942 resultados para Species distribution modelling
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Mode of access: Internet.
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Mode of access: Internet.
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Indexed in Annual report for 1912, p. 148-164, 201-203.
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The morphology of the exine of Late Cretaceous and Tertiary specimens of Tricolpites reticulatus previously documented from Kerguelen, the Antarctic Peninsula, and the Otway Basin of southeastern Australia has been re-examined and compared with the three pollen types identified in the genus Gunnera. An Antarctic specimen of T reticulatus (Maastrichtian) has a uniform reticulum with elongated lumina, similar to that characterising pollen type 3a of Gunnera macrophylla (subgenus Pseudogunnera). Late Cretaceous (Maastrichtian) Australian specimens of T reticulatus differ; specimens from McNamara resemble pollen of subgenera Pseudogunnera and Milligania of type 3a or type 3b, while specimens of T reticulatus from Princes show more rounded and equidimensional lumina and are therefore tentatively attributed to pollen type 2 found in subgenera Gunnera, Misandra and Panke. Kerguelen Island T reticulatus (Miocene) are distinct from Vega Island specimens: a closer resemblance of Kerguelen T reticulatus and pollen type 2 of extant Gunnera is hypothesised. A comparison between specimens of the North American Tricolpites reticulatus/microreticulatus and pollen of Gunnera is also made. The clear similarity of the North American specimens of Tricolpites microreticulatus and pollen of Gunnera in shape and in the exine surface features of pollen suggests that this taxon should not be separated from T reticulatus but should be treated as a synonym of this species. (C) 2004 Elsevier B.V. All rights reserved.
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Modelling and optimization of the power draw of large SAG/AG mills is important due to the large power draw which modern mills require (5-10 MW). The cost of grinding is the single biggest cost within the entire process of mineral extraction. Traditionally, modelling of the mill power draw has been done using empirical models. Although these models are reliable, they cannot model mills and operating conditions which are not within the model database boundaries. Also, due to its static nature, the impact of the changing conditions within the mill on the power draw cannot be determined using such models. Despite advances in computing power, discrete element method (DEM) modelling of large mills with many thousands of particles could be a time consuming task. The speed of computation is determined principally by two parameters: number of particles involved and material properties. The computational time step is determined by the size of the smallest particle present in the model and material properties (stiffness). In the case of small particles, the computational time step will be short, whilst in the case of large particles; the computation time step will be larger. Hence, from the point of view of time required for modelling (which usually corresponds to time required for 3-4 mill revolutions), it will be advantageous that the smallest particles in the model are not unnecessarily too small. The objective of this work is to compare the net power draw of the mill whose charge is characterised by different size distributions, while preserving the constant mass of the charge and mill speed. (C) 2004 Elsevier Ltd. All rights reserved.
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Computer modelling promises to. be an important tool for analysing and predicting interactions between trees within mixed species forest plantations. This study explored the use of an individual-based mechanistic model as a predictive tool for designing mixed species plantations of Australian tropical trees. The 'spatially explicit individually based-forest simulator' (SeXI-FS) modelling system was used to describe the spatial interaction of individual tree crowns within a binary mixed-species experiment. The three-dimensional model was developed and verified with field data from three forest tree species grown in tropical Australia. The model predicted the interactions within monocultures and binary mixtures of Flindersia brayleyana, Eucalyptus pellita and Elaeocarpus grandis, accounting for an average of 42% of the growth variation exhibited by species in different treatments. The model requires only structural dimensions and shade tolerance as species parameters. By modelling interactions in existing tree mixtures, the model predicted both increases and reductions in the growth of mixtures (up to +/- 50% of stem volume at 7 years) compared to monocultures. This modelling approach may be useful for designing mixed tree plantations. (c) 2006 Published by Elsevier B.V.
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Traditional vegetation mapping methods use high cost, labour-intensive aerial photography interpretation. This approach can be subjective and is limited by factors such as the extent of remnant vegetation, and the differing scale and quality of aerial photography over time. An alternative approach is proposed which integrates a data model, a statistical model and an ecological model using sophisticated Geographic Information Systems (GIS) techniques and rule-based systems to support fine-scale vegetation community modelling. This approach is based on a more realistic representation of vegetation patterns with transitional gradients from one vegetation community to another. Arbitrary, though often unrealistic, sharp boundaries can be imposed on the model by the application of statistical methods. This GIS-integrated multivariate approach is applied to the problem of vegetation mapping in the complex vegetation communities of the Innisfail Lowlands in the Wet Tropics bioregion of Northeastern Australia. The paper presents the full cycle of this vegetation modelling approach including sampling sites, variable selection, model selection, model implementation, internal model assessment, model prediction assessments, models integration of discrete vegetation community models to generate a composite pre-clearing vegetation map, independent data set model validation and model prediction's scale assessments. An accurate pre-clearing vegetation map of the Innisfail Lowlands was generated (0.83r(2)) through GIS integration of 28 separate statistical models. This modelling approach has good potential for wider application, including provision of. vital information for conservation planning and management; a scientific basis for rehabilitation of disturbed and cleared areas; a viable method for the production of adequate vegetation maps for conservation and forestry planning of poorly-studied areas. (c) 2006 Elsevier B.V. All rights reserved.
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Wet woodlands have been recognised as a priority habitat and have featured in the UK BAP since 1994. Although this has been acknowledged in a number of UK policies and guidelines, there is little information relating to their detailed ecology and management. This research, focusing on lowland Alnus glutinosa woodlands, aimed to address this data paucity through the analysis of species requirements and to develop a methodology to guide appropriate management for this habitat for the benefit of wildlife. To achieve these aims data were collected from 64 lowland Alnus glutinosa woodlands and a review of the literature was undertaken to identify species associated with the target habitat. The groundflora species found to be associated with lowland Alnus glutinosa woodland were assessed in relation to their optimal environmental conditions (Ellenberg indicator values) and survival strategies (Grime CSR-Strategy) to determine the characteristics (Characters of a Habitat; CoaHs) and range of intra-site conditions (Niches of a Habitat; NoaH). The methodologies, using CSR and Ellenberg indicator values in combination, were developed to determine NoaHs and were tested both quantitatively and qualitatively at different lowland Alnus glutinosa sites. The existence of CoaHs and NoaHs in actual sites was verified by detailed quadrat data gathered at three Alnus glutinosa woodlands at Stonebridge Meadows, Warwickshire, UK and analysed using TWINSPAN and DCA ordination. The CoaHs and NoaHs and their component species were confirmed to have the potential to occur in a particular woodland. Following a literature search relating to the management of small wet woodlands within the UK, in conjunction with the current research, broad principles and strategies were identified for the management of lowland Alnus glutinosa woodland. Using the groundflora composition, an innovative procedure is developed and described for identifying the potential variation within a particular site and determining its appropriate management. Case studies were undertaken on distinct woodlands and the methodology proved effective.
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Dynamic asset rating is one of a number of techniques that could be used to facilitate low carbon electricity network operation. This paper focusses on distribution level transformer dynamic rating under this context. The models available for use with dynamic asset rating are discussed and compared using measured load and weather conditions from a trial Network area within Milton Keynes. The paper then uses the most appropriate model to investigate, through simulation, the potential gains in dynamic rating compared to static rating under two transformer cooling methods to understand the potential gain to the Network Operator.
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Climate change is one of the most crucial ecological problems of our age with great influence. Seasonal dynamics of aquatic communities are — among others — regulated by the climate, especially by temperature. In this case study we attempted the simulation modelling of the seasonal dynamics of a copepod species, Cyclops vicinus, which ranks among the zooplankton community, based on a quantitative database containing ten years of data from the Danube’s Göd area. We set up a simulation model predicting the abundance of Cyclops vicinus by considering only temperature as it affects the abundance of population. The model was adapted to eight years of daily temperature data observed between 1981 and 1994 and was tested successfully with the additional data of two further years. The model was run with the data series of climate change scenarios specified for the period around 2070- 2100. On the other hand we looked for the geographically analogous areas with the Göd region which are mostly similar to the future climate of the Göd area. By means of the above-mentioned points we can get a view how the climate of the region will change by the end of the 21st century, and the way the seasonal dynamics of a chosen planktonic crustacean species may follow this change. According to our results the area of Göd will be similar to the northern region of Greece. The maximum abundance of the examined species occurs a month to one and a half months earlier, moreover larger variances are expected between years in respect of the abundance. The deviations are expected in the direction of smaller or significantly larger abundance not observed earlier.
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Our study intended to explore the potential distributionshif of Phlebotomusariasi, P. neglectus, P. perfiliewi, P. perniciosus, and P. tobbi, and some other sandfly species: P. papatasi, P. sergenti, and P. similis. We used climate envelope modeling (CEM) method to determine the ecological requirements of the species and to model the potential distribution for three periods (1961-1990, 2011-2040, and 2041- 2070). We found that by the end of the 2060’s the Southern UK, Germany, entire France and also the western part of Poland can be colonized by sandfly species, mostly by P. ariasi and P. pernicosus. P. ariasishowe the greatest potential northward expansion, from 49°N to 59°N. For all of the studied sand fly species the entire Mediterranean Basin, the Balkan Peninsula, the Carpathian Basin, and northern coastline of the Black Sea are potentially suitable. The length of the predicted active period of the vectors will increase with one or two months.
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Climate change has serious effects on the setting up and the operation of natural ecosystems. Small increase in temperature could cause rise in the amount of some species or potential disappearance of others. During our researches, the dispersion of the species and biomass production of a theoretical ecosystem were examined on the effect of the temperature–climate change. The answers of the ecosystems which are given to the climate change could be described by means of global climate modelling and dynamic vegetation models. The examination of the operation of the ecosystems is only possible in huge centres on supercomputers because of the number and the complexity of the calculation. The number of the calculation could be decreased to the level of a PC by considering the temperature and the reproduction during modelling a theoretical ecosystem, and several important theoretical questions could be answered.
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The potential future distribution of four Mediterranean pines was aimed to be modeled supported by EUFORGEN digital area database (distribution maps), ESRI ArcGIS 10 software’s Spatial Analyst module (modeling environment), PAST (calibration of the model with statistical method), and REMO regional climate model (climatic data). The studied species were Pinus brutia, Pinus halepensis, Pinus pinaster, and Pinus pinea. The climate data were available in a 25 km resolution grid for the reference period (1961-90) and two future periods (2011-40, 2041-70). The climate model was based on the IPCC SRES A1B scenario. The model results show explicit shift of the distributions to the north in case of three of the four studied species. The future (2041-70) climate of Western Hungary seems to be suitable for Pinus pinaster.
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The Standard Cosmological Model is generally accepted by the scientific community, there are still an amount of unresolved issues. From the observable characteristics of the structures in the Universe,it should be possible to impose constraints on the cosmological parameters. Cosmic Voids (CV) are a major component of the LSS and have been shown to possess great potential for constraining DE and testing theories of gravity. But a gap between CV observations and theory still persists. A theoretical model for void statistical distribution as a function of size exists (SvdW) However, the SvdW model has been unsuccesful in reproducing the results obtained from cosmological simulations. This undermines the possibility of using voids as cosmological probes. The goal of our thesis work is to cover the gap between theoretical predictions and measured distributions of cosmic voids. We develop an algorithm to identify voids in simulations,consistently with theory. We inspecting the possibilities offered by a recently proposed refinement of the SvdW (the Vdn model, Jennings et al., 2013). Comparing void catalogues to theory, we validate the Vdn model, finding that it is reliable over a large range of radii, at all the redshifts considered and for all the cosmological models inspected. We have then searched for a size function model for voids identified in a distribution of biased tracers. We find that, naively applying the same procedure used for the unbiased tracers to a halo mock distribution does not provide success- full results, suggesting that the Vdn model requires to be reconsidered when dealing with biased samples. Thus, we test two alternative exten- sions of the model and find that two scaling relations exist: both the Dark Matter void radii and the underlying Dark Matter density contrast scale with the halo-defined void radii. We use these findings to develop a semi-analytical model which gives promising results.