Trawl operations in the South East Fishery, Australia: spatial distribution and intensity

2001 ◽  
Vol 52 (4) ◽  
pp. 419 ◽  
Author(s):  
James W. P. Larcombe ◽  
Kevin J. McLoughlin ◽  
Richard D. J. Tilzey
Keyword(s):  
Interannual Variation ◽  
Fine Scale ◽  
Scale Analysis ◽  
Coarse Scale ◽  
Depth Stratum ◽  
North East ◽  
Management Area ◽  
Catch Rates ◽  
High Effort ◽  
Total Effort

Trawl areas and intensities were mapped at coarse (22 km 1986–99)and fine (1 km 1995–99)scales, and statistics reported by area and depth stratum. Total effort in hours was relatively stable to 1992, then increased substantially to 1999. The total distance trawled from fine-scale analysis showed a similar trend for the 1995–99 period. Coarse-scale analysis from 1986–99 indicated effort increases in north-east Bass Strait in particular, and also off western Tasmania and west of Bass Strait. There was little change in the total area of the fishery from 1995 to 1999, but grid cells on the periphery showed considerable interannual variation in the presence or absence of fishing. Increased or redistributed effort tended to further concentrate in the relatively small high-effort areas, rather than increasing equally across the grounds, or spreading to new grounds. In the total management area, a small proportion of the 1 km grids was fished. However, in 200–1000 m depth strata, ≥50%of the grids were fished with some intensity. The consequences and compromises of spatial scale are discussed in terms of data quality, the use of trawl effort as a surrogate for marine disturbance, and the interpretation of catch rates.

scholarly journals Spatial Downscaling of TRMM Precipitation Using Geostatistics and Fine Scale Environmental Variables

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
No-Wook Park
Keyword(s):  
Environmental Variables ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Tropical Rainfall Measuring Mission ◽  
Predictive Performance ◽  
Environmental Modeling ◽  
Fine Scale ◽  
Coarse Scale ◽  
Uncertainty Measures ◽  
Trmm Precipitation

A geostatistical downscaling scheme is presented and can generate fine scale precipitation information from coarse scale Tropical Rainfall Measuring Mission (TRMM) data by incorporating auxiliary fine scale environmental variables. Within the geostatistical framework, the TRMM precipitation data are first decomposed into trend and residual components. Quantitative relationships between coarse scale TRMM data and environmental variables are then estimated via regression analysis and used to derive trend components at a fine scale. Next, the residual components, which are the differences between the trend components and the original TRMM data, are then downscaled at a target fine scale via area-to-point kriging. The trend and residual components are finally added to generate fine scale precipitation estimates. Stochastic simulation is also applied to the residual components in order to generate multiple alternative realizations and to compute uncertainty measures. From an experiment using a digital elevation model (DEM) and normalized difference vegetation index (NDVI), the geostatistical downscaling scheme generated the downscaling results that reflected detailed characteristics with better predictive performance, when compared with downscaling without the environmental variables. Multiple realizations and uncertainty measures from simulation also provided useful information for interpretations and further environmental modeling.

scholarly journals Fine scale analysis of shifts in bacterial community structure in the chemocline of meromictic Lake Cadagno, Switzerland

2009 ◽  
Vol 68 (1) ◽  
pp. 16 ◽  
Author(s):  
Paola M.A. DECRISTOPHORIS ◽  
Sandro PEDUZZI ◽  
Nadia RUGGERI-BERNARDI ◽  
Dittmar HAHN ◽  
Mauro TONOLLA
Keyword(s):  
Community Structure ◽  
Bacterial Community ◽  
Bacterial Community Structure ◽  
Meromictic Lake ◽  
Fine Scale ◽  
Scale Analysis

Numerical Calculation of Equivalent Permeability Tensor for Fractured Vuggy Porous Media Based on Homogenization Theory

2011 ◽  
Vol 9 (1) ◽  
pp. 180-204 ◽  
Author(s):  
Zhaoqin Huang ◽  
Jun Yao ◽  
Yajun Li ◽  
Chenchen Wang ◽  
Xinrui Lv
Keyword(s):  
Porous Media ◽  
Network Model ◽  
Darcy's Law ◽  
Permeability Tensor ◽  
Homogenization Theory ◽  
Fine Scale ◽  
Porous Rock ◽  
Coarse Scale ◽  
Equivalent Permeability ◽  
Discrete Fracture

AbstractA numerical procedure for the evaluation of equivalent permeability tensor for fractured vuggy porous media is presented. At first we proposed a new conceptual model, i.e., discrete fracture-vug network model, to model the realistic fluid flow in fractured vuggy porous medium on fine scale. This new model consists of three systems: rock matrix system, fractures system, and vugs system. The fractures and vugs are embedded in porous rock, and the isolated vugs could be connected via discrete fracture network. The flow in porous rock and fractures follows Darcy’s law, and the vugs system is free fluid region. Based on two-scale homogenization theory, we obtained an equivalent macroscopic Darcy’s law on coarse scale from fine-scale discrete fracture-vug network model. A finite element numerical formulation for homogenization equations is developed. The method is verified through application to a periodic model problem and then is applied to the calculation of equivalent permeability tensor of porous media with complex fracture-vug networks. The applicability and validity of the method for these more general fractured vuggy systems are assessed through a simple test of the coarse-scale model.

Survival analysis at multiple scales for the modeling of track geometry deterioration

2017 ◽  
Vol 232 (3) ◽  
pp. 842-850 ◽  
Author(s):  
Negin Alemazkoor ◽  
Conrad J Ruppert ◽  
Hadi Meidani
Keyword(s):  
Survival Analysis ◽  
Multiple Scales ◽  
Fine Scale ◽  
Coarse Scale ◽  
Track Geometry ◽  
Time Period ◽  
Scale Models ◽  
Optimal Maintenance ◽  
Maintenance Decisions

Defects in track geometry have a notable impact on the safety of rail transportation. In order to make the optimal maintenance decisions to ensure the safety and efficiency of railroads, it is necessary to analyze the track geometry defects and develop reliable defect deterioration models. In general, standard deterioration models are typically developed for a segment of track. As a result, these coarse-scale deterioration models may fail to predict whether the isolated defects in a segment will exceed the safety limits after a given time period or not. In this paper, survival analysis is used to model the probability of exceeding the safety limits of the isolated defects. These fine-scale models are then used to calculate the probability of whether each segment of the track will require maintenance after a given time period. The model validation results show that the prediction quality of the coarse-scale segment-based models can be improved by exploiting information from the fine-scale defect-based deterioration models.

A MULTI-SCALE NONEQUILIBRIUM MOLECULAR DYNAMICS ALGORITHM AND ITS APPLICATIONS

2009 ◽  
Vol 01 (03) ◽  
pp. 405-420 ◽  
Author(s):  
NI SHENG ◽  
SHAOFAN LI
Keyword(s):  
Molecular Dynamics ◽  
Local Equilibrium ◽  
Random Force ◽  
Coarse Grained ◽  
Nonequilibrium Molecular Dynamics ◽  
Fine Scale ◽  
Coarse Scale ◽  
Fe Method ◽  
Time Step ◽  
Multi Scale

In this paper, we introduce a multi-scale nonequilibrium molecular dynamics (MS-NEMD) model that is capable of simulating nano-scale thermal–mechanical interactions. Recent simulation results using the MS-NEMD model are presented. The MS-NEMD simulation generalises the nonequilibrium molecular dynamics (NEMD) simulation to the setting of concurrent multi-scale simulation. This multi-scale framework is based on a novel concept of multi-scale canonical ensemble. Under this concept, each coarse scale finite element (FE) node acts as a thermostat, while the atoms associated with each node are assumed to be in a local equilibrium state within one coarse scale time step. The coarse scale mean field is solved by the FE method based on a coarse-grained thermodynamics model; whereas in the fine scale the NEMD simulation is driven by the random force that is regulated by the inhomogeneous continuum filed through a distributed Nośe–Hoover thermostat network. It is shown that the fine scale distribution function is canonical in the sense that it obeys a drifted local Boltzmann distribution.

Adequacies and deficiencies of alpine and subalpine treeline studies in the national parks of the western USA

2010 ◽  
Vol 35 (1) ◽  
pp. 19-42 ◽  
Author(s):  
Clayton J. Whitesides ◽  
David R. Butler
Keyword(s):  
Climate Change ◽  
Content Analysis ◽  
National Parks ◽  
Fine Scale ◽  
Scale Analysis ◽  
The West ◽  
Western Usa ◽  
Alpine Treeline ◽  
The Impact ◽  
Geomorphic Processes

To mitigate the impact of direct human activity on treeline pattern and process, much alpine treeline research in the western USA has been conducted in nationally protected areas. The use of treeline as a proxy for climate change has been assessed in parks throughout the west but often at the expense of geology or geomorphology as controls of treeline variation. The dissimilar geology and geomorphic processes of the western national parks suggest that treeline may respond differently between national parks when subjected to disturbance. Therefore, predicted vegetation response to disturbance across the western USA may provide a limited assessment of change beyond fine-scale analysis due to data collection from a limited number of national parks containing alpine treeline. We performed a content analysis on previous research that examined alpine treeline in national parks and classified each treeline study as anthropogenic, orographic/edaphic, or climatic according to the primary factor attributed to treeline control. Results indicated that the three types of treeline are not uniformly studied. Climatic treeline is most commonly studied whereas anthropogenic and orographic/edaphic studies are often lacking. Furthermore, several western national parks are entirely devoid of anthropogenic and orographic treeline research. Similar findings exist for treeline studies in protected places worldwide. More research in protected places is required to broaden our understanding of multiple treeline processes across both regional and worldwide extents.

Machine learning for cross-scale geomorphometric classification of landforms: a day at the beach

2018 ◽  
Author(s):  
Ashton Shortridge ◽  
Clayton Queen ◽  
Alan Arbogast
Keyword(s):  
Machine Learning ◽  
Random Forests ◽  
Classification Accuracy ◽  
Spatial Prediction ◽  
Coastal Dune ◽  
Fine Scale ◽  
Coarse Scale ◽  
Sample Points

This paper investigates the use of random forests and spatial random forests (RFsp) for the classification of coastal dune areas along 41km of Lake Michigan’s shoreline using a lidar- derived DEM. Terrain variables across a range of spatial neighborhood scales are utilized, and for two different cell resolutions. Distance is explicitly incorporated into the RFsp models through the calculation of buffer distances around small numbers (6-13) of gridded points in the study area. While classification accuracy is high generally, RFsp produced much more accurate results. At the fine scale, topographic variables and their neighborhood ranges were not predictive of dune areas, perhaps because large (> 0.1 hectare) neighborhoods were not tested at that scale. At the coarse scale these variables were much more important. The use of small numbers of gridded (non-sample) points to improve spatial prediction warrants further investigation.

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