Event Abstract

The impact of outdoor lighting on ecosystem function – gaining information with a Citizen Science approach using a questionnaire

  • 1 Leibniz Institute of Freshwater Ecology and Inland Fishery (IGB), Germany
  • 2 University Potsdam, Institute of Earth and Environmental Science, Germany
  • 3 Berlin Center for Genomics in Biodiversity Research, Germany

Introduction
Artificial light at night (ALAN) is an irreplaceable technology, providing visibility for human activity after the onset of darkness. Nonetheless, outdoor lighting has manifold side-effects. It can disturb nightscapes, ecosystems and consequently biodiversity (Schroer & Hölker 2016). ALAN is increasing rapidly (Hölker et al. 2010), including in protected areas (Gaston et al. 2015). It is the most visible pollutant of our planet, perceptible even from space. One instrument to measure ALAN is therefore via remote sensing by satellite. The Visible Infrared Imaging Radiometer Suite Day-Night Band (VIIRS-DNB) takes images of the entire Earth at around midnight local time. The camera detects lighting below streetlight emission levels (≥ 0.2 nW/cm²sr) (Elvidge et al. 2013), but has low sensitivity in the spectral emission below 500 nm (Kyba et al. 2015). This is a weakness because modern street lights such as LEDs have considerable emission in the range 450-480 nm (Elvidge et al. 2010). Secondly, the measurement is restricted to the overpass, hence temporary lighting before midnight is not recorded. Additional measurements are required to supplement these disadvantages. One approach is exemplified by the citizen science (CS) application ‘Loss of the Night’ which asks participants to detect stars of different brightness, in order to estimate light pollution from the ground (Kyba et al. 2013). Unfortunately the application depends on weather conditions and the position of the moon, and cannot be used in direct proximity of light sources. Hence, a questionnaire was developed to gain more information about outdoor lighting conditions. Our aim is to determine whether we can use CS methods to detect potential impact of ALAN on the microbial community composition and its ecological function at a nationwide scale. Hölker et al. (2015) observed increases in biomass and abundance of photosynthetic microbes in freshwater sediments that were exposed to ALAN for more than one year, indicating that ALAN can alter communities and ecosystem processes. The CS project “Tatort Gewässer” (crime scene freshwater) was developed to gain new knowledge about the role of inland waters in the carbon-cycle and what effects ALAN may have. Here we discuss the usefulness of a questionnaire for information on local ALAN. Material and Methods
A CS sampling campaign of Germany’s inland waters was conducted in early November 2015. Citizens could register online using an interactive inland water map (http://tatortgewässer.de/) that indicates the registered location, the successful return of the sample and information of the respective freshwater system. Participants were asked to take samples at a freshwater body close to their home to measure CO2-and CH4-concentrations and microbial diversity. A sampling kit was developed to ensure standardized sampling (Fig 1). In total, 742 sampling kits were distributed to registered citizens, including nature conservation organizations, schools, kinder-gardens, diving and angling associations, national parks, nature conservation authorities and provincial offices. Participants recorded the exact time and location of the sampling (using Google Maps GPS data) and other sampling metadata. The CS records were supplemented by data from the German Digital Landscape Model (ATKIS Base-DLM), for more information on the environmental context of the sample. For the determination of the night-time brightness, a questionnaire was provided (http://tatortgewässer.de/wp-content/uploads/2015/07/Druckdokument-Befragung-künstliches-Licht_19.10.15.pdf). Citizens were asked about the distance to the nearest light source, the number of visible light sources and the estimated intensity. Further questions referred to lamp cover and form, maintenance condition and the colour of emitted light. For professional measure VIIRS-DNB data were used as recorded in November 2015. Additionally, the ‘Loss of the Night’ App was offered to participants. Results
From the 742 sampling kits that were distributed, 86% were returned from throughout Germany (Fig. 2). These contained samples from 161 streams, 103 rivers, 94 ponds and 276 lakes. The sample sites were distributed among naturally dark rural to central urban areas with variable levels of upward radiation (Fig 3). Of all sample kits returned, 609 contained information on the questionnaires about visible artificial light sources (Table 1). Of these, 226 sites had no visible artificial light sources, of which 85 sites were in areas below 0.43 nW/cm²sr upward radiation, which is rated as natural dark areas. Another 107 sites were in areas with 0.43 - 2.2 nW/cm²sr, which is rated as rural low district lighting; 34 sites were in areas with 2.2 -5.6 nW/cm²sr, which can be reached in outskirts of smaller cities. 383 sites had visible light sources; 16 of these sites were in areas with 19-36 nW/cm²sr upward radiation, which are light levels of small cities or urban areas, 140 sites were from rural low district lighting areas and 43 were recorded in natural dark areas. From the total of 128 sites in natural dark areas, 6 were less than 50 m away from a light source and had more than 1 lamp (Table 2). Figure 4 presents the distribution of sample sites indicating the upward radiation of the area and the recorded distance to visible lamps. Overall, the citizens’ responses match the satellite data and additionally offer more detailed information about direct or indirect radiation on inland waters. Discussion
The data required to answer the question if ALAN has an impact on the microbial community composition and its ecological function demands large numbers of comparable samples from non-illuminated and illuminated sites in natural dark to relative bright urban areas. The broad spatial distribution of sampled inland waters in this short collecting period could only be gained with citizen scientists. The CS approach was therefore proven to be a powerful tool for sampling and characterizing sample sites. The results present only a few artificial light sources, which were undetected by VIIRS imaging. With the questionnaire we gained information to distinguish between sample sites with direct illumination or background lighting of the area. We are currently processing CO2, CH4, and microbial community data to test for ALAN effects. Adding other collected metadata, it may be possible to detect additive, antagonistic or synergistic interactions of ALAN and other stressors, for example land use or climate change.

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Acknowledgements

We want to thank all citizen scientists involved for their dedication, their great contribution to this work and the many photos and comments that were sent in addition. The study was supported by the IGB Seed Money Program.

References

Elvidge, C.D., et al. (2010). Spectral identification of lighting type and character. Sensors, 10, 3961–3988.
Elvidge, C.D., et al.(2013). Why VIIRS data are superior to DMSP for mapping nighttime lights. Proceedings of the Asia-Pacific Advanced Network, 7, 62–69.
Gaston, K.J., Duffy, J.P., and Bennie, J. (2015). Quantifying the erosion of natural darkness in the global protected area system. Conservation Biology, 29, 1132–1141.
Hölker, F., et al., 2015. Microbial diversity and community respiration in freshwater sediments influenced by artificial light at night. Philosophical Transactions of the Royal Society B-Biological Sciences, 370, 20140130.
Hölker, F., et al., 2010. The Dark Side of Light: A Transdisciplinary Research Agenda for Light. Ecology and Society, 15(4), art. 13.
Kyba, C.C.M., et al., 2015. High-Resolution Imagery of Earth at Night: New Sources, Opportunities and Challenges. Remote Sensing, 7, 1–23.
Kyba, C.C.M., et al., 2013. Citizen Science provides valuable data for monitoring global night sky luminance. Scientific Reports, 3, 1835.
Schroer, S., Hölker, F., 2016. Impact of Lighting on Flora and Fauna. In R. Karlicek et al., eds. Handbook of Advanced Lighting Technology. Springer International Publishing. DOI: 10.1007/978-3-319-00295-8_42-1

Keywords: carbon dynamics, carbon source, carbon sink, sediment, light pollution, Artificial light at night, ALAN, lighting factors, inland waters, lake heterotrophy

Conference: Austrian Citizen Science Conference 2016, Lunz am See, Austria, 18 Feb - 19 Feb, 2016.

Presentation Type: Oral Presentation

Topic: Citizen Science - Quo vadis?

Citation: Schroer S, Felsmann K, Hölker F, Mummert S, Monaghan MT, Wurzbacher C and Premke K (2016). The impact of outdoor lighting on ecosystem function – gaining information with a Citizen Science approach using a questionnaire. Front. Environ. Sci. Conference Abstract: Austrian Citizen Science Conference 2016. doi: 10.3389/conf.FENVS.2016.01.00008

Received: 17 Jun 2016; Published Online: 06 Sep 2016.

* Correspondence: Dr. Sibylle Schroer, Leibniz Institute of Freshwater Ecology and Inland Fishery (IGB), Berlin, Germany, Schroer@igb-berlin.de

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