Environmental and Ecological Statistics

, Volume 20, Issue 3, pp 353–375 | Cite as

Spatial variogram estimation from temporally aggregated seabird count data

  • B. Pérez-Lapeña
  • K. M. Wijnberg
  • A. Stein
  • S. J. M. H. Hulscher


Seabird abundance is an important indicator for assessing impact of human activities on the marine environment. However, data collection at sea is time consuming and surveys are carried out over several consecutive days for efficiency reasons. This study investigates the validity of aggregating those data over time to estimate a spatial variogram that is representative for spatial correlation in species abundance. For this purpose we simulate four-day surveys of seabird count data that contain spatial and temporal correlation arising from temporal changes in the spatial pattern of environmental conditions. Estimates of the aggregated spatial variogram are compared to a variogram that would arise when data were collected over a single day. The study reveals that, under changing environmental conditions over surveys days, aggregating data over a four-day survey increases both the non-spatial variation in the data and the scale of spatial correlation in seabird data. Next, the effect of using an aggregated variogram on the statistical power to test the significance of an impact is investigated. The impact concerns a case of establishing an offshore wind farm resulting in seabird displacement. The study shows that both overestimation and underestimation of statistical power occurs, with power estimates differing up to a factor of two. We conclude that the spatial variation in seabird abundance can be misrepresented by using temporally aggregated data. In impact studies, such misrepresentation can lead to erroneous assessments of the ability to detect impact.


Ecological surveys Impact assessment Spatio-temporal correlation Statistical power Unconditional simulation 


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Copyright information

© Springer Science+Business Media New York 2012

Authors and Affiliations

  • B. Pérez-Lapeña
    • 1
  • K. M. Wijnberg
    • 1
  • A. Stein
    • 2
  • S. J. M. H. Hulscher
    • 1
  1. 1.Department of Water Engineering and Management, Faculty of Engineering TechnologyUniversity of TwenteEnschedeThe Netherlands
  2. 2.Department of Earth Observation Science, Faculty of Geo-Information Science and Earth Observation (ITC)University of TwenteEnschedeThe Netherlands

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