3 resultados para STRUCTURAL EQUATION MODELLING
em Publishing Network for Geoscientific
Resumo:
It is well known that ocean acidification can have profound impacts on marine organisms. However, we know little about the direct and indirect effects of ocean acidification and also how these effects interact with other features of environmental change such as warming and declining consumer pressure. In this study, we tested whether the presence of consumers (invertebrate mesograzers) influenced the interactive effects of ocean acidification and warming on benthic microalgae in a seagrass community mesocosm experiment. Net effects of acidification and warming on benthic microalgal biomass and production, as assessed by analysis of variance, were relatively weak regardless of grazer presence. However, partitioning these net effects into direct and indirect effects using structural equation modeling revealed several strong relationships. In the absence of grazers, benthic microalgae were negatively and indirectly affected by sediment-associated microalgal grazers and macroalgal shading, but directly and positively affected by acidification and warming. Combining indirect and direct effects yielded no or weak net effects. In the presence of grazers, almost all direct and indirect climate effects were nonsignificant. Our analyses highlight that (i) indirect effects of climate change may be at least as strong as direct effects, (ii) grazers are crucial in mediating these effects, and (iii) effects of ocean acidification may be apparent only through indirect effects and in combination with other variables (e.g., warming). These findings highlight the importance of experimental designs and statistical analyses that allow us to separate and quantify the direct and indirect effects of multiple climate variables on natural communities.
Resumo:
Measurements of tree heights and crown sizes are essential in long-term monitoring of spatially distributed forests to assess the health of forests over time. In Switzerland, in 1994 and 1997, more than 4'500 trees have been recorded in a 8x8 km plot within the Sanasilva Inventory, which comprises the Swiss Level I sites of the International Co-operative Programme on Assessment and Monitoring of Air Pollution Effects on Forests' (ICP Forests). Tree heights and crown sizes were measured for the dominant and co-dominant trees (n = 1,723), resulting in a data set from 171 plots in Switzerland, spreading over a broad range of climatic gradient and forest characteristics (species recorded = 20). Average tree height was 22.1 m, average DBH 34.6 cm and crown diameter 6.5 m. The data set presented here is open to use and shall foster research in allometric equation modelling.
Resumo:
The "Hydroblack91" dataset is based on samples collected in the summer of 1991 and covers part of North-Western in front of Romanian coast and Western Black Sea (Bulgarian coasts) (between 43°30' - 42°10' N latitude and 28°40'- 31°45' E longitude). Mesozooplankton sampling was undertaken at 20 stations. The whole dataset is composed of 72 samples with data of zooplankton species composition, abundance and biomass. Samples were collected in discrete layers 0-10, 0-20, 0-50, 10-25, 25-50, 50-100 and from bottom up to the surface at depths depending on water column stratification and the thermocline depth. Zooplankton samples were collected with vertical closing Juday net,diameter - 36cm, mesh size 150 µm. Tows were performed from surface down to bottom meters depths in discrete layers. Samples were preserved by a 4% formaldehyde sea water buffered solution. Sampling volume was estimated by multiplying the mouth area with the wire length. Mesozooplankton abundance: The collected materia was analysed using the method of Domov (1959). Samples were brought to volume of 25-30 ml depending upon zooplankton density and mixed intensively until all organisms were distributed randomly in the sample volume. After that 5 ml of sample was taken and poured in the counting chamber which is a rectangle form for taxomomic identification and count. Large (> 1 mm body length) and not abundant species were calculated in whole sample. Counting and measuring of organisms were made in the Dimov chamber under the stereomicroscope to the lowest taxon possible. Taxonomic identification was done at the Institute of Oceanology by Asen Konsulov using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972). The biomass was estimated as wet weight by Petipa, 1959 (based on species specific wet weight). Wet weight values were transformed to dry weight using the equation DW=0.16*WW as suggested by Vinogradov & Shushkina, 1987. Taxon-specific abundance: The collected material was analysed using the method of Domov (1959). Samples were brought to volume of 25-30 ml depending upon zooplankton density and mixed intensively until all organisms were distributed randomly in the sample volume. After that 5 ml of sample was taken and poured in the counting chamber which is a rectangle form for taxomomic identification and count. Copepods and Cladoceras were identified and enumerated; the other mesozooplankters were identified and enumerated at higher taxonomic level (commonly named as mesozooplankton groups). Large (> 1 mm body length) and not abundant species were calculated in whole sample. Counting and measuring of organisms were made in the Dimov chamber under the stereomicroscope to the lowest taxon possible. Taxonomic identification was done at the Institute of Oceanology by Asen Konsulov using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972). The biomass was estimated as wet weight by Petipa, 1959 ussing standard average weight of each species in mg/m3. WW were converted to DW by equation DW=0.16*WW (Vinogradov ME, Sushkina EA, 1987).