983 resultados para Marsh, Daniel L. (Daniel Lash), 1880-1968
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Fil: Chain, Leyla Inés. Universidad Nacional de La Plata. Facultad de Humanidades y Ciencias de la Educación; Argentina.
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Nos proponemos analizar el rol desempeñado por las agencias estatales en el proceso de modernización de la agricultura cañera en Tucumán. Centraremos nuestra atención en la labor desarrollada por el Departamento Nacional de Agricultura (posteriormente convertido en Ministerio) y en el accionar de las oficinas públicas provinciales en la creación de instituciones educativas y experimentales como base para el desarrollo agroindustrial. Como complemento, estudiaremos la interacción entre el Estado y el sector privado (tanto cañeros, industriales, como personal cientÃfico involucrado en la actividad) frente a las reformas propuestas para incorporar la agricultura 'cientÃfica' en el espacio rural tucumano.
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Fil: Bisso, Andrés. Universidad Nacional de La Plata. Facultad de Humanidades y Ciencias de la Educación; Argentina.
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El enfoque comportamental y perceptual que asume la ciencia geográfica puede resultar un aporte muy importante a la gestión ambiental del territorio. Dicho enfoque no pretende suplantar al enfoque cuantitativo, si postula su complementariedad. El presente trabajo plantea como objetivo general conocer la percepción que los habitantes de la localidad de General Daniel Cerri (BahÃa Blanca, Buenos Aires, Argentina) poseen sobre su calidad de vida ambiental. La metodologÃa empleada fue una encuesta de población representativa de la localidad en estudio, dividida en tres partes: una parte estructural -que permitirá conocer la forma en que la información que se posee sobre el lugar es percibida-; un apartado valorativo -que indicará cómo se valora el espacio en relación con las decisiones que se deberÃan adoptar-; y uno preferencial -orientado al análisis de las preferencias que se tienen respecto de algunos lugares
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Fil: Máspoli, Evangelina. Universidad Nacional de La Plata. Facultad de Humanidades y Ciencias de la Educación; Argentina.
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Fucus vesiculosus L. (Phaeophyceae) is the most abundant and hence ecologically most important primary producer, carbon sink and habitat provider in the western Baltic Sea. All F. vesiculosus L. specimens were collected on 23 April 2014 from a depth of 0.2-1 m in the non-tidal Kiel Fjord, western Baltic Sea (54°27'N; 10°12'E), where this species forms dense and almost monospecific stands on stones. After sampling the algal thalli were stored in a refrigerator box with water from the sampling site, transported to Bremerhaven and stored at 10 °C for one day in filtered seawater. Experiments were conducted with vegetative apical tips (6.7±0.5 cm length), the actively growing region of F. vesiculosus, which were randomly selected and cut from 144 different individuals prior to the experiments. These tips were acclimated to laboratory conditions for three days in filtered seawater at 10 °C before the start of the experiment. Furthermore, 30 additional vegetative apices were freeze-dried to document the initial biochemical status of F. vesiculosus in its native habitat. A temperature gradient was installed in a walk-in constant cooling chamber (15 °C) in nine water baths (5, 10, 15, 20, 24, 26, 27, 28 and 29 °C ± 0.1 °C) which were tempered by thermostats (5, 10 and 15 °C: Huber Variostat CC + Pilot ONE, Peter Huber Kältemaschinen GmbH, Offenburg, Germany; 20 and 28 °C: Haake DC3, Thermo Fisher Scientific Inc., Waltham, USA; 24, 26, 27 and 29 °C: Haake DC10). Every temperature treatment consisted of four 2 L glass beakers (n = 4). In each beaker four F. vesiculosus apices were grown in 2 µm-filtered North Sea water diluted with demineralized water in a ratio of 1:1 and enriched with nutrients after Provasoli (1968; 1/10 enrichment), leading to a salinity of about 15.6 which equaled habitat conditions. The algae were exposed to an irradiance of 130 µmol photons m-2 s-1 ±10 % (Powerstar HGI-TS 150 W, OSRAM GmbH, Bad Homburg, Germany) measured at the top of the beaker under a 16:8 h L:D cycle. The media in the beakers was changed every third or fourth day and aerated with artificial air containing 380 ppm CO2 (gas mixing device; HTK Hamburg GmbH, Hamburg, Germany). Before the experiment, the algae were acclimated to the final temperatures in steps of 5 °C for 2 days each, beginning at 10 °C. After 21 days exposure time, three out of four samples per replicate were freeze-dried for further biochemical analyses, and afterwards the thermostats were turned off to reduce the temperature to 16±0.4 °C for another 10 days permitting growth under post-culture conditions.
Meteorological observations during Jan Daniel cruise from Nederland to Batavia started at 1852-08-19
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The episodic occurrence of debris flow events in response to stochastic precipitation and wildfire events makes hazard prediction challenging. Previous work has shown that frequency-magnitude distributions of non-fire-related debris flows follow a power law, but less is known about the distribution of post-fire debris flows. As a first step in parameterizing hazard models, we use frequency-magnitude distributions and cumulative distribution functions to compare volumes of post-fire debris flows to non-fire-related debris flows. Due to the large number of events required to parameterize frequency-magnitude distributions, and the relatively small number of post-fire event magnitudes recorded in the literature, we collected data on 73 recent post-fire events in the field. The resulting catalog of 988 debris flow events is presented as an appendix to this article. We found that the empirical cumulative distribution function of post-fire debris flow volumes is composed of smaller events than that of non-fire-related debris flows. In addition, the slope of the frequency-magnitude distribution of post-fire debris flows is steeper than that of non-fire-related debris flows, evidence that differences in the post-fire environment tend to produce a higher proportion of small events. We propose two possible explanations: 1) post-fire events occur on shorter return intervals than debris flows in similar basins that do not experience fire, causing their distribution to shift toward smaller events due to limitations in sediment supply, or 2) fire causes changes in resisting and driving forces on a package of sediment, such that a smaller perturbation of the system is required in order for a debris flow to occur, resulting in smaller event volumes.
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The HCMR_SES_LAGRANGIAN_GR2_ MICROBIAL PARAMETERS dataset is based on samples collected in the framework of the project SESAME, in the North Aegean Sea during October 2008. The objectives were to measure the standing stocks and calculate the production of the microbial compartment of the food web, describe the vertical distribution pattern and characterize its structure and function through the water column as influenced by the BSW. Heterotrophic bacteria, Synechococcus, Prochlorococcus and Virus abundance: Subsamples for virus, heterotrophic bacteria and cyanobacteria (Synechococcus spp. and Prochlorococcus spp.) counting were analyzed using a FACSCalibur (Becton Dickinson) flow cytometer equipped with a standard laser (488 nm) and filter set and using deionized water as sheath fluid. Fluorescent beads with a diameter of 0.97 µm (Polysciences) were added to each sample as an internal standard, and all parameters were normalized to the beads and expressed as relative units. SYBRGreen I stain (Molecular Probe) was used to stain viral and heterotrophic bacterial DNA. Viruses were counted according to (Brussaard 1984). In order to avoid bulk consentrations of viruses samples we dilluted to Tris-EDTA (pH=8,0) buffer to a final sollution of 1/5 to 1/100. Total abundance and nucleid content classes were calculated using the Paint-A-Gate software (Becton Dickinson). Heterotrophic Nanoflagellate abundance: Subsamples (30-150 ml) were concentrated on 25mm black polycarbonate filters of porosity 0.6?m and stained with DAPI for 10 min (Porter and Feig 1980). Under epifluorescence microscopy heterotrophic nanoflagellates (HNAN) were distinguished using UV and blue excitation and enumerated. Nanoflagellates were classified in size categories and the biovolume was calculated. Ciliate abundance: For ciliate identification and enumeration, 100-3000 ml samples were left for 24h-4d for sedimentation and then observed under an inverted microscope. Ciliates were counted, distinguished into size-classes and major taxonomic groups and identified down to genus or species level where possible (Pitta et al. 2005). Heterotrophic bacteria, Synechococcus, Prochlorococcus bacteria: Subsamples for virus, heterotrophic bacteria and cyanobacteria (Synechococcus spp. and Prochlorococcus spp.) counting were analyzed using a FACSCalibur (Becton Dickinson) flow cytometer equipped with a standard laser (488 nm) and filter set and using deionized water as sheath fluid. Fluorescent beads with a diameter of 0.97 µm (Polysciences) were added to each sample as an internal standard, and all parameters were normalized to the beads and expressed as relative units. SYBRGreen I stain (Molecular Probe) was used to stain viral and heterotrophic bacterial DNA. Viruses were counted according to (Brussaard 1984). In order to avoid bulk consentrations of viruses samples we dilluted to Tris-EDTA (pH=8,0) buffer to a final sollution of 1/5 to 1/100. Total abundance and nucleid content classes were calculated using the Paint-A-Gate software (Becton Dickinson). Abundance data were converted into C biomass using 250 fgC cell-1 (Kana & Glibert 1987) for Synechococcus, 50 fgC cell-1 (Campbell et al. 1994) for Prochlorococcus and 20fgC cell-1 (Lee & Fuhrman 1987) for heterotrophic bacteria. Heterotrophic Nanoflagellate biomass: Subsamples (30-150 ml) were concentrated on 25mm black polycarbonate filters of porosity 0.6µm and stained with DAPI for 10 min (Porter and Feig 1980). Under epifluorescence microscopy heterotrophic nanoflagellates (HNAN) were distinguished using UV and blue excitation and enumerated. Nanoflagellates were classified in size categories and the biovolume was calculated. Abundance data were converted into C biomass using 183 fgC µm**3 (Caron et al. 1995). Ciliate biomass: For ciliate identification and enumeration, 100-3000 ml samples were left for 24h-4d for sedimentation and then observed under an inverted microscope. Ciliates were counted, distinguished into size-classes and major taxonomic groups and identified down to genus or species level where possible (Pitta et al. 2005). Ciliate cell sizes were measured and converted into cell volumes using appropriate geometric formulae using image analysis. For biomass estimation, the conversion factor 190 fgC µm**3 was used (Putt and Stoecker 1989).