632 resultados para Tuberculo (Botanica)
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Also published in Linnés Amoenitates academicae, vol. 1, [ed. 1] 1749, p. 352-388; [ed. 2] 1749, p. 509-539; ed. 3, 1787, p. 509-540. For other reprints and translations see Krok, T.O.B.N. Bibliotheca botanica suecana (1925): Aspelin. 1.
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Also in Linné's Amoenitates academicae, v. 6, ed. 1, 1763; ed. 2, 1789, p. 116-131. For reprints and translations see T.O.B.N. Krok, Bibliotheca botanica suecana (1925) : Linné. 113.
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Half title page reads: Corso delle botaniche lezioni del dottor Michele Tenore
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"Errori, correzioni" at end.
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Title following prologue: Flora Chilena.
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Bibliograhy: p. [169]-174.
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Mode of access: Internet.
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Issued in 28 parts; no more published.
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Title from cover.
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Vols. 6-9, fasc. 2, 1907-June 15, 1910, have subtitle: Revista de sciencias naturaes do Collegio de S. Fiel; v. 9, fasc. 3, Nov. 1, 1910, Revista de sciencias naturaes; v. 10-21, 1912-24, Revista luso-brasileira.
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Subtitles vary; v. 1 has special t.p. in Latin and German; v. 25, pt. [2] is without t.-p.
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Climate change highly impacts on tree growth and also threatens the forest of the karstic terrains. From the 1980s the frequency of decay events of the Pinus nigra Arnold forests showed a marked increase in Hungary. To understanding the vulnerability of Pinus nigra forests to climate change on shallow karstic soils in continental-sub Mediterranean climatic conditions we developed the study of three sampled population in the typical karstic landscape of Veszprém in North Transdanubia. We built our model on non-invasive approach using the annual growth of the individuals. MPI Echam5 climate model and as aridity index the Thornthwaite Agrometeorological Index were used. Our results indicate that soil thickness up to 11 cm has a major influence on the main growth intensity, however, aridity determines the annual growth rate. Our model results showed that the increasing decay frequency in the last decades was a parallel change to the decreasing growth rate of pines. The climate model predicts the similar, increased decay frequency to the presents. Our results can be valid for a wider areas of the periphery of Mediterranean climate zone while the annual-growth based model is a cost-effective and simple method to study the vitality of pine trees in a given area.
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The exponential growth of studies on the biological response to ocean acidification over the last few decades has generated a large amount of data. To facilitate data comparison, a data compilation hosted at the data publisher PANGAEA was initiated in 2008 and is updated on a regular basis (doi:10.1594/PANGAEA.149999). By January 2015, a total of 581 data sets (over 4 000 000 data points) from 539 papers had been archived. Here we present the developments of this data compilation five years since its first description by Nisumaa et al. (2010). Most of study sites from which data archived are still in the Northern Hemisphere and the number of archived data from studies from the Southern Hemisphere and polar oceans are still relatively low. Data from 60 studies that investigated the response of a mix of organisms or natural communities were all added after 2010, indicating a welcomed shift from the study of individual organisms to communities and ecosystems. The initial imbalance of considerably more data archived on calcification and primary production than on other processes has improved. There is also a clear tendency towards more data archived from multifactorial studies after 2010. For easier and more effective access to ocean acidification data, the ocean acidification community is strongly encouraged to contribute to the data archiving effort, and help develop standard vocabularies describing the variables and define best practices for archiving ocean acidification data.
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An object based image analysis approach (OBIA) was used to create a habitat map of the Lizard Reef. Briefly, georeferenced dive and snorkel photo-transect surveys were conducted at different locations surrounding Lizard Island, Australia. For the surveys, a snorkeler or diver swam over the bottom at a depth of 1-2m in the lagoon, One Tree Beach and Research Station areas, and 7m depth in Watson's Bay, while taking photos of the benthos at a set height using a standard digital camera and towing a surface float GPS which was logging its track every five seconds. The camera lens provided a 1.0 m x 1.0 m footprint, at 0.5 m height above the benthos. Horizontal distance between photos was estimated by fin kicks, and corresponded to a surface distance of approximately 2.0 - 4.0 m. Approximation of coordinates of each benthic photo was done based on the photo timestamp and GPS coordinate time stamp, using GPS Photo Link Software (www.geospatialexperts.com). Coordinates of each photo were interpolated by finding the gps coordinates that were logged at a set time before and after the photo was captured. Dominant benthic or substrate cover type was assigned to each photo by placing 24 points random over each image using the Coral Point Count excel program (Kohler and Gill, 2006). Each point was then assigned a dominant cover type using a benthic cover type classification scheme containing nine first-level categories - seagrass high (>=70%), seagrass moderate (40-70%), seagrass low (<= 30%), coral, reef matrix, algae, rubble, rock and sand. Benthic cover composition summaries of each photo were generated automatically in CPCe. The resulting benthic cover data for each photo was linked to GPS coordinates, saved as an ArcMap point shapefile, and projected to Universal Transverse Mercator WGS84 Zone 56 South. The OBIA class assignment followed a hierarchical assignment based on membership rules with levels for "reef", "geomorphic zone" and "benthic community" (above).
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In contrast to numerous studies on the biomass of marine microphytobenthos from temperate coastal ecosystems, little is known from polar regions. Therefore, microphytobenthos biomass was measured at several coastal sites in Arctic Kongsfjorden (Spitsbergen) during the polar summer (June-August 2006). On sandy sediments, chla varied between 8 and 200 mg/m**2 and was related to water depth, current/wave exposure and geographical location. Biomass was rather independent of abiotic parameters such as sediment properties, salinity, temperature or light availability. At three stations, sediments at water depths of 3-4, 10, 15, 20 and 30 m were investigated to evaluate the effect of light availability on microalgae. Significant differences in distribution patterns of biomass in relation to deeper waters >10 m were found. The productive periods were not as distinct as phytoplankton blooms. Only at 3-4 m water depth at all three stations were two- to threefold increases of biomass measured during the investigation period. Hydrodynamic conditions seemed to be the driving force for differences in sediment colonisation by benthic microalgae. In spite of the extreme Arctic environmental conditions for algal growth, microphytobenthos biomass was comparable to marine temperate waters.