photosynthetic declines at elevated temperatures as little as 3oC above ambient. However, regional and global vegetation models lack the data needed to accurately represent physiological response to increased temperatures in tropical forests. We compared the instantaneous photosynthetic responses to elevated temperatures of four mature tropical rainforest tree species in Puerto Rico and the temperate broadleaf species sugar maple (Acer saccharum) in Michigan. Contrary to expectations, leaves in the upper canopy of both temperate and tropical forests had temperature optima that are already exceeded by mean daily leaf temperatures. This indicates that tropical and temperate forests are already seeing photosynthesis decline at mid-day temperature. This decline may worsen as air temperatures rise with climate change if trees are unable to acclimate, increasing the likelihood that forests may shift from carbon sinks to sources. A secondary study was conducted on experimentally warmed sugar maple seedlings to determine if photosynthesis had been able to acclimate to +5oC air temperature over four years. Species abundance models had predicted a decline of sugar maple within the Upper Peninsula of Michigan over the next 100 years, due to elevated temperature and altered precipitation. Instantaneous photosynthetic temperature response curves on both control and heated seedlings showed that the differences between treatments were not statistically significant, though there was a 16% increase in temperature optima and a 3% increase in maximum rates of photosynthesis in warmed plots. Though evidence of acclimation was not significant, the seedlings did not fare poorly as the models suggest.

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The Earth’s carbon and hydrologic cycles are intimately coupled by gas exchange through plant stomata1, 2, 3. However, uncertainties in the magnitude4, 5, 6 and consequences7, 8 of the physiological responses9, 10 of plants to elevated CO2 in natural environments hinders modelling of terrestrial water cycling and carbon storage11. Here we use annually resolved long-term δ13C tree-ring measurements across a European forest network to reconstruct the physiologically driven response of intercellular CO2 (Ci) caused by atmospheric CO2 (Ca) trends. When removing meteorological signals from the δ13C measurements, we find that trees across Europe regulated gas exchange so that for one ppmv atmospheric CO2 increase, Ci increased by ~0.76 ppmv, most consistent with moderate control towards a constant Ci/Ca ratio. This response corresponds to twentieth-century intrinsic water-use efficiency (iWUE) increases of 14 ± 10 and 22 ± 6% at broadleaf and coniferous sites, respectively. An ensemble of process-based global vegetation models shows similar CO2 effects on iWUE trends. Yet, when operating these models with climate drivers reintroduced, despite decreased stomatal opening, 5% increases in European forest transpiration are calculated over the twentieth century. This counterintuitive result arises from lengthened growing seasons, enhanced evaporative demand in a warming climate, and increased leaf area, which together oppose effects of CO2-induced stomatal closure. Our study questions changes to the hydrological cycle, such as reductions in transpiration and air humidity, hypothesized to result from plant responses to anthropogenic emissions.

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Disponer de información precisa y actualizada de inventario forestal es una pieza clave para mejorar la gestión forestal sostenible y para proponer y evaluar políticas de conservación de bosques que permitan la reducción de emisiones de carbono debidas a la deforestación y degradación forestal (REDD). En este sentido, la tecnología LiDAR ha demostrado ser una herramienta perfecta para caracterizar y estimar de forma continua y en áreas extensas la estructura del bosque y las principales variables de inventario forestal. Variables como la biomasa, el número de pies, el volumen de madera, la altura dominante, el diámetro o la altura media son estimadas con una calidad comparable a los inventarios tradicionales de campo. La presente tesis se centra en analizar la aplicación de los denominados métodos de masa de inventario forestal con datos LIDAR bajo diferentes condiciones y características de masa forestal (bosque templados puros y mixtos) y utilizando diferentes bases de datos LiDAR (información proveniente de vuelo nacionales e información capturada de forma específica). Como consecuencia de lo anterior, se profundiza en la generación de inventarios forestales continuos con LiDAR en grandes áreas. Los métodos de masa se basan en la búsqueda de relaciones estadísticas entre variables predictoras derivadas de la nube de puntos LiDAR y las variables de inventario forestal medidas en campo con el objeto de generar una cartografía continua de inventario forestal. El rápido desarrollo de esta tecnología en los últimos años ha llevado a muchos países a implantar programas nacionales de captura de información LiDAR aerotransportada. Estos vuelos nacionales no están pensados ni diseñados para fines forestales por lo que es necesaria la evaluación de la validez de esta información LiDAR para la descripción de la estructura del bosque y la medición de variables forestales. Esta información podría suponer una drástica reducción de costes en la generación de información continua de alta resolución de inventario forestal. En el capítulo 2 se evalúa la estimación de variables forestales a partir de la información LiDAR capturada en el marco del Plan Nacional de Ortofotografía Aérea (PNOA-LiDAR) en España. Para ello se compara un vuelo específico diseñado para inventario forestal con la información de la misma zona capturada dentro del PNOA-LiDAR. El caso de estudio muestra cómo el ángulo de escaneo, la pendiente y orientación del terreno afectan de forma estadísticamente significativa, aunque con pequeñas diferencias, a la estimación de biomasa y variables de estructura forestal derivadas del LiDAR. La cobertura de copas resultó más afectada por estos factores que los percentiles de alturas. Considerando toda la zona de estudio, la estimación de la biomasa con ambas bases de datos no presentó diferencias estadísticamente significativas. Las simulaciones realizadas muestran que las diferencias medias en la estimación de biomasa entre un vuelo específico y el vuelo nacional podrán superar el 4% en áreas abruptas, con ángulos de escaneo altos y cuando la pendiente de la ladera no esté orientada hacia la línea de escaneo. En el capítulo 3 se desarrolla un estudio en masas mixtas y puras de pino silvestre y haya, con un enfoque multi-fuente empleando toda la información disponible (vuelos LiDAR nacionales de baja densidad de puntos, imágenes satelitales Landsat y parcelas permanentes del inventario forestal nacional español). Se concluye que este enfoque multi-fuente es adecuado para realizar inventarios forestales continuos de alta resolución en grandes superficies. Los errores obtenidos en la fase de ajuste y de validación de los modelos de área basimétrica y volumen son similares a los registrados por otros autores (usando un vuelo específico y parcelas de campo específicas). Se observan errores mayores en la variable número de pies que los encontrados en la literatura, que pueden ser explicados por la influencia de la metodología de parcelas de radio variable en esta variable. En los capítulos 4 y 5 se evalúan los métodos de masa para estimar biomasa y densidad de carbono en bosques tropicales. Para ello se trabaja con datos del Parque Nacional Volcán Poás (Costa Rica) en dos situaciones diferentes: i) se dispone de una cobertura completa LiDAR del área de estudio (capitulo 4) y ii) la cobertura LiDAR completa no es técnica o económicamente posible y se combina una cobertura incompleta de LiDAR con imágenes Landsat e información auxiliar para la estimación de biomasa y carbono (capitulo 5). En el capítulo 4 se valida un modelo LiDAR general de estimación de biomasa aérea en bosques tropicales y se compara con los resultados obtenidos con un modelo ajustado de forma específica para el área de estudio. Ambos modelos están basados en la variable altura media de copas (TCH por sus siglas en inglés) derivada del modelo digital LiDAR de altura de la vegetación. Los resultados en el área de estudio muestran que el modelo general es una alternativa fiable al ajuste de modelos específicos y que la biomasa aérea puede ser estimada en una nueva zona midiendo en campo únicamente la variable área basimétrica (BA). Para mejorar la aplicación de esta metodología es necesario definir en futuros trabajos procedimientos adecuados de medición de la variable área basimétrica en campo (localización, tamaño y forma de las parcelas de campo). La relación entre la altura media de copas del LiDAR y el área basimétrica (Coeficiente de Stock) obtenida en el área de estudio varía localmente. Por tanto es necesario contar con más información de campo para caracterizar la variabilidad del Coeficiente de Stock entre zonas de vida y si estrategias como la estratificación pueden reducir los errores en la estimación de biomasa y carbono en bosques tropicales. En el capítulo 5 se concluye que la combinación de una muestra sistemática de información LiDAR con una cobertura completa de imagen satelital de moderada resolución (e información auxiliar) es una alternativa efectiva para la realización de inventarios continuos en bosques tropicales. Esta metodología permite estimar altura de la vegetación, biomasa y carbono en grandes zonas donde la captura de una cobertura completa de LiDAR y la realización de un gran volumen de trabajo de campo es económica o/y técnicamente inviable. Las alternativas examinadas para la predicción de biomasa a partir de imágenes Landsat muestran una ligera disminución del coeficiente de determinación y un pequeño aumento del RMSE cuando la cobertura de LiDAR es reducida de forma considerable. Los resultados indican que la altura de la vegetación, la biomasa y la densidad de carbono pueden ser estimadas en bosques tropicales de forma adecuada usando coberturas de LIDAR bajas (entre el 5% y el 20% del área de estudio). ABSTRACT The availability of accurate and updated forest data is essential for improving sustainable forest management, promoting forest conservation policies and reducing carbon emissions from deforestation and forest degradation (REDD). In this sense, LiDAR technology proves to be a clear-cut tool for characterizing forest structure in large areas and assessing main forest-stand variables. Forest variables such as biomass, stem volume, basal area, mean diameter, mean height, dominant height, and stem number can be thus predicted with better or comparable quality than with costly traditional field inventories. In this thesis, it is analysed the potential of LiDAR technology for the estimation of plot-level forest variables under a range of conditions (conifer & broadleaf temperate forests and tropical forests) and different LiDAR capture characteristics (nationwide LiDAR information vs. specific forest LiDAR data). This study evaluates the application of LiDAR-based plot-level methods in large areas. These methods are based on statistical relationships between predictor variables (derived from airborne data) and field-measured variables to generate wall to wall forest inventories. The fast development of this technology in recent years has led to an increasing availability of national LiDAR datasets, usually developed for multiple purposes throughout an expanding number of countries and regions. The evaluation of the validity of nationwide LiDAR databases (not designed specifically for forest purposes) is needed and presents a great opportunity for substantially reducing the costs of forest inventories. In chapter 2, the suitability of Spanish nationwide LiDAR flight (PNOA) to estimate forest variables is analyzed and compared to a specifically forest designed LiDAR flight. This study case shows that scan angle, terrain slope and aspect significantly affect the assessment of most of the LiDAR-derived forest variables and biomass estimation. Especially, the estimation of canopy cover is more affected than height percentiles. Considering the entire study area, biomass estimations from both databases do not show significant differences. Simulations show that differences in biomass could be larger (more than 4%) only in particular situations, such as steep areas when the slopes are non-oriented towards the scan lines and the scan angles are larger than 15º. In chapter 3, a multi-source approach is developed, integrating available databases such as nationwide LiDAR flights, Landsat imagery and permanent field plots from SNFI, with good resultos in the generation of wall to wall forest inventories. Volume and basal area errors are similar to those obtained by other authors (using specific LiDAR flights and field plots) for the same species. Errors in the estimation of stem number are larger than literature values as a consequence of the great influence that variable-radius plots, as used in SNFI, have on this variable. In chapters 4 and 5 wall to wall plot-level methodologies to estimate aboveground biomass and carbon density in tropical forest are evaluated. The study area is located in the Poas Volcano National Park (Costa Rica) and two different situations are analyzed: i) available complete LiDAR coverage (chapter 4) and ii) a complete LiDAR coverage is not available and wall to wall estimation is carried out combining LiDAR, Landsat and ancillary data (chapter 5). In chapter 4, a general aboveground biomass plot-level LiDAR model for tropical forest (Asner & Mascaro, 2014) is validated and a specific model for the study area is fitted. Both LiDAR plot-level models are based on the top-of-canopy height (TCH) variable that is derived from the LiDAR digital canopy model. Results show that the pantropical plot-level LiDAR methodology is a reliable alternative to the development of specific models for tropical forests and thus, aboveground biomass in a new study area could be estimated by only measuring basal area (BA). Applying this methodology, the definition of precise BA field measurement procedures (e.g. location, size and shape of the field plots) is decisive to achieve reliable results in future studies. The relation between BA and TCH (Stocking Coefficient) obtained in our study area in Costa Rica varied locally. Therefore, more field work is needed for assessing Stocking Coefficient variations between different life zones and the influence of the stratification of the study areas in tropical forests on the reduction of uncertainty. In chapter 5, the combination of systematic LiDAR information sampling and full coverage Landsat imagery (and ancillary data) prove to be an effective alternative for forest inventories in tropical areas. This methodology allows estimating wall to wall vegetation height, biomass and carbon density in large areas where full LiDAR coverage and traditional field work are technically and/or economically unfeasible. Carbon density prediction using Landsat imaginery shows a slight decrease in the determination coefficient and an increase in RMSE when harshly decreasing LiDAR coverage area. Results indicate that feasible estimates of vegetation height, biomass and carbon density can be accomplished using low LiDAR coverage areas (between 5% and 20% of the total area) in tropical locations.

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Abrupt climate changes from 18 to 15 thousand years before present (kyr BP) associated with Heinrich Event 1 (HE1) had a strong impact on vegetation patterns not only at high latitudes of the Northern Hemisphere, but also in the tropical regions around the Atlantic Ocean. To gain a better understanding of the linkage between high and low latitudes, we used the University of Victoria (UVic) Earth System-Climate Model (ESCM) with dynamical vegetation and land surface components to simulate four scenarios of climate-vegetation interaction: the pre-industrial era, the Last Glacial Maximum (LGM), and a Heinrich-like event with two different climate backgrounds (interglacial and glacial). We calculated mega-biomes from the plant-functional types (PFTs) generated by the model to allow for a direct comparison between model results and palynological vegetation reconstructions. Our calculated mega-biomes for the pre-industrial period and the LGM corresponded well with biome reconstructions of the modern and LGM time slices, respectively, except that our pre-industrial simulation predicted the dominance of grassland in southern Europe and our LGM simulation resulted in more forest cover in tropical and sub-tropical South America. The HE1-like simulation with a glacial climate background produced sea-surface temperature patterns and enhanced inter-hemispheric thermal gradients in accordance with the "bipolar seesaw" hypothesis. We found that the cooling of the Northern Hemisphere caused a southward shift of those PFTs that are indicative of an increased desertification and a retreat of broadleaf forests in West Africa and northern South America. The mega-biomes from our HE1 simulation agreed well with paleovegetation data from tropical Africa and northern South America. Thus, according to our model-data comparison, the reconstructed vegetation changes for the tropical regions around the Atlantic Ocean were physically consistent with the remote effects of a Heinrich event under a glacial climate background.

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The late Early to early Middle Eocene Okanagan Highlands fossil sites, spanning -1000 km north-south (northeastern Washington State, southern British Columbia) provide an opportunity to reconstruct biotic communities across a broad upland landscape during the warmest part of the Cenozoic. Plant taxa from these fossil sites are characteristic of the modern eastern North American deciduous forest zone, principally the mixed mesophytic forest, but also include extinct taxa, taxa known only from eastern Asian mesothermal forests, and a small number of taxa restricted to the present-day North American west coast coniferous biome. In this preliminary report, paleoclimates and forest types are reconstructed using collections from Republic in Washington State, USA., and Princeton, Quilchena, Falkland, McAbee, Hat Creek, Horsefly, and Driftwood Canyon in British Columbia, Canada. Both leaf margin analysis (LMA) and quantitative bioclimatic analysis of identified nearest living relatives of megaflora indicated upper microthermal to lower mesothermal moist environments (MAT -10-15 degrees C, CMMT > 0 degrees C, MAP > 100 cm/year). Some taxa common to most sites suggest cool conditions (e.g., Abies, other Pinaceae; Alnus, other Betulaceae). However, all floras contain a substantive broadleaf deciduous element (e.g., Fagaceae, Juglandaceae) and conifers (e.g., Metasequoia) with the bioclimatic analysis yielding slightly higher MAT than LMA. Thermophilic (principally mesothermal) taxa include various insects, the aquatic fern Azolla, palms, the banana relative Ensete, taxodiaceous conifers, Eucommia and Gordonia, taxa which may have occurred near their climatic limits. The mixture of thermophilic and temperate insect and plant taxa indicates low-temperature seasonality (i.e., highly equable climate).

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The strong selection pressure exerted by intensive use of glyphosate in cultivated areas has selected populations of the Rubiaceae weed species Borreria latifolia (Aubl.) K.Shum. (broadleaf buttonweed), Galianthe chodatiana (Standl.) E.L. Cabral (galiante) and Richardia brasiliensis Gomes (Brazilian pusley) with differential sensitivity to this herbicide in the South region of Brazil. The control of these weeds with herbicides is troublesome and signals the need to incorporate management practices of ruderal flora and crops, more sustainable and that results in more efficient control for long-term. Therefore, it is very important to expand the information about their biology and management. This study aimed: (a) select efficient methods to overcome dormancy of B. latifolia and G. chodatiana and determine how they influence the kinetics of seeds germination; (b) analyze the effects of temperature, irradiance, pH, aluminum and salinity on seed germination and initial growth of the B. latifolia, G. chodatiana e R. brasiliensis seedlings; (c) evaluate tolerance to glyphosate levels in biotypes of B. latifolia, G. chodatiana e R. brasiliensis through dose-response curves and compare two methods to evaluate herbicidal control; (d) and evaluated the effectiveness of alternative herbicides in pre-emergence and in early and late post-emergence of the three species. The treatment with KNO3 2%/3h + gibberellic acid 400 ppm resulted in higher percentage of G. chodatiana seed germination. This treatment and also the dry heat (60°C/30 min) + KNO3 2%/3h were more effective in overcoming dormancy of B. latifolia. G. chodatiana and R. brasiliensis tolerate lower temperatures during the germination process, while B. latifolia tolerate higher temperatures. B. latifolia and R. brasiliensis are positive photoblastic while G. chodatiana is indifferent to the photoperiod. B. latifolia shows higher germination and early development in pH 3, while G. chodatiana and R. brasiliensis prefer pH range between 5 and 7. B. latifolia and G. chodatiana were more tolerant to the aluminum during the germination process than R. brasiliensis. Low salt levels were sufficient to reduce the seed germination of the three species. Some biotypes of B. latifolia and R. brasiliensis showed medium-high glyphosate tolerance, not being controlled by higher doses than recommended. The G. chodatiana specie was not controlled with the highest dose used, showing a high glyphosate tolerance. The sulfentrazone, s-metolachlor and saflufenacil herbicides sprayed in pre-emergence showed high efficacy both on B. latifolia and R. brasiliensis, while chlorimuron-ethyl and diclosulan were effective only on R. brasiliensis. In early post-emergence the fomesafen, lactofem and flumioxazin herbicides efficiently controlled plants of all species, while bentazon showed high efficacy only on B. latifolia. Noteworthy the susceptibility of the G. chodatiana specie for applications in early post-emergence, because the control effectiveness and the number of effective herbicides are reduced with increasing the plant age. Many treatments with tank mix or sequencial applications with glyphosate, were effective in controlling B. latifolia and R. brasiliensis plants in advanced stage of development.