Long-term environmental monitoring for assessment of change: measurement inconsistencies over time and potential solutions
- 350 Downloads
The importance of long-term environmental monitoring and research for detecting and understanding changes in ecosystems and human impacts on natural systems is widely acknowledged. Over the last decades, a number of critical components for successful long-term monitoring have been identified. One basic component is quality assurance/quality control protocols to ensure consistency and comparability of data. In Norway, the authorities require environmental monitoring of the impacts of the offshore petroleum industry on the Norwegian continental shelf, and in 1996, a large-scale regional environmental monitoring program was established. As a case study, we used a sub-set of data from this monitoring to explore concepts regarding best practices for long-term environmental monitoring. Specifically, we examined data from physical and chemical sediment samples and benthic macroinvertebrate assemblages from 11 stations from six sampling occasions during the period 1996–2011. Despite the established quality assessment and quality control protocols for this monitoring program, we identified several data challenges, such as missing values and outliers, discrepancies in variable and station names, changes in procedures without calibration, and different taxonomic resolution. Furthermore, we show that the use of different laboratories over time makes it difficult to draw conclusions with regard to some of the observed changes. We offer recommendations to facilitate comparison of data over time. We also present a new procedure to handle different taxonomic resolution, so valuable historical data is not discarded. These topics have a broader relevance and application than for our case study.
KeywordsData comparability Long-term monitoring Macrobenthos Oil and gas industry Taxonomic resolution
KEE was supported by the Norwegian Oil and Gas Association (project no. 20-2013), the Norwegian Environment Agency (project no. 1204110 and 4013045), the Norwegian Research Council (project no. 212135), and Norwegian Institute for Nature Research (NINA). NGY and TT were supported by NINA. We thank one anonymous referee for useful comments on this article.
- Buss, D. F., Carlisle, D. M., Chon, T.-S., Culp, J., Harding, J. S., Keizer-Vlek, H. E., et al. (2015). Stream biomonitoring using macroinvertebrates around the globe: a comparison of large-scale programs. Environmental Monitoring and Assessment, 187, 4132. https://doi.org/10.1007/s10661-014-4132-8.CrossRefGoogle Scholar
- Cochrane, S., Palerud, R., Wasbotten, I. H., Larsen, L. H., & Mannvik, H. P. (2009). Offshore sediment survey of Region I, 2008. Akvaplan-niva report no. 4215-02. Akvaplan-niva, Tromsø. 314 pp.Google Scholar
- Gattuso, J.-P., Magnan, A., Billé, R., Cheung, W. W. L., Howes, E. L., Joos, F., et al. (2015). Contrasting futures for ocean and society from different anthropogenic CO2 emissions scenarios. Science, 349.Google Scholar
- Iversen, P. E., Green, A. M. V., Lind, M. J., Petersen, M. R. H., Bakke, T., Lichtenthaler, R., et al., (2011). Guidelines for offshore environmental monitoring: the petroleum sector on the Norwegian continental shelf. Climate and Pollution Agency. TA number 2849/2011. 49 pp.Google Scholar
- Iversen, P. E. Lind, M. J., Ersvik, M., Rønning, I., Skaare, B. B., Green, A. M. V., et al., (2015). Guidelines for environmental monitoring of petroleum activities on the Norwegian continental shelf. The Norwegian Environment. Agency M-number M-300/2015. 60 pp. (In Norwegian).Google Scholar
- Jensen, T., Gjøs, N., Nøland, S.-A., Oreld, F., Møskeland, T., Bakke, S. M., et al., (2000). Environmental monitoring 1999, Region I—Ekofisk. Technical report. Report no. 2000-3238. Det Norske Veritas & Sintef Applied Chemistry, Norway. 294 pp.Google Scholar
- Lindenmayer, D. B., & Likens, G. E. (2010). Effective ecological monitoring. London: CSIRO Publishing 170 pp.Google Scholar
- Little, R. J. A., & Rubin, D. B. (1987). Statistical analysis with missing data. New York: John Wiley and Sons.Google Scholar
- Mannvik, H. P., Pearson, T., Pettersen, A., & Lie Gabrielsen, K. (1997). Environmental monitoring survey Region I 1996. Main report. Akvaplan-niva report no. 411.96.996-1. Akvaplan-Niva, Tromsø. 246 pp.Google Scholar
- Mannvik, H. P., Wasbotten, I. H., Cochrane, S., & Moldes-Anaya, A. (2012). Miljøundersøkelse Region I, 2011. Akvaplan-niva report no. 5339.02. Akvaplan-niva, Tromsø. 196 pp. (In Norwegian).Google Scholar
- Mieszkowska, N., Sugden, H., Firth, L. B., & Hawkins, S. J. (2014). The role of sustained observations in tracking impacts of environmental change on marine biodiversity and ecosystems. Philosophical Transactions of the Royal Society A, 372, 20130339.Google Scholar
- Norwegian Oil and Gas (2013). Environmental report 2013. The Norwegian Oil and Gas Association. http://www.norskoljeoggass.no/en/Publica/Environmentalreports/Environmental-report-2013/.
- Nøland, S. A., Gjøs, N., Bakke, S. M., & Oreld F. (2003). Environmental monitoring 2002, Region I—Ekofisk. Main report. Technical report. Report no. 2003-0338. Det Norske Veritas/Sintef, Norway. 316 pp.Google Scholar
- Nøland, S. A., Bakke, S. M., Rustad, I., & Brinchmann, K. M. (2006). Environmental monitoring Region I, 2005. Main report. Report no. 2006-0187. Det Norske Veritas, Norway. 344 pp.Google Scholar
- R Core Team (2015). R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. URL http://www.R-project.org/.
- Renaud, P. E., Jensen, T., Wassbotten, I., Mannvik, H. P., & Botnen, H., (2008). Offshore sediment monitoring on the Norwegian shelf. A regional approach 1996–2006. Akvaplan-niva report no 3487–003. Akvaplan-Niva, Tromsø. 95 pp.Google Scholar
- Ross, D. S., Bailey, S. W., Briggs, R. D., Curry, J., Fernandez, I. J., Fredriksen, G., et al. (2015). Inter-laboratory variation in the chemical analysis of acidic forest soil reference samples from eastern North America. Ecosphere, 6(5), 73. https://doi.org/10.1890/ES14-00209.1.CrossRefGoogle Scholar