scholarly journals Spatial Patterns and Temporal Trends of Human Leishmaniasis Incidence in Khemisset Province, Morocco

2022 ◽  
Vol 14 (01) ◽  
pp. 09-15
Author(s):  
Hanna M ◽  
Boussaa S ◽  
Raghay K ◽  
Mabchour I ◽  
Fadli M
2014 ◽  
Vol 124 (1-2) ◽  
pp. 239-253 ◽  
Author(s):  
Tayeb Raziei ◽  
Jamal Daryabari ◽  
Isabella Bordi ◽  
Reza Modarres ◽  
Luis S. Pereira

2010 ◽  
Vol 158 (10) ◽  
pp. 3144-3156 ◽  
Author(s):  
H. Harmens ◽  
D.A. Norris ◽  
E. Steinnes ◽  
E. Kubin ◽  
J. Piispanen ◽  
...  

2008 ◽  
Vol 56 (5) ◽  
pp. 825-833 ◽  
Author(s):  
Norma Serra-Sogas ◽  
Patrick D. O’Hara ◽  
Rosaline Canessa ◽  
Peter Keller ◽  
Ronald Pelot

2014 ◽  
Vol 27 (14) ◽  
pp. 5396-5410 ◽  
Author(s):  
Nicholas R. Cavanaugh ◽  
Samuel S. P. Shen

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.


2017 ◽  
Author(s):  
Tobias Jeppsson

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.


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