997 resultados para Forest-Agriculture Frontiers
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The reproductive success of tropical amphibians is influenced by factors such as body size and the characteristics of breeding sites. Data on reproductive biology are important for the understanding of population dynamics and the maintenance of species. The objectives of the present study were to examine the abundance of Ameerega trivittata, analyze the use of microhabitats by calling males and the snout-vent length (SVL) of breeding males and females, the number of tadpoles carried by the males and mature oocytes in the females, as well as the relationship between the SVL of the female and both the number and mean size of the mature oocytes found in the ovaries. Three field trips were conducted between January and September, 2009. A total of 31 plots, with a mean area of 2.3 ha, were surveyed, resulting in records of 235 individuals, with a mean density of 3.26 individuals per hectare. Overall, 66.1% of the individuals sighted were located in the leaf litter, while 17.4% were perched on decaying tree trunks on the forest floor, 15.7% on the aerial roots of Cecropia trees, and 0.8% on lianas. Males were observed transporting a mean of 10.8 tadpoles on their backs. A significant correlation was found between the size of the females and the mean diameter of the oocytes. New data were collected on the size of oocytes and no pattern was found in the type of perches used by calling males of the different Ameerega species.
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Radiometric changes observed in multi-temporal optical satellite images have an important role in efforts to characterize selective-logging areas. The aim of this study was to analyze the multi-temporal behavior of spectral-mixture responses in satellite images in simulated selective-logging areas in the Amazon forest, considering red/near-infrared spectral relationships. Forest edges were used to infer the selective-logging infrastructure using differently oriented edges in the transition between forest and deforested areas in satellite images. TM/Landsat-5 images acquired at three dates with different solar-illumination geometries were used in this analysis. The method assumed that the radiometric responses between forest with selective-logging effects and forest edges in contact with recent clear-cuts are related. The spatial frequency attributes of red/near infrared bands for edge areas were analyzed. Analysis of dispersion diagrams showed two groups of pixels that represent selective-logging areas. The attributes for size and radiometric distance representing these two groups were related to solar-elevation angle. The results suggest that detection of timber exploitation areas is limited because of the complexity of the selective-logging radiometric response. Thus, the accuracy of detecting selective logging can be influenced by the solar-elevation angle at the time of image acquisition. We conclude that images with lower solar-elevation angles are less reliable for delineation of selecting logging.
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Species distribution modeling has relevant implications for the studies of biodiversity, decision making about conservation and knowledge about ecological requirements of the species. The aim of this study was to evaluate if the use of forest inventories can improve the estimation of occurrence probability, identify the limits of the potential distribution and habitat preference of a group of timber tree species. The environmental predictor variables were: elevation, slope, aspect, normalized difference vegetation index (NDVI) and height above the nearest drainage (HAND). To estimate the distribution of species we used the maximum entropy method (Maxent). In comparison with a random distribution, using topographic variables and vegetation index as features, the Maxent method predicted with an average accuracy of 86% the geographical distribution of studied species. The altitude and NDVI were the most important variables. There were limitations to the interpolation of the models for non-sampled locations and that are outside of the elevation gradient associated with the occurrence data in approximately 7% of the basin area. Ceiba pentandra (samaúma), Castilla ulei (caucho) and Hura crepitans (assacu) is more likely to occur in nearby water course areas. Clarisia racemosa (guariúba), Amburana acreana (cerejeira), Aspidosperma macrocarpon (pereiro), Apuleia leiocarpa (cumaru cetim), Aspidosperma parvifolium (amarelão) and Astronium lecointei (aroeira) can also occur in upland forest and well drained soils. This modeling approach has potential for application on other tropical species still less studied, especially those that are under pressure from logging.
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Trophic relationships in fish communities are affected by the availability of resources, which in turn is affected by spatial and temporal variations throughout the year. The aims of this study were to characterize the diet of A. tetramerus in a streamlet in the north of Brazil and compare its composition in different hydrological seasons (wet and dry seasons). Collections were performed every two months from October 2011 to September 2012 with the aid of seine nets, hand net and fishing traps in the streamlet located in the Machado River drainage basin in the Rondônia state. Most of the specimens collected were quite small (< 40 mm) and had empty stomachs. Our results showed that A. tetramerus feeds on a wide variety of items of plant origin, such as algae, seeds and leaves, as well as items of animal origin, including bryozoans, crustaceans, fish scales, terrestrial insects and detritus. The data also indicated higher consumption of aquatic insects than other food items, suggesting a primarily insect-based diet. Items of plant and allochthonous origin were consumed more in the wet season than in the dry season, but there were no seasonal differences in the consumption of animal and autochthonous items.
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ABSTRACTThe Amazon várzeas are an important component of the Amazon biome, but anthropic and climatic impacts have been leading to forest loss and interruption of essential ecosystem functions and services. The objectives of this study were to evaluate the capability of the Landsat-based Detection of Trends in Disturbance and Recovery (LandTrendr) algorithm to characterize changes in várzeaforest cover in the Lower Amazon, and to analyze the potential of spectral and temporal attributes to classify forest loss as either natural or anthropogenic. We used a time series of 37 Landsat TM and ETM+ images acquired between 1984 and 2009. We used the LandTrendr algorithm to detect forest cover change and the attributes of "start year", "magnitude", and "duration" of the changes, as well as "NDVI at the end of series". Detection was restricted to areas identified as having forest cover at the start and/or end of the time series. We used the Support Vector Machine (SVM) algorithm to classify the extracted attributes, differentiating between anthropogenic and natural forest loss. Detection reliability was consistently high for change events along the Amazon River channel, but variable for changes within the floodplain. Spectral-temporal trajectories faithfully represented the nature of changes in floodplain forest cover, corroborating field observations. We estimated anthropogenic forest losses to be larger (1.071 ha) than natural losses (884 ha), with a global classification accuracy of 94%. We conclude that the LandTrendr algorithm is a reliable tool for studies of forest dynamics throughout the floodplain.
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ABSTRACT The analysis of changes in species composition and vegetation structure in chronosequences improves knowledge on the regeneration patterns following land abandonment in the Amazon. Here, the objective was to perform floristic-structural analysis in mature forests (with/without timber exploitation) and secondary successions (initial, intermediate and advanced vegetation regrowth) in the Tapajós region. The regrowth age and plot locations were determined using Landsat-5/Thematic Mapper images (1984-2012). For floristic analysis, we determined the sample sufficiency and the Shannon-Weaver (H'), Pielou evenness (J), Value of Importance (VI) and Fisher's alpha (α) indices. We applied the Non-metric Multidimensional Scaling (NMDS) for similarity ordination. For structural analysis, the diameter at the breast height (DBH), total tree height (Ht), basal area (BA) and the aboveground biomass (AGB) were obtained. We inspected the differences in floristic-structural attributes using Tukey and Kolmogorov-Smirnov tests. The results showed an increase in the H', J and α indices from initial regrowth to mature forests of the order of 47%, 33% and 91%, respectively. The advanced regrowth had more species in common with the intermediate stage than with the mature forest. Statistically significant differences between initial and intermediate stages (p<0.05) were observed for DBH, BA and Ht. The recovery of carbon stocks showed an AGB variation from 14.97 t ha-1 (initial regrowth) to 321.47 t ha-1 (mature forests). In addition to AGB, Ht was also important to discriminate the typologies.
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El avance de la frontera agropecuaria y la urbanización han reducido la superficie boscosa del Espinal en Córdoba a fragmentos que son sumamente valiosos como relictos del ambiente original del Algarrobal y como barreras frente a la acción erosiva del agua y los vientos. Por su estructura, degradada y enmarañada, el productor agropecuario generalmente los visualiza como una molestia ya que le restan superficie apta para el cultivo y resultan poco aprovechables para el pastoreo de los animales. Bajo pautas de manejo adecuadas estos bosquecillos podrían rehabilitarse para el aprovechamiento del ganado y otros usos complementarios. Para que el productor local cuente con herramientas de manejo sustentable de sus recursos naturales es necesario generar información confiable para la zona. En ese contexto, se plantea la siguiente Hipótesis General: Existen alternativas de manejo que, aplicadas sobre los bosques del Espinal, permiten recuperar y conservar la biodiversidad a la vez que mejoran la rentabilidad del productor. El Objetivo General es diseñar y evaluar, en términos ecológicos, tecnológicos y socio-económicos, alternativas de manejo sustentable de bosques degradados del Espinal de la provincia de Córdoba tendientes a su recuperación y conservación. El proyecto se localizará en el bosque fragmentado del Campo Escuela de la FCA-UNC. Se establecerán parcelas con distintos niveles de cobertura arbustiva en las que se medirán el efecto de los arbustos sobre la regeneración de especies arbóreas deseables, la producción y calidad de la pastura, el crecimiento de los árboles y las condiciones edáficas del sistema. Además, la incidencia del ganado vacuno sobre la regeneración de especies arbóreas deseables, la riqueza y abundancia de especies forrajeras deseables y las condiciones edáficas del sistema. Se hará enriquecimiento con plantines de tres especies de Prosopis tanto en el bosque con distintos anchos de fajas como en suelo desmontado, para evaluar su comportamiento. También se probará la diseminación y establecimiento posterior de estas especies por medio de la ingesta del ganado vacuno. Se relevarán especies medicinales, aromáticas, melíferas, tintóreas y ornamentales nativas, y se las valorará económicamente según su uso actual y potencial en esta y otras zonas de la provincia y el país. Se efectuará la caracterización socio-económica y ambiental del área circundante al Campo Escuela y mediante encuestas se determinará el grado de valorización del bosque que tienen los pobladores zonales. Se realizará el análisis económico y financiero del sistema propuesto versus el sistema sin proyecto, considerando bienes producidos y servicios ambientales del bosque y se socializará el proyecto a través de encuestas y reuniones participativas con los productores zonales. Para el análisis de toda la información se usará el software INFOSTAT 2007. Se harán tablas y gráficos de estadística descriptiva para visualizar la distribución de datos. Se usará análisis de correlación, análisis de regresión lineal múltiple, ANAVA y test a posteriori. Se espera generar pautas preliminares de manejo, sencillas y económicas, fácilmente adoptables por los productores de la región, que aseguren la persistencia de estos fragmentos boscosos, relictos de la vegetación original del Espinal.
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Se propone analizar el efecto del uso productivo en el Chaco Árido de la provincia de Córdoba, mediante la aplicación de indicadores de sustentabilidad relacionados con la calidad de la materia orgánica y la liberación de nutrientes en el suelo, con la finalidad de aportar a un tema de suma interes para la provincia de Córdoba como es la formulación de criterios y pautas de manejo para la implementación de la Ley de Bosques (N° 26331). Se trabajará en la localidad de San Miguel en el departamento Pocho, en un sitio de bosque no disturbado y en tres sistemas productivos: desmonte selectivo con implantación de pasturas; desmonte total con agricultura bajo riego y desmonte total sobrepastoreado. En cada sitio se medirá “in situ” la emisión de CO2 y se tomaran muestras de suelo a las que se les determinará: a) contenido de materia orgánica total (MO), b) contenido de sustancias húmicas (SH), diferenciando ácidos húmicos (AH) y fúlvicos (AF), c) abundancia y actividad de microorganismos nitrificadores y d) propiedades químicas de los AH y AF. Se calcularán los siguientes índices de sustentabilidad a) materia orgánica biodisponible (MOB=MO–SH); b) índice de humificación (IH=SH/MO); c) tipo de humus (TH=AF/AH; d) índice de mineralización de C (IMC=CO2/MO); e) índice de nitrificación (IN=actividad/abundancia); y f) índice de estabilidad de las fracciones humificadas: compuestos aromáticos/ alifáticos. Los datos serán analizados estadísticamente mediante ANOVA y comparación de medias por LSD (P<0.05) y tests multivariados. We proposed analyze the effect of land use in Arid Chaco of Cordoba province, using sustainability indicators related to organic matter quality and nutrient release in soil, with the aim to formulate management criteria for the implementation of the Ley de Bosques (N° 26331) in Córdoba province. The study will be conducted in San Miguel village in Pocho department, in one undisturbed forest site and three productive systems: selective clearing with grass sowing; total clearing with irrigation agriculture and total clearing with overgrazed. In each site "in situ" CO2 emission will be measured and soil samples will be taken, in which the following parameters will be determined: a) total organic matter content (MO), b) humic substances content (SH), in humic acids (AH) and fulvic acids (AF), c) abundance and activity of nitrifier microorganisms and d) chemical properties of AH and AF. The sustainability indexes will be calculated: biodisponible organic matter (MOB=MO–SH); b) humification index (IH=SH/MO); c) humus type (TH=AF/AH; d) C mineralization index (IMC=CO2/MO); e) nitrifying index (IN=activity/abundance); and f) humic fractions stability index: aromatic/aliphatic compounds. The data will be statistically analyzed by ANOVA and the means will be compared by LSD (P<0.05) and multivariate tests.
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A partir de las últimas décadas se ha impulsado el desarrollo y la utilización de los Sistemas de Información Geográficos (SIG) y los Sistemas de Posicionamiento Satelital (GPS) orientados a mejorar la eficiencia productiva de distintos sistemas de cultivos extensivos en términos agronómicos, económicos y ambientales. Estas nuevas tecnologías permiten medir variabilidad espacial de propiedades del sitio como conductividad eléctrica aparente y otros atributos del terreno así como el efecto de las mismas sobre la distribución espacial de los rendimientos. Luego, es posible aplicar el manejo sitio-específico en los lotes para mejorar la eficiencia en el uso de los insumos agroquímicos, la protección del medio ambiente y la sustentabilidad de la vida rural. En la actualidad, existe una oferta amplia de recursos tecnológicos propios de la agricultura de precisión para capturar variación espacial a través de los sitios dentro del terreno. El óptimo uso del gran volumen de datos derivado de maquinarias de agricultura de precisión depende fuertemente de las capacidades para explorar la información relativa a las complejas interacciones que subyacen los resultados productivos. La covariación espacial de las propiedades del sitio y el rendimiento de los cultivos ha sido estudiada a través de modelos geoestadísticos clásicos que se basan en la teoría de variables regionalizadas. Nuevos desarrollos de modelos estadísticos contemporáneos, entre los que se destacan los modelos lineales mixtos, constituyen herramientas prometedoras para el tratamiento de datos correlacionados espacialmente. Más aún, debido a la naturaleza multivariada de las múltiples variables registradas en cada sitio, las técnicas de análisis multivariado podrían aportar valiosa información para la visualización y explotación de datos georreferenciados. La comprensión de las bases agronómicas de las complejas interacciones que se producen a la escala de lotes en producción, es hoy posible con el uso de éstas nuevas tecnologías. Los objetivos del presente proyecto son: (l) desarrollar estrategias metodológicas basadas en la complementación de técnicas de análisis multivariados y geoestadísticas, para la clasificación de sitios intralotes y el estudio de interdependencias entre variables de sitio y rendimiento; (ll) proponer modelos mixtos alternativos, basados en funciones de correlación espacial de los términos de error que permitan explorar patrones de correlación espacial de los rendimientos intralotes y las propiedades del suelo en los sitios delimitados. From the last decades the use and development of Geographical Information Systems (GIS) and Satellite Positioning Systems (GPS) is highly promoted in cropping systems. Such technologies allow measuring spatial variability of site properties including electrical conductivity and others soil features as well as their impact on the spatial variability of yields. Therefore, site-specific management could be applied to improve the efficiency in the use of agrochemicals, the environmental protection, and the sustainability of the rural life. Currently, there is a wide offer of technological resources to capture spatial variation across sites within field. However, the optimum use of data coming from the precision agriculture machineries strongly depends on the capabilities to explore the information about the complex interactions underlying the productive outputs. The covariation between spatial soil properties and yields from georeferenced data has been treated in a graphical manner or with standard geostatistical approaches. New statistical modeling capabilities from the Mixed Linear Model framework are promising to deal with correlated data such those produced by the precision agriculture. Moreover, rescuing the multivariate nature of the multiple data collected at each site, several multivariate statistical approaches could be crucial tools for data analysis with georeferenced data. Understanding the basis of complex interactions at the scale of production field is now within reach the use of these new techniques. Our main objectives are: (1) to develop new statistical strategies, based on the complementarities of geostatistics and multivariate methods, useful to classify sites within field grown with grain crops and analyze the interrelationships of several soil and yield variables, (2) to propose mixed linear models to predict yield according spatial soil variability and to build contour maps to promote a more sustainable agriculture.
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