Depth-stratified density estimates and distribution of the Cape hake Merluccius capensis and M. paradoxus off Namibia deduced from survey data, 1990–1999

In this study demersal survey data for the period 1990–1999 are used to investigate the average distribution of the Cape hake Merluccius capensis and M. paradoxus off Namibia in terms of density and mean length. Further, biomass estimates are compared on the basis of depth and density stratification. The main distribution of M. capensis was north of 27°S and that of M. paradoxus south of 24°S. M. paradoxus was deeper than M. capensis. For both species, average length increased with depth. M. paradoxus expanded its range to the north through the 1990s as its population size (off South Africa and Namibia) increased. In Namibian waters, small M. paradoxus were found only south of 25°S. Mean length of M. capensis increased north of 21°S, largely as a result of decreased numbers of small fish in shallower water. Abundance estimates stratified by depth were no different from those post-stratified on similar densities.     

The Exploratory Essays Initiative: Background and Overview

We define as Positional Accuracy Improvement the problem of putting together maps A and B of the same area, with B of higher planimetric accuracy. To do so, all objects in A might have to be slightly moved according to a mathematical transformation. Such transformation might ideally be of a specific type, like analytical or conformal functions. We have developed a theory to find a suitable analytical transformation despite it is not well defined because the only data available is the displacement vectors at a limited number of homologue control points. There exists a similar problem in fluid mechanics devoted on estimating the complete velocity field given just values at a limited number of points. We borrowed some ideas from there and introduced them into the positional accuracy improvement problem. We shall demonstrate that it is possible to numerically estimate an analytic function that resembles the given displacement at control points. As a byproduct, an uncertainty estimation is produced, which might help to detect regions of different lineage. The theory has been applied to rural 1:50.000 cartography of Uruguay while trying to diminish the discrepancies against GNSS readings. After the analytic transformation, the RMSE error diminished from 116 m to 48 m. Other problems with similar math requirements are the transformation between geodetic control networks.     

Using Semi-variance Image Texture Statistics to Model Population Densities

This study presents a method to model population densities by using image texture statistics of semi-variance. In a case study of the City of Austin, Texas, we first selected sample census blocks of the same land use to build population models by land use. Regression analyses were conducted to infer the relationship between block population densities and image texture statistics of the semi-variance. We then applied the population models to an area of 251 blocks to estimate populations for within-blocks land-use areas while maintaining census block populations. To assess the proposed method, the same analysis was performed while census block-group populations were maintained, and the aggregated block populations were compared with original census block populations. We also tested a conventional land-use-based dasymetric mapping method with pre-calculated population densities for land uses. The results show that our approach, which is based on initial land-use stratification and further image-texture statistical modeling of population, has higher accuracy statistics than the conventional land-use-based dasymetric mapping method.     

An Automated Method of Scale Selection and Sheet Configuration for Multiple Sheet Census Maps with Insets

In order to create a useful map, the cartographer must select a scale at which the map reader can distinguish features shown on the map and read their labels. However, the choice of scale for a paper map is also constrained by the size of the map sheet and by the cost of working with a large number of sheets. When the feature density pattern allows, space can be conserved by making the map at more than one scale: a small scale suitable for most of the map, while dense features are shown on inset maps at larger scales. Creating inset maps requires the cartographer to make a series of complex, interrelated decisions regarding the most effective overall sheet configuration, which is dependent upon the scale chosen for the main map and how the inset maps are created. The Census Automated Map Production System (CAMPS) applies cartographic logic and density analysis to make these decisions in a fully automated mapping environment.     

Accumulation of Thematic Map Errors in Digital Overlay Analysis

The storage of digital resource information as geographically referenced data layers in computerized database systems has given managers access to a large variety of data that contribute to cost-effective management decisions. However, users of this information should be aware of potential shortcomings in using database techniques such as overlay analysis. Using fundamental concepts of conditional probability theory, the results of this investigation suggest that the accuracy of the map resulting from overlay analysis is determined by: 1) the number of map layers in the data, 2) the accuracy of these map layers, and 3) the coincidence of errors at the same position from several map layers. A method of calculating the upper and lower accuracy bounds of a composite overlay map is presented.     

Pigment signatures of phytoplankton composition in the northern Benguela ecosystem during spring

Pigment indices were used to investigate the distribution and composition of phytoplankton in the northern Benguela during the austral spring of 2000, with sampling being conducted on five transect lines between 19°S and 25°S and at other inshore stations on the shelf. Total chlorophyll a concentrations (TChla) at the surface ranged from 18.4mg m^?3 at shallow inshore stations to 0.58mg ^m?3 at offshore localities in deeper water. Phytoplankton communities in the inshore environment were characterised by elevated biomass levels and the dominance of diatoms (high Fuc_DP indices). These diatom populations were associated with cool, higher density, nutrient-rich waters near the coast. Phytoplankton biomass declined with increasing distance offshore and the communities changed to a mixed population where small flagellates were generally dominant (high Flag_DP indices). These flagellate communities were associated with warmer, lower density waters. Whereas dinoflagellates (Per_DP Index) and prokaryotes (Zea_DP Index) were observed throughout the region, their contribution to the communities was of secondary importance.     

Visualizing Distributions from Multi-Return Lidar Data to Understand Forest Structure

Abstract

Spatially distributed probability density functions (pdfs) are becoming more relevant to Earth scientists and ecologists because of stochastic models and new sensors that provide numerous realizations or data points per unit area. One source of these data is from multi-return airborne lidar, a type of laser that records multiple returns for each pulse of light sent towards the ground. Data from multi-return lidar is a vital tool in helping us understand the structure of forest canopies over large extents. This paper presents visualization tools to allow scientists to rapidly explore, interpret and discover characteristic distributions within the entire spatial field. The major contribution of this work is a paradigm shift which allows ecologists to think of and analyse their data in terms of full distributions, not just summary statistics. The tools allow scientists to depart from traditional parametric statistical analyses and to associate multimodal distribution characteristics to forest structures. Information on the modality and shape of distributions, previously ignored, can now be visualized as well. Examples are given using data from High Island, southeast Alaska.     

Landscape Controls over Major Nutrients and Primary Productivity of Arctic Lakes

Increasing surface temperatures in the Arctic are affecting the dynamics between lakes and their landscapes. In this paper, we use landscape metrics for land cover and statistical analysis to explore the interactions between such measures as shape and patch density indices for land cover and lake primary productivity. The objective was to identify metrics that could be used to predict lake primary productivity, as measured by chlorophyll a, total nitrogen and total phosphorus estimates. Land cover and landscape metrics for the Toolik region of Alaska were derived using satellite imagery and Fragstats software. The metrics, treated as independent variables in a stepwise regression, were derived for two levels of land cover. The first comprised the entire watershed studied; the second was derived using buffers created around water channels within each watershed. A statistically significant model for each dependent variable was obtained. Results suggest that, of the metrics tested; those related to broad leaf vegetation complexes were most useful in predicting lake primary productivity. The Landscape Shape Index for riparian patches and the Patch Density for heath complex were the two most important metrics for predicting variation in chlorophyll a (p<0.001, r² = 0.52). For total nitrogen estimates, the most significant metrics were Percentage of riparian complex and Patch Density for fen complex (p<0.001, r² = 0.48). Total phosphorus estimates were most influenced by the Patch Density for shrub complex, the Mean Shape Index for moist acidic tundra complex, and the Patch Density for aquatic vegetation (p<0.001, r² = 0.52).     

Nest Densities of the Wandering Albatross Diomedea Exulans at the Prince Edward Islands,Estimated Using Gps

Hand-held Global Positioning System (GPS) receivers provide opportunities for detailed and rapid mapping of features, including biological ones, further enhanced by the removal during 2000 of "selective availability". GPS was used to map, describe and compare nest densities within wandering albatross Diomedea exulans colonies at subantarctic Marion and Prince Edward islands. On Prince Edward Island, the coordinates of 1 061 wandering albatross nests were determined and, on Marion Island, 1 779 nests. For describing nest densities of wandering albatrosses, a 50-m grid is recommended, at which scale, the densest area of Prince Edward Island was in Albatross Valley, where the area of the colony was 46 ha and nest density was 22.3 nests ha^?1. For Marion Island, the total area of the wandering albatross colonies was 306 ha and the nest density was 5.8 nests ha^?1. In the three study colonies there (Macaroni Bay, 28 nests; Sealer's Beach, 117 nests; Goney Plain, 140 nests), the density statistics did not differ greatly from the overall densities on the island, with overall mean densities of 4.9, 5.7 and 8.0 birds ha^?1 respectively. Although comparisons with nest densities at other breeding colonies are uncertain because of differing methods of computing them, the nest densities in Albatross Valley lie within the reported ranges for other colonies of great albatrosses.     

Biochemical genetic variation in the Cape anchovy Engraulis capensis Gilchrist

The extent of biochemical genetic variation in the Cape anchovy Engraulis capensis was estimated from starch-gel protein electrophoresis. The gene products of 31 protein-coding loci were identified and Mendelian polymorphisms were observed at 21 (68 per cent). Ten of these loci (32 per cent) had common-allele frequencies less than 0,95 and hence were useful for testing hypotheses of geographic stock structure. The average population heterozygosity, a measure of genetic variation, ranged from 0,110 to 0,128 and averaged 0,115 over samples from 31 locations. Cape anchovies and other clupeiform fishes appear, on average, to have higher levels of genetic variation than many other marine fishes. This may result from the large population sizes and weak population subdivision that characterize them.