The macroinvertebrate fauna of an Australian dryland river: spatial and temporal patterns and environmental relationships

2006 ◽  
Vol 57 (1) ◽  
pp. 61 ◽  
Author(s):  
Jonathan C. Marshall ◽  
Fran Sheldon ◽  
Martin Thoms ◽  
Satish Choy
Keyword(s):  
Spatial Patterns ◽  
Spatial Scales ◽  
Temporal Patterns ◽  
Environmental Aspects ◽  
Spatial And Temporal Patterns ◽  
Channel Network ◽  
Spatial Changes ◽  
Dryland River ◽  
Macroinvertebrate Fauna

Waterholes within the dryland Cooper Creek, Lake Eyre Basin, Australia, are connected only during floods and are typically isolated for long periods. Spatial changes in the macroinvertebrate assemblages of 15 of these waterholes belonging to four regions were explored and these changes were related to environmental aspects of the waterholes measured at four spatial scales: floodplain, waterhole, within waterhole and sample habitat. To explore temporal patterns, one region was sampled on four occasions differing in time since connection. Spatial patterns were characterised by ‘differentiation by distance’ whereby samples collected closer to each other in the landscape were more similar in assemblage composition than those collected further apart. Thus, there were significant differences between the assemblages of the four regions. Although there was a correlation between macroinvertebrate spatial patterns and a combination of local habitat, geomorphology and water chemistry attributes, it appears unlikely that these variables were responsible for the faunal differentiation by distance. Temporal variability was larger than spatial variability and temporal assemblage patterns were best explained by the ‘connectivity potential’ of waterholes, reflecting the position of individual waterholes within the broader channel network and long-term connectivity relationships, rather than the actual time since hydrological connection.

Capturing Spatial and Temporal Patterns of NO2 in Cities using mobile and stationary DOAS measurements

2021 ◽  
Author(s):  
Mark Wenig ◽  
Sheng Ye ◽  
Ying Zhu ◽  
Hanlin Zhang
Keyword(s):  
Air Quality ◽  
Hot Spots ◽  
Temporal Patterns ◽  
Optical Absorption Spectroscopy ◽  
Spatial And Temporal Patterns ◽  
The Public ◽  
Measurement Height ◽  
Weekly Cycles

<p>The problem of elevated NO<sub>2</sub> levels in cities has gained some attention in the public in recent years and has given rise to questions about the plausibility of banning diesel engines in cities, the meaning of exceedances of air quality limits and the effects of corona lock-downs on air quality to name a few. Urban air quality is typically monitored using a relatively small number of monitoring stations. Those in-situ measurements follow certain guidelines in terms of inlet height and location relative to streets, but the question remains how a limited number of point measurements can capture the spatial variability in cities. In this talk we present two measurement campaigns in Hong Kong and Munich where we utilized a combination of mobile in-situ and stationary remote sensing differential optical absorption spectroscopy (DOAS) instruments. We developed an algorithm to separate spatial and temporal patterns in order to generate pollution maps that represent average NO<sub>2</sub> exposure. </p> <p>We use those maps to identify pollution hot spots and capture the weekly cycles of on-road NO2 levels and spatial dependency of long-term changes and we analyze how on-road measurements compare to monitoring station data and how the measurement height and distance to traffic emissions have to be considered when interpreting observed concentration patterns.</p>

scholarly journals Spatial and temporal patterns of sediment storage and erosion following a wildfire and extreme flood

2019 ◽  
Author(s):  
Daniel J. Brogan ◽  
Peter A. Nelson ◽  
Lee H. MacDonald
Keyword(s):  
Laser Scanning ◽  
Sediment Accumulation ◽  
Temporal Patterns ◽  
Burn Severity ◽  
Spatial And Temporal Patterns ◽  
Channel Network ◽  
Valley Bottom ◽  
Erosion And Deposition ◽  
Downstream Effects ◽  
Extreme Flood

Abstract. Post-wildfire landscapes are highly susceptible to rapid geomorphic changes at both the hillslope and watershed scales due to increases in hillslope runoff and erosion, and the resulting downstream effects. Numerous studies have documented these changes at the hillslope scale, but relatively few studies have documented larger-scale post-fire geomorphic changes over time. In this study we used five airborne laser scanning (ALS) datasets collected over four years to quantify valley bottom changes in two ∼15 km2 watersheds, Skin Gulch and Hill Gulch, after the June 2012 High Park fire in northern Colorado and a large mesoscale flood 15 months later. The objectives were to: 1) quantify spatial and temporal patterns of erosion and deposition throughout the channel network following the wildfire and including the mesoscale flood; and 2) evaluate whether these changes are correlated to precipitation metrics, burn severity, or morphologic variables. Geomorphic changes were calculated using a DEMs of difference (DoD) approach for the channel network segmented into 50-m lengths. The results showed net sediment accumulation after the wildfire in the valley bottoms of both watersheds, with the greatest accumulations in the first two years after burning in wider and flatter valley bottoms. In contrast, the mesoscale flood caused large net erosion, with the greatest erosion in the areas with the greatest post-fire deposition. Volume changes for the different time periods were weakly but significantly correlated to, in order of decreasing correlation, contributing area, channel width, percent burned at high and/or moderate severity, channel slope, confinement ratio, maximum 30-minute rainfall, and total rainfall. These results suggest that morphometric characteristics, when combined with burn severity and a specified storm, can indicate the relative likelihood and locations for post-fire erosion and deposition. This information can help assess downstream risks and prioritize areas for post-fire hillslope rehabilitation treatments.

scholarly journals Long-term surveillance defines spatial and temporal patterns implicating Culex tarsalis as the primary vector of West Nile virus

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Brendan M. Dunphy ◽  
Kristofer B. Kovach ◽  
Ella J. Gehrke ◽  
Eleanor N. Field ◽  
Wayne A. Rowley ◽  
...  
Keyword(s):  
West Nile Virus ◽  
Temporal Patterns ◽  
Culex Tarsalis ◽  
Spatial And Temporal Patterns ◽  
West Nile ◽  
Primary Vector

Long-term spatial and temporal patterns of sea turtle strandings in southern Brazil

2016 ◽  
Vol 163 (12) ◽  
Author(s):  
Danielle S. Monteiro ◽  
Sérgio C. Estima ◽  
Tiago B. R. Gandra ◽  
Andrine P. Silva ◽  
Leandro Bugoni ◽  
...  
Keyword(s):  
Temporal Patterns ◽  
Sea Turtle ◽  
Southern Brazil ◽  
Spatial And Temporal Patterns

scholarly journals How Do Disturbance Generated Patterns Influence the Spatial Dynamics of Ecosystem Processes?

2005 ◽  
Vol 29 ◽  
pp. 59-60
Author(s):  
Monica Turner ◽  
William Romme ◽  
Daniel Tinker
Keyword(s):  
Spatial Variability ◽  
Spatial Variation ◽  
Spatial Patterns ◽  
Ecosystem Function ◽  
Spatial Dynamics ◽  
Temporal Patterns ◽  
Ecosystem Processes ◽  
Current Theory ◽  
Spatial And Temporal Patterns ◽  
Magnitude Variation

Our studies following the 1988 Yellowstone fires demonstrated that succession was surprisingly more variable in space and time than even current theory would have suggested, and that initial spatial patterns of disturbance may persist to produce long­lasting changes in vegetation. Our focus now is on explaining the spatial and temporal patterns of succession and understanding how these patterns influence ecosystem function. The most interesting new questions revolve around the degree to which the spatial variation in postfire vegetation -- in particular, the six orders of magnitude variation in pine sapling density, ranging from 0 to greater than 500,000 saplings/ha --controls the spatial variability in ecosystem processes across the landscape.

scholarly journals Spatial and temporal distribution patterns of tick-borne diseases (Tick-borne Encephalitis and Lyme Borreliosis) in Germany

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e12422
Author(s):  
Sarah Cunze ◽  
Gustav Glock ◽  
Sven Klimpel
Keyword(s):  
Spatial Patterns ◽  
Lyme Borreliosis ◽  
Temporal Distribution ◽  
Temporal Patterns ◽  
Weather Conditions ◽  
Driving Factors ◽  
Spatial And Temporal Patterns ◽  
Federal States ◽  
Reporting Practices ◽  
Tick Borne Encephalitis

Background In the face of ongoing climate warming, vector-borne diseases are expected to increase in Europe, including tick-borne diseases (TBD). The most abundant tick-borne diseases in Germany are Tick-Borne Encephalitis (TBE) and Lyme Borreliosis (LB), with Ixodes ricinus as the main vector. Methods In this study, we display and compare the spatial and temporal patterns of reported cases of human TBE and LB in relation to some associated factors. The comparison may help with the interpretation of observed spatial and temporal patterns. Results The spatial patterns of reported TBE cases show a clear and consistent pattern over the years, with many cases in the south and only few and isolated cases in the north of Germany. The identification of spatial patterns of LB disease cases is more difficult due to the different reporting practices in the individual federal states. Temporal patterns strongly fluctuate between years, and are relatively synchronized between both diseases, suggesting common driving factors. Based on our results we found no evidence that weather conditions affect the prevalence of both diseases. Both diseases show a gender bias with LB bing more commonly diagnosed in females, contrary to TBE being more commonly diagnosed in males. Conclusion For a further investigation of of the underlying driving factors and their interrelations, longer time series as well as standardised reporting and surveillance system would be required.

Long-Term Variation in Mesohaline Chesapeake Bay Macrobenthos: Spatial and Temporal Patterns

Estuaries ◽  
1987 ◽  
Vol 10 (3) ◽  
pp. 227 ◽  
Author(s):  
A. F. Holland ◽  
Anna T. Shaughnessy ◽  
Martha H. Hiegel
Keyword(s):  
Chesapeake Bay ◽  
Temporal Patterns ◽  
Spatial And Temporal Patterns ◽  
Term Variation
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