Factors affecting spatial and temporal patterns in perfluoroalkyl acid (PFAA) concentrations in migratory aquatic species: a case study of an exploited crustacean

2019 ◽  
Vol 21 (11) ◽  
pp. 1946-1956 ◽  
Author(s):  
Matthew D. Taylor
Keyword(s):  
Temporal Variation ◽  
Temporal Patterns ◽  
Spatial And Temporal Variation ◽  
Aquatic Species ◽  
Spatial And Temporal Patterns ◽  
Physiological Factors ◽  
Factors Affecting ◽  
Free Ranging ◽  
Perfluoroalkyl Acid

Free-ranging prawns showed substantial spatial and temporal variation in PFOS concentrations, most likely driven by behavioural and physiological factors.

scholarly journals Spatial and Temporal Patterns of Illegal Logging in Selectively Logged Production Forest: A Case Study in Yedashe, Myanmar

2018 ◽  
Vol 23 (2) ◽  
pp. 15-25 ◽  
Author(s):  
Zar Chi Win ◽  
Nobuya Mizoue ◽  
Tetsuji Ota ◽  
Guangyu Wang ◽  
John L. Innes ◽  
...  
Keyword(s):  
Temporal Patterns ◽  
Illegal Logging ◽  
Spatial And Temporal Patterns

scholarly journals Spatial and Temporal Patterns in Volunteer Data Contribution Activities: A Case Study of eBird

2020 ◽  
Vol 9 (10) ◽  
pp. 597
Author(s):  
Guiming Zhang
Keyword(s):  
Temporal Dynamics ◽  
Bird Species ◽  
Temporal Patterns ◽  
Volunteered Geographic Information ◽  
Geographic Information ◽  
Spatial And Temporal Patterns ◽  
Space And Time ◽  
Spatial And Temporal Dynamics ◽  
The World

Volunteered geographic information (VGI) has great potential to reveal spatial and temporal dynamics of geographic phenomena. However, a variety of potential biases in VGI are recognized, many of which root from volunteer data contribution activities. Examining patterns in volunteer data contribution activities helps understand the biases. Using eBird as a case study, this study investigates spatial and temporal patterns in data contribution activities of eBird contributors. eBird sampling efforts are biased in space and time. Most sampling efforts are concentrated in areas of denser populations and/or better accessibility, with the most intensively sampled areas being in proximity to big cities in developed regions of the world. Reported bird species are also spatially biased towards areas where more sampling efforts occur. Temporally, eBird sampling efforts and reported bird species are increasing over the years, with significant monthly fluctuations and notably more data reported on weekends. Such trends are driven by the expansion of eBird and characteristics of bird species and observers. The fitness of use of VGI should be assessed in the context of applications by examining spatial, temporal and other biases. Action may need to be taken to account for the biases so that robust inferences can be made from VGI observations.

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