7 research outputs found

    Floristic Composition And Structure Of A Tropical Dry Forest At Different Successional Stages In The Espinhaço Mountains, Southeastern Brazil

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    The floristic composition and structure of intermediate and late successional stages of a tropical dry forest (TDF) growing on limestone outcrops, situated in the southern portion of the Espinhaço Mountains, Southeastern Brazil, was studied. In each fragment, three plots of 20×50m were delimited, totaling 0.3ha for each successional stage. In each plot, all trees with a diameter at breast height (DBH) >5cm were sampled and identified. Standard phyto-sociological parameters were calculated and compared between stages. The most representative families in the two successional stages were Fabaceae, Apocynaceae and Malvaceae, but species composition differed between intermediate and late stages: species with highest importance value in the former were Myracrodruon urundeuva, Rauwolfia sellowii and Inga platyptera, whereas Anadenanthera colubrina, Myracrodruon urundeuva and Bauhinia brevipes predominated in the latter. The main parameters measured varied with the successional stage. In the intermediate stage, the structural parameters were: basal area 17.8m2·h-1, density 1076 individuals/ha, average height 6.30m, species richness 23, while community indexes were Shannon-Winner biodiversity 1.51 and Pielou evenness 0.48. For the late succession stage, the structural parameters were: basal area 29.3m 2·h-1, density 1226 individuals/ha, average height 7.7m and species richness 38; community indexes were Shannon-Winner's diversity 2.38 and Pielou's evenness 0.64. Due to the marked isolation, this TDF has a unique floristic composition. Results demonstrated important changes in floristic composition and structure along two successional stages, contributing to ecological process understanding. The limited knowledge about this rich ecosystem was expanded and the urgent need for its preservation is reinforced.373190196Almeida, H.S., MacHado, E.L.M., Relações fo-rísticas entre remanescentes de foresta es-tacional decídua no Brasil (2007) Rev. Bras. 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    Using visible-near-infrared spectroscopy to classify lichens at a Neotropical Dry Forest

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    The optical properties of lichens have been traditionally explored in the context of geological mapping where the encrustation of lichens on rocks may influence the detection of minerals of interest. As of today, few studies have looked into the potential of using the optical properties of lichens to classify them; however, none has investigated the classification of tropical lichens using spectroscopy. Here we explore the use of the visible-near infrared reflectance (VNIR; 450–1000 nm) to discriminate Neotropical corticolous lichens; the most abundant lichens in tropical forests. Reflectance measurements on lichens and their bark substrate were performed on 282 lichens samples of 32 species attached to their host's bark. Using these measurements, we first explored the degree of spectral mixing of bark and lichens by linear unmixing each lichen spectrum with the corresponding average species spectrum and bark spectrum. Overall, the results reveal that the lichen signatures tend to mask the spectral contributions from bark; however, there are some specific groups of species with high bark mixing probably due to their nature and the similarities between the lichen and bark spectra. Next, we classified the lichen spectra based on growth forms and taxonomic ranks (i.e., family, genus, species) using five machine learning classifiers. This analysis was conducted on raw reflectance spectra and wavelet-transformed spectra to enhance the absorption features prior to classification. As expected, the classification of lichen spectra is less accurate at species-specific levels, rather than higher taxonomic ranks. The wavelet transformation was found to enhance the general performance of classification; however, the accuracy of the classification depends on the classifier. Of the classifiers used in this study, linear discrimination applied to reflectance spectra presents the highest performance at the species level. Our results reveal the potential of using the VNIR reflectance as a method to discriminate Neotropical lichens. The introduced methodology may be conducted in the field, thus allowing the monitoring of lichen communities in forests; thereby furthering the current understanding of the role of lichens in ecosystem functioning.Las propiedades ópticas de los líquenes se han explorado tradicionalmente en el contexto del mapeo geológico donde la incrustación de líquenes en las rocas puede influir en la detección de minerales de interés. Hasta la fecha, pocos estudios han examinado el potencial de utilizar las propiedades ópticas de los líquenes para clasificarlos; sin embargo, ninguno ha investigado la clasificación de los líquenes tropicales mediante espectroscopia. Aquí exploramos el uso de la reflectancia del infrarrojo cercano visible (VNIR; 450–1000 nm) para discriminar líquenes cortícolas neotropicales; los líquenes más abundantes en los bosques tropicales. Las mediciones de reflectancia en líquenes y su sustrato de corteza se realizaron en 282 muestras de líquenes de 32 especies adheridas a la corteza de su huésped. Usando estas medidas, primero exploramos el grado de mezcla espectral de la corteza y los líquenes mediante la desmezcla lineal de cada espectro de líquenes con el espectro de especies promedio correspondiente y el espectro de corteza. En general, los resultados revelan que las firmas de los líquenes tienden a enmascarar las contribuciones espectrales de la corteza; sin embargo, existen algunos grupos específicos de especies con una alta mezcla de corteza probablemente debido a su naturaleza y las similitudes entre los espectros de líquenes y corteza. A continuación, clasificamos los espectros de líquenes según las formas de crecimiento y los rangos taxonómicos (es decir, familia, género, especie) utilizando cinco clasificadores de aprendizaje automático. Este análisis se realizó en espectros de reflectancia sin procesar y espectros transformados por ondículas para mejorar las características de absorción antes de la clasificación. Como era de esperar, la clasificación de los espectros de líquenes es menos precisa a niveles específicos de especies, en lugar de rangos taxonómicos más altos. Se descubrió que la transformación de ondículas mejora el rendimiento general de la clasificación; sin embargo, la precisión de la clasificación depende del clasificador. De los clasificadores utilizados en este estudio, la discriminación lineal aplicada a los espectros de reflectancia presenta el rendimiento más alto a nivel de especie. Nuestros resultados revelan el potencial de utilizar la reflectancia VNIR como método para discriminar líquenes neotropicales. La metodología introducida podrá realizarse en el campo, permitiendo así el seguimiento de las comunidades de líquenes en los bosques; fomentando así la comprensión actual del papel de los líquenes en el funcionamiento de los ecosistemas.Universidad Nacional, Costa RicaUniversity of Minnesota Twin Cities, USAUniversity of Alberta, CanadaEscuela de Ciencias Biológica

    SpecNet revisited: bridging flux and remote sensing communities

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    Spectral Network (SpecNet) began as a Working Group in 2003 with the goals of integrating remote sensing with biosphere-atmosphere carbon flux measurements and standardizing field optical sampling methods. SpecNet has evolved into an international network of collaborating sites and investigators, with a particular focus on matching optical sampling tools to the temporal and spatial scale of flux measurements and ecological sampling. Current emphasis within the SpecNet community is on greater automation of field optical sampling using simple cost-effective technologies, improving the light-use-efficiency (LUE) model of carbon dioxide flux, consideration of view and illumination angle to improve physiological retrievals, and incorporation of informatics and cyberinfrastructure solutions that address the increasing data dimensionality of cross-site and multiscale sampling. In this review, we summarize recent findings and current directions within the SpecNet community and provide recommendations for the larger remote sensing and flux communities. These recommendations include comparing the LUE model to other flux models driven by remote sensing, considering a wider array of biogenic trace gases in addition to carbon dioxide, adoption of standardized and automated field sensors and sampling protocols where possible, continued development of cyberinfrastructure tools to facilitate data comparison and integration, expanding the network itself so that a greater range of sites are covered by combined optical and flux measurements, and encouraging a broader communication between the flux and remote sensing communities

    Rates of change in tree communities of secondary Neotropical forests following major disturbances

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    Rates of change in tree communities following major disturbances are determined by a complex set of interactions between local site factors, landscape history and structure, regional species pools and species life histories. Our analysis focuses on vegetation change following abandonment of agricultural fields or pastures, as this is the most extensive form of major disturbance in Neotropical forests. We consider five tree community attributes: stem density, basal area, species density, species richness and species composition. We describe two case studies, in northeastern Costa Rica and Chiapas, Mexico, where both chronosequence and annual tree dynamics studies are being applied. These case studies show that the rates of change in tree communities often deviate from chronosequence trends. With respect to tree species composition, sites of different ages differ more than a single site followed over time through the same age range. Dynamic changes in basal area within stands, on the other hand, generally followed chronosequence trends. Basal area accumulation was more linked with tree growth rates than with net changes in tree density due to recruitment and mortality. Stem turnover rates were poor predictors of species turnover rates, particularly at longer time-intervals. Effects of the surrounding landscape on tree community dynamics within individual plots are poorly understood, but are likely to be important determinants of species accumulation rates and relative abundance patterns
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