A flexible Bayesian hierarchical approach for analyzing spatial and temporal variation in the fecal corticosterone levels in birds when there is imperfect knowledge of individual identity

2013 ◽  
Vol 194 ◽  
pp. 64-70 ◽  
Author(s):  
Guthrie S. Zimmerman ◽  
Joshua J. Millspaugh ◽  
William A. Link ◽  
Rami J. Woods ◽  
R.J. Gutiérrez
Keyword(s):  
Temporal Variation ◽  
Spatial And Temporal Variation ◽  
Individual Identity ◽  
Hierarchical Approach ◽  
Bayesian Hierarchical ◽  
Imperfect Knowledge

Temporal and spatial variability in seedling dynamics: a cross-site comparison in four lowland tropical forests

2008 ◽  
Vol 24 (1) ◽  
pp. 9-18 ◽  
Author(s):  
Margaret R. Metz ◽  
Liza S. Comita ◽  
Yu-Yun Chen ◽  
Natalia Norden ◽  
Richard Condit ◽  
...  
Keyword(s):  
Temporal Variation ◽  
Tropical Forests ◽  
Spatial And Temporal Variation ◽  
Monitoring Methods ◽  
Bayesian Hierarchical ◽  
Seedling Demography ◽  
Temporal And Spatial Variability ◽  
Seedling Dynamics ◽  
Lowland Forests

Abstract:Spatial and temporal variation in seedling dynamics was assessed using records of community-wide seedling demography collected with identical monitoring methods at four tropical lowland forests in Panama, Malaysia, Ecuador and French Guiana for periods of between 3 and 10 y. At each site, the fates of between 8617 and 391 777 seedlings were followed through annual censuses of the 370–1008 1-m2 seedling plots. Within-site spatial and inter-annual variation in density, recruitment, growth and mortality was compared with among-site variability using Bayesian hierarchical modelling to determine the generality of each site's patterns and potential for meaningful comparisons among sites. The Malaysian forest, which experiences community-wide masting, was the most variable in both seedling density and recruitment. However, density varied year-to-year at all sites (CVamong years at site = 8–43%), driven largely by high variability in recruitment rates (CV = 40–117%). At all sites, recruitment was more variable than mortality (CV = 5–64%) or growth (CV = 12–51%). Increases in mortality rates lagged 1 y behind large recruitment events. Within-site spatial variation and inter-annual differences were greater than differences among site averages in all rates, emphasizing the value of long-term comparative studies when generalizing how spatial and temporal variation drive patterns of recruitment in tropical forests.

Effects of streamflow regime on the concentration-flow (CQ) relationships across climate zones: a study across the Australian continent

2021 ◽  
Author(s):  
Clément Duvert ◽  
Danlu Guo ◽  
Camille Minaudo ◽  
Rémi Dupas ◽  
Anna Lintern ◽  
...  
Keyword(s):  
Water Quality ◽  
Temporal Variation ◽  
Spatial And Temporal Variation ◽  
Phosphorus Species ◽  
Climate Zones ◽  
Bayesian Hierarchical ◽  
Australian Continent ◽  
Data Driven Approach ◽  
Total Variability ◽  
Reactive Phosphorus

<p>Understanding the spatial and temporal variation of concentration-flow (CQ) relationships is valuable to enhance understanding of the key processes that drive changes in catchment water quality. This study used a data-driven approach to understand how the CQ relationship is influenced by catchment flow regimes (baseflow versus runoff dominated) throughout the Australian continent. To summarize the CQ relationship, we focus on the b exponent in a power-law relationship (C=aQ<sup>b</sup>). We considered six commonly monitored constituents, namely, electrical conductivity (EC), total phosphorus (TP), filterable reactive phosphorus (FRP), total suspended solids (TSS), nitrate–nitrite (NO<sub>x</sub>) and total nitrogen (TN), at a total of 251 catchments in Australia. A novel Bayesian hierarchical model was developed to assess a) the impacts of flow regime on CQ relationships, both across catchments (spatial variation) and within individual catchments (temporal variation); and b) how these impacts vary across five typical Australian climate zones – arid, Mediterranean, temperate, sub-tropical and tropical.</p><p>We found that for individual constituents: 1) spatial variations in CQ relationships are clearly influenced by the catchment-level baseflow contribution, and these influences differ with climate regions; 2) across climate zones, runoff-dominated catchments (i.e. with low baseflow contribution) have relatively stable CQ relationships, while groundwater-dominated catchments (i.e. with high baseflow contribution) have highly variable CQ patterns across climate zones; 3) within individual catchments, the variations in instantaneous baseflow contribution have no systematic and consistent effect on the CQ relationships. The influence of catchment baseflow contribution on CQ relationships has potential to be used to predict catchment water quality across Australia, with over half the total variability in concentration of sediment, salt and phosphorus species explained by variations in catchment-level baseflow contribution.</p>

scholarly journals Spatial and Temporal Variation Characteristics of Snowfall in the Haihe River Basin from 1960 to 2016

Water ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 1798
Author(s):  
Xu Wu ◽  
Su Li ◽  
Bin Liu ◽  
Dan Xu
Keyword(s):  
Temporal Variation ◽  
River Basin ◽  
Spatial And Temporal Variation ◽  
Haihe River Basin ◽  
Temperature Threshold ◽  
Threshold Method ◽  
Exponential Equation ◽  
Haihe River ◽  
The Haihe River Basin ◽  
Different Levels

The spatio-temporal variation of precipitation under global warming had been a research hotspot. Snowfall is an important part of precipitation, and its variabilities and trends in different regions have received great attention. In this paper, the Haihe River Basin is used as a case, and we employ the K-means clustering method to divide the basin into four sub-regions. The double temperature threshold method in the form of the exponential equation is used in this study to identify precipitation phase states, based on daily temperature, snowfall, and precipitation data from 43 meteorological stations in and around the Haihe River Basin from 1960 to 1979. Then, daily snowfall data from 1960 to 2016 are established, and the spatial and temporal variation of snowfall in the Haihe River Basin are analyzed according to the snowfall levels as determined by the national meteorological department. The results evalueted in four different zones show that (1) the snowfall at each meteorological station can be effectively estimated at an annual scale through the exponential equation, for which the correlation coefficient of each division is above 0.95, and the relative error is within 5%. (2) Except for the average snowfall and light snowfall, the snowfall and snowfall days of moderate snow, heavy snow, and snowstorm in each division are in the order of Zones III > IV > I > II. (3) The snowfall and the number of snowfall days at different levels both show a decreasing trend, except for the increasing trend of snowfall in Zone I. (4) The interannual variation trend in the snowfall at the different levels are not obvious, except for Zone III, which shows a significant decreasing trend.

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