Abrupt environmental shift associated with changes in the distribution of Cape anchovy Engraulis encrasicolus spawners in the southern Benguela

Cape anchovy Engraulis encrasicolus spawners in the southern Benguela showed an eastward shift in their distribution on the Agulhas Bank that occurred abruptly in 1996 and has since persisted. We assessed whether this shift was environmentally mediated by examining sea surface temperature data from different regions of the Agulhas Bank, which showed that in 1996 the inner shelf of the Agulhas Bank to the east of Cape Agulhas abruptly became 0.5°C colder than in previous years and has since remained that way. In addition, signals, coherent with the 1996 shift recorded in sea surface temperatures, were also found in atmospheric surface pressure and zonal wind data for that region; interannual coastal SST variability is also shown to be correlated with zonal wind-stress forcing. As a result, increased wind-induced coastal upwelling east of Cape Agulhas is proposed as the main driver of the observed cooling in the coastal region. The synchrony between the environmental and biological signals suggests that the eastward shift in anchovy spawner distribution was environmentally mediated and arose from a change in environmental forcing that altered the relative favourability for spawning between regions to the west and east of Cape Agulhas. The results highlight how a relatively minor change in environmental conditions can lead to a drastic spatial reorganisation of the life history of one species in an ecosystem.     

Bicomponent Trend Maps: A Multivariate Approach to Visualizing Geographic Time Series

The most straightforward approaches to temporal mapping cannot effectively illustrate all potentially significant aspects of spatio-temporal patterns across many regions and times. This paper introduces an alternative approach, bicomponent trend mapping, which employs a combination of principal component analysis and bivariate choropleth mapping to illustrate two distinct dimensions of long-term trend variations. The approach also employs a bicomponent trend matrix, a graphic that illustrates an array of typical trend types corresponding to different combinations of scores on two principal components. This matrix is useful not only as a legend for bicomponent trend maps but also as a general means of visualizing principal components. To demonstrate and assess the new approach, the paper focuses on the task of illustrating population trends from 1950 to 2000 in census tracts throughout major U.S. urban cores. In a single static display, bicomponent trend mapping is not able to depict as wide a variety of trend properties as some other multivariate mapping approaches, but it can make relationships among trend classes easier to interpret, and it offers some unique flexibility in classification that could be particularly useful in an interactive data exploration environment.     

Toward a Differential Calculus for Temporal Map Analysis

Investigators in many fields are analyzing temporal change in spatial data. Such analyses are typically conducted by comparing the value of some metric (e. g., area, contagion, or diversity indices) measured at time T₁ with the value of the same metric measured at time T₂ . These comparisons typically include the use of simple interpolation models to estimate the value of the metric of interest at points in time between observations, followed by applications of differential calculus to investigate the rates at which the metric is changing. Unfortunately, these techniques treat the values of the metrics being analyzed as if they were observed values, when in fact the metrics are derived from more fundamental spatial data. The consequence of treating metrics as observed values is a significant reduction in the degrees of freedom in spatial change over time. This results in an oversimplified view of spatio-temporal change. A more accurate view can be produced by (1) applying temporal interpolation models to observed spatial data rather than derived spatial metrics; (2) expanding the metric of interest's computational equation by replacing the terms relating to the observed spatial data with their temporal interpolation equations; and (3) differentiating the expanded computational equation. This alternative, three-step spatio-temporal analysis technique will be described and justified. The alternative technique will be compared to the conventional approach using common metrics and a sample data set.     

The Impact of Hurricanes on Crime: A Spatio-Temporal Analysis in the City of Houston,Texas

The impact that natural disasters have on crime is not well understood. In general, it is assumed that crime declines shortly after the disaster and slowly increases to pre-disaster levels over time. However, this assumption is not always confirmed by the few empirical studies that have been conducted to date. In this paper we analyze the impacts that Hurricane Rita, and for the purpose of comparison, Hurricane Katrina had on the temporal and spatial distributions of reported crimes in the city of Houston, TX. Crime data were collected before, during, and after the landfall of both hurricanes. The modeling part of this paper focused on primarily spatio-temporal and local regression models at the local scale. Spatio-temporal models were applied to identify potential spatio-temporal crime clusters associated with the hurricanes. A local regression model in the form of a geographically weighted regression was applied to explore relationships between crime clusters and possible underlying factors leading to the creation of said clusters.

The results show that while Hurricane Katrina did not have any apparent impact on crime, Hurricane Rita led to a significant short-term increase in burglaries and auto thefts. The post important result was the identification of a large, highly significant spatio-temporal burglary cluster located in the northeastern part of Houston. This cluster lasted from a few days before to a few days after the landfall of Hurricane Rita. Empirical evidence was found that the mandatory evacuation order that was issued prior to the arrival of Hurricane Rita led to a short-time spike in burglaries. It was assumed that these crimes were committed by individuals who did not follow the evacuation order, but instead burglarized the residences of individuals who did evacuate. No mandatory evacuation order was issued for Hurricane Katrina. Altogether, three variables including the percentage of African Americans, the percentage of persons living below the poverty level, and the distance to the nearest police station was identified as having a positive relationship with the increase in burglaries associated with Hurricane Rita     

Impact and implications of large-scale environmental anomalies on the spatial distribution of spawning of the Namibian pilchard and anchovy populations

Trends in the spatial pattern of spawning of pilchard Sardinops ocellatus and anchovy Engraulis capensis during the period 1971–1985 were examined in relation to large-scale environmental anomalies outside the spawning area. Shifts in the locality of peak spawning of anchovy often coincided with that of pilchard, although sometimes anchovy were slower to respond to an environmental change. With negative sea surface temperature (SST) anomalies spawning shifted northwards, whereas with positive anomalies spawning took place both in the north and farther south. With a transition from negative SST anomalies early in the spawning season to zero or positive anomalies later in the spawning season, the impact on anchovy and pilchard spawning differed. Anchovy spawning was either reduced or absent during the negative phase of transitional seasons, thus avoiding unfavourable conditions. Pilchard, on the other hand, were spawning mainly in the north during the negative phase of the transitional seasons, but also in the south during the zero to positive phase. The shifts in spawning locality in response to environmental anomalies outside the spawning area imply that explanations for such shifts need not be sought in changes in biomass or age structure or in the fact that stocks may be genetically different, all theories previously advanced.     

Collection of mussel worms Pseudonereis variegata for bait — a legislative anachronism

The extent of damage caused to mussel and tube-worm Gunnarea capensis beds by the collection of mussel worms Pseudonereis variegata for use as bait is assessed. Between 0,4 and 5,0 m² of mussel bed and 0,7 m² of tube-worm reef is destroyed in the collection of the legal limit of 20 mussel worms. Such destruction has implications for ecological succession and is at variance with legislative restrictions governing the collection of mussels.     

Modeling Dynamic Polygon Objects in Space and Time: A New Graph-based Technique

The analysis of dynamic spatial systems requires an explicit spatio-temporal data model and spatio-temporal analysis tools. Event-based models have been developed to analyze discrete change in continuous and feature-based spatial data. In this paper, a spatio-temporal graph model is described that supports the analysis of continuous change in feature-based polygon spatial data. The spatio-temporal graph edges, called temporal links, track changes in polygon topology through space and time. The model also introduces the concept of a spatial-interaction region that extends a model's focus beyond short-term local events to encompass long-term regional events. The structure of the spatio-temporal graph is used to classify these events into five types of local polygon events and two types of spatial-interaction region events. To illustrate its utility, the model is applied to the ecological question of how patch size influences longevity in underwater plant communities in Chesapeake Bay, USA. Both a short-term local analysis and a longer-term regional analysis showed that patches of plants, or groups of patches, larger than one to two hectares in size were more likely to persist than smaller patches or groups of patches. Overall, the spatio-temporal graph model approach appears applicable to a variety of spatio-temporal questions.     

Analyzing Cognitive Conceptualizations Using Interactive Visual Environments

The conceptualization of spatio-temporal information is an interdisciplinary research area. The focus of this article is on human conceptualizations of spatio-temporal geographic phenomena (also referred to as events). Identifying and understanding human conceptualizations is a crucial component in defining the semantics of spatio-temporal information. However, most research focuses primarily on how humans imbue dynamic phenomena with meaning on a general level. In contrast, this article is concerned with contextual factors (specifically: individual differences) that are too often neglected in general theories and in the analysis of behavioral data. In other words, we are interested in individual or group strategies of participants that are not detected by classical analysis methods. Research on individual difference is gaining widespread attention in cognitive and spatial sciences and it is time to consider individual differences in the area of conceptualizing spatio-temporal information. To understand individual differences in behavioral data on how people conceptualize events, we have developed illustrative software and have combined them with established similarity measures. We demonstrate the feasibility of our approach, its usefulness in analyzing behavioral data, and results that can be obtained through this individualized analysis by reanalyzing four sets of experimental data we previously collected.     

Mesoscale coupling between planktonic cnidarian distribution and water masses during a temporal transition between active upwelling and abatement in the northern Benguela system

The composition and spatio-temporal distribution of planktonic cnidarians in the northern Benguela system are described from plankton samples collected on four cruises between December 1981 and March 1982. The sampling period was characterized by initially active coastal upwelling, followed by abatement of upwelling. In all, 20 species of medusae and 24 species of siphonophores were identified. The most abundant medusae were Chrysaora hysoscella, Aequorea aequorea and Liriope tetraphylla, and the most abundant siphonophores were Muggiaea atlantica, Abylopsis tetragona and Bassia bassensis. Three assemblages of planktonic cnidarians were differentiated. The first was associated with coastal upwelling and consisted of the medusae Proboscidactyla menoni, Aglauropsis edwardsii and juvenile C. hysoscella, along with the siphonophore M. atlantica. The second assemblage was associated with oceanic water and the component species were indicative of the offshore influence of the Benguela system; L. tetraphylla and most of the siphonophores belonged to this assemblage. The third assemblage consisted of species typical of shelf fauna, namely A. aequorea, Mitrocomella grandis and adult C. hysoscella, all also typical of the northernmost waters of the Benguela system. Overall, there was coupling between mesoscale hydrographic features and the pattern of distribution of cnidarian populations, with a distinct cross-shelf gradient that was more pronounced during active upwelling.