Distribution of algae on tropical rocky shores: spatial and temporal patterns of non-coralline encrusting algae in Hong Kong

1996 ◽  
Vol 125 (1) ◽  
pp. 177-187 ◽  
Author(s):  
S. Kaehler ◽  
Gray A. Williams
Keyword(s):  
Hong Kong ◽  
Temporal Patterns ◽  
Rocky Shores ◽  
Spatial And Temporal Patterns

Variation in algal assemblages on wave-exposed rocky shores in New South Wales

1998 ◽  
Vol 49 (3) ◽  
pp. 241 ◽  
Author(s):  
A. J. Underwood ◽  
M. G. Chapman
Keyword(s):  
Large Scale ◽  
New South ◽  
New South Wales ◽  
Temporal Patterns ◽  
Explanatory Models ◽  
Small Scale ◽  
Rocky Shores ◽  
Spatial And Temporal Patterns ◽  
South Wales ◽  
Algal Assemblages

Data were collected in New South Wales from replicate sites on five wave-exposed shores separated by hundreds of kilometres at three-monthly intervals for four years, to examine large and small spatial and temporal patterns in low-shore algal assemblages. These data were used to test hypotheses from the models that algal assemblages show large-scale, predictable changes in structure or, alternatively, that variation from time to time is small-scale and differs from shore to shore or site to site on a shore. There was considerable variation at all scales examined — among replicate quadrats within sites, between sites on a shore and among shores. Similarly, assemblages differed from one sampling period to the next and changes in the assemblages over time periods of three months were as great as from year to year. These changes were interactive, with no two sites or shores showing similar temporal patterns. Thus, understanding diversity along a coast-line requires detailed understanding of local processes. Without adequate spatial and temporal replication in sampling designs and without explanatory models, the large and complex variability in intertidal assemblages at different scales cannot be documented and understood.

Measuring Spatial and Temporal Patterns of Urban NO2 Concentrations by combining mobile and stationary DOAS instruments

2020 ◽  
Author(s):  
Mark Wenig ◽  
Ying Zhu ◽  
Sheng Ye ◽  
Ka Lok Chan ◽  
Jia Chen ◽  
...  
Keyword(s):  
Hong Kong ◽  
Air Quality ◽  
Temporal Patterns ◽  
Optical Absorption Spectroscopy ◽  
Data Sets ◽  
Spatial And Temporal Patterns ◽  
Air Quality Monitoring Stations ◽  
Weekly Cycles ◽  
Mobile Measurements ◽  
Monitoring Stations

<p>In many cities around the world the NO<sub>2</sub> concentration levels exceed WHO guideline limits. Urban air quality is typically monitored using a relatively small number or monitoring stations that follow certain guidelines in terms of inlet height and location relative to streets. However, the question remains how a limited number of point measurements can represent the city-wide air quality and capture spatial patterns. Measurement campaigns in Hong Kong and Munich were conducted, using a combination of mobile in-situ and stationary remote sensing differential optical absorption spectroscopy (DOAS) instruments. In order to separate spatial and temporal patterns, we developed an algorithm based on a combination of mobile and stationary data sets that corrects for the diurnal cycle in the mobile measurements.  We constructed pollution maps from the corrected measurements that represent daily average NO<sub>2</sub> exposure. The maps have been used to identify pollution hot spots, determine the spatial dependency of long-term changes, and capture the weekly cycles of on-road NO<sub>2</sub> levels in Hong Kong and Munich. Since our method can also be used to determine the spatial representativeness of the monitoring stations in cities, it is very valuable tool for identifying suitable locations for air quality monitoring stations.</p>

SPATIAL AND TEMPORAL PATTERNS OF GROUNDWATER ELEVATION AND SALINITY ON ASSATEAGUE ISLAND

2016 ◽  
Author(s):  
Ruth Coffey ◽  
◽  
Hannah Sprinkle ◽  
Eric Sherry ◽  
Brian Sturgis ◽  
...  
Keyword(s):  
Temporal Patterns ◽  
Spatial And Temporal Patterns ◽  
Assateague Island
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