Visualization of spatial patterns and temporal trends for aerial surveillance of illegal oil discharges in western Canadian marine waters

2008 ◽  
Vol 56 (5) ◽  
pp. 825-833 ◽  
Author(s):  
Norma Serra-Sogas ◽  
Patrick D. O’Hara ◽  
Rosaline Canessa ◽  
Peter Keller ◽  
Ronald Pelot
Keyword(s):  
Spatial Patterns ◽  
Temporal Trends ◽  
Marine Waters ◽  
Aerial Surveillance

Spatial patterns and temporal trends of daily precipitation indices in Iran

2014 ◽  
Vol 124 (1-2) ◽  
pp. 239-253 ◽  
Author(s):  
Tayeb Raziei ◽  
Jamal Daryabari ◽  
Isabella Bordi ◽  
Reza Modarres ◽  
Luis S. Pereira
Keyword(s):  
Spatial Patterns ◽  
Daily Precipitation ◽  
Temporal Trends ◽  
Precipitation Indices

Mosses as biomonitors of atmospheric heavy metal deposition: Spatial patterns and temporal trends in Europe

2010 ◽  
Vol 158 (10) ◽  
pp. 3144-3156 ◽  
Author(s):  
H. Harmens ◽  
D.A. Norris ◽  
E. Steinnes ◽  
E. Kubin ◽  
J. Piispanen ◽  
...  
Keyword(s):  
Heavy Metal ◽  
Spatial Patterns ◽  
Temporal Trends ◽  
Metal Deposition ◽  
Heavy Metal Deposition

scholarly journals Northern Hemisphere Climatology and Trends of Statistical Moments Documented from GHCN-Daily Surface Air Temperature Station Data from 1950 to 2010

2014 ◽  
Vol 27 (14) ◽  
pp. 5396-5410 ◽  
Author(s):  
Nicholas R. Cavanaugh ◽  
Samuel S. P. Shen
Keyword(s):  
Standard Deviation ◽  
Northern Hemisphere ◽  
Spatial Patterns ◽  
Air Temperature ◽  
Probability Distributions ◽  
Temporal Trends ◽  
Surface Air Temperature ◽  
Statistical Moments ◽  
Station Data ◽  
Skewness And Kurtosis

Abstract The first four statistical moments and their trends are calculated for the average daily surface air temperature (SAT) from 1950 to 2010 using the Global Historical Climatology Network–Daily station data for each season relative to the 1961–90 climatology over the Northern Hemisphere. Temporal variation of daily SAT probability distributions are represented as generalized linear regression coefficients on the mean, standard deviation, skewness, and kurtosis calculated for each 10-yr moving time window from 1950–59 to 2001–10. The climatology and trends of these statistical moments suggest that daily SAT probability distributions are non-Gaussian and are changing in time. The climatology of the first four statistical moments has distinct spatial patterns with large coherent structure for mean and standard deviation and relatively smaller and more regionalized patterns for skewness and kurtosis. The linear temporal trends from 1950 to 2010 of the first four moments also have coherent spatial patterns. The linear temporal trends in the characterizing statistical moments are statistically significant at most locations and have differing spatial patterns for different moments. The regionalized variations specific to higher moments may be related to the climate dynamics that contribute to extremes. The nonzero skewness and kurtosis makes this detailed documentation on the higher statistical moments useful for quantifying climate changes and assessing climate model uncertainties.

scholarly journals The many forms of beta diversity: a comment on McGill et al. and some notational suggestions

2017 ◽  
Author(s):  
Tobias Jeppsson
Keyword(s):  
Spatial Patterns ◽  
Beta Diversity ◽  
Temporal Trend ◽  
Species Turnover ◽  
Temporal Trends ◽  
Β Diversity ◽  
Different Types ◽  
Biodiversity Change ◽  
The Many

Fundamentally, beta diversity is a measure of species turnover across time or space. In practice, it is sometimes unclear exactly what aspect of beta diversity that is implied in studies. For instance, a trend in ’spatial beta diversity’ can be used to refer to both differences in spatial beta diversity between sites, as well as a temporal trend in spatial beta diversity (at the same site). In a recent review, McGill et al. [1] provide a useful and much needed overview of different aspects of biodiversity change, and show areas where we lack knowledge. Even so, McGill et al. ignore some aspects of beta diversity and sometimes pool different types of beta diversity under the same heading. However, their review mainly focused on temporal trends in diversity, while I here want to highlight spatial patterns in temporal β -diversity (species turnover) as an important but somewhat overlooked component of biodiversity change. Furthermore, I propose a slightly modified classification and nomenclature of metrics of biodiversity change, with the aim of complementing their review. The notation used here can hopefully be useful to other authors as well.

scholarly journals Nitrogen Deposition on Danish Nature

Atmosphere ◽  
2018 ◽  
Vol 9 (11) ◽  
pp. 447 ◽  
Author(s):  
Thomas Ellermann ◽  
Jesper Nygaard ◽  
Jesper Christensen ◽  
Per Løfstrøm ◽  
Camilla Geels ◽  
...  
Keyword(s):  
Nitrogen Deposition ◽  
Critical Loads ◽  
Temporal Trends ◽  
Monitoring Program ◽  
Terrestrial Ecosystems ◽  
Marine Waters ◽  
Model Calculations ◽  
Nitrogen Loads ◽  
Long Term Trends

Eutrophication events are frequent in Inner Danish waters and critical loads are exceeded for much of the Danish sensitive terrestrial ecosystems. The Danish air quality monitoring program combines measurements and model calculations to benefit from the complementarities in data from these two sources. Measurements describe actual status, seasonal variation, and temporal trends. Model calculations extrapolate the results to the entire country and determine depositions to specific ecosystems. Measurements in 2016 show annual depositions between 7.5 and 11 kg N/ha to terrestrial ecosystems, and a load to marine waters of 5.3 kg N/ha. The deposition on Danish marine waters in 2016 was calculated to be 73,000 tons N with an average deposition of 6.9 kg N/ha. For terrestrial areas, the deposition was calculated to be 57,000 tons N with an average deposition of 13 kg N/ha. This is above critical loads for sensitive ecosystems. Long-term trends show a 35% decrease since 1990 in measured annual nitrogen deposition. At two out of four stations in nature areas, measured ammonia levels exceeded critical levels for lichens and mosses. Conclusions: Nitrogen loads and levels to Danish nature is decreasing, but critical loads and levels are still exceeded for sensitive ecosystems. Combining measurements and model calculations is a strong tool in monitoring.

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