Human alteration of natural light cycles: causes and ecological consequences
- 7k Downloads
Artificial light at night is profoundly altering natural light cycles, particularly as perceived by many organisms, over extensive areas of the globe. This alteration comprises the introduction of light at night at places and times at which it has not previously occurred, and with different spectral signatures. Given the long geological periods for which light cycles have previously been consistent, this constitutes a novel environmental pressure, and one for which there is evidence for biological effects that span from molecular to community level. Here we provide a synthesis of understanding of the form and extent of this alteration, some of the key consequences for terrestrial and aquatic ecosystems, interactions and synergies with other anthropogenic pressures on the environment, major uncertainties, and future prospects and management options. This constitutes a compelling example of the need for a thoroughly interdisciplinary approach to understanding and managing the impact of one particular anthropogenic pressure. The former requires insights that span molecular biology to ecosystem ecology, and the latter contributions of biologists, policy makers and engineers.
KeywordsDay Diurnal Night Nocturnal Skyglow
Ecological systems are organized foremost by light, and particularly by daily and seasonal cycles of light and dark (Bradshaw and Holzapfel 2010; Kronfeld-Schor et al. 2013). Humans are profoundly altering these cycles as detected and/or perceived by many organisms. This is occurring by the introduction of artificial light at night (ALAN) in the environment, predominantly from electric lighting sources associated with human settlement, transport networks and industry, the impact of which extends across much of the globe (Cinzano et al. 2001). In turn this is influencing biological systems from the molecule to the ecosystem, including impacts on gene expression, physiology and behaviour of organisms, abundance and distribution of species, ecological interactions, and the composition of communities (e.g. recent examples include Bird et al. 2004; Davies et al. 2012; Dwyer et al. 2012; Dominoni et al. 2013a; Le Tallec et al. 2013; Mazor et al. 2013; Picchi et al. 2013). This then almost inevitably affects the function and process of ecosystems, and thus other fundamental ecological cycles. This paper reviews the form and extent of the human alteration of natural light cycles, key consequences for terrestrial and aquatic ecosystems, interactions and synergies with other anthropogenic environmental pressures, major uncertainties, and future prospects and management options. Several of these topics have not previously been well developed. As a synthesis, this is an illustrative rather than an exhaustive compilation of relevant studies, which are numerous but highly scattered within the literature (see Rich and Longcore 2006; Hölker et al. 2010; Perkin et al. 2011; Gaston et al. 2012, 2013; Bogard 2013; Gaston and Bennie 2014).
Human alteration of natural light cycles
These daily, annual and lunar geophysical cycles have also remained rather invariant over long periods of time. For example, the Earth’s period of revolution around the Sun has been effectively constant. Its period of rotation around its axis, presently 24 h, has experienced deceleration, such that day length has increased through geological time, from ~21 h at the beginning of the Cambrian (Wells 1963). However, this amounts to a rate of increase only of ~0.002 s per century (Wahr 1988). This background means that ALAN is rather unusual amongst anthropogenic environmental pressures. Most others (e.g. changes in CO2, precipitation, temperature) have historical analogues, having previously altered naturally over geological or evolutionary time in similar ways to those presently experienced, albeit often at different rates. The most fundamental human-caused change to light cycles has two key characteristics, changes in the spatial and temporal occurrence of light and changes in its spectrum.
Changing occurrence of light
Light emissions detected from satellite imagery and aerial surveys can bear complex relations to those experienced at ground level. Key features of ALAN on the ground include a marked degree of spatial heterogeneity, with maximum values of intensity in areas of direct illumination, complex patterns of shading on the ground surface due to the number and location of light sources, and large areas affected by lower intensity illumination from reflected and scattered light in the atmosphere. It varies markedly in intensity, with areas such as sports fields and parking lots often lit to illuminance values of several hundred lux or above, ground-level illuminance in the vicinity of street lights around 10–40 lux and reduced to <1 lux several metres away.
ALAN that is emitted or reflected upwards can be scattered by water, dust and gas molecules in the atmosphere, resulting in skyglow. Studies of sky irradiance have been made for individual sites, sets of sites, and cities (Kyba et al. 2011a, b; Biggs et al. 2012; Davies et al. 2013). Skyglow can be detected over a much wider area than direct artificial lighting—extending tens and perhaps hundreds of kilometres from the source—particularly because of the contribution of light that is emitted or reflected upward at relatively shallow angles to the horizontal (Crawford 2000). Local levels tend to be closely associated with prevailing land use, being greater in more highly developed areas and declining away from these (Garstang 1986; Crawford 2000; Biggs et al. 2012). It can attain levels of up to 0.2–0.5 lux (Kurtze 1974; Eisenbeis 2006), and under cloudy conditions in urban areas skyglow has been shown to be of an equivalent or greater magnitude than high-elevation summer moonlight (Kyba et al. 2011b). Indeed, cloud cover (which varies markedly; Fig. 2d) increases ALAN, the reverse of what happens during daytime (Kyba et al. 2011b). On clear nights skyglow reduces the visibility of stars and other celestial objects (Kyba et al. 2013).
Modelling techniques enable global sky brightness estimates to be obtained using satellite imagery of nighttime lights (e.g. Cinzano et al. 2001; Cinzano and Elvidge 2004). One such exercise estimated that at the turn of the twenty-first century about two-thirds of the global human population already lived in areas where sky brightness is above the threshold set for polluted status, about one fifth had lost naked-eye visibility of the Milky Way, and for about a tenth sky brightness was such they no longer viewed nighttime skies with the eye adapted to night vision (Cinzano et al. 2001).
Changing spectra of light
Sources of change
There is a diversity of principal public and private sources of ALAN.
Street lighting appears from satellite and aerial imagery to be the dominant terrestrial source of ALAN, albeit not that with the most intense emissions (Kuechly et al. 2012). To some extent this is because street lights are more prone to upward unshielded or reflected light emissions, but it also results from the huge numbers of such lights and the lighting being unconstrained by other factors (e.g. lighting from within buildings is filtered through windows). Good estimates of the actual numbers of street lights appear to be lacking, although one recent figure suggests there are ca. 60 million in EU countries alone (Van Tichelen et al. 2007). However, the global paved road network, much of which is typically lit at night, is estimated at 18,015,713 km (CIA 2011), giving some indication of the potential extent of this source of ALAN.
The internal and, particularly, external lighting of buildings contributes substantially to nighttime views of major cities and conurbations, rendering some iconic in this regard (e.g. Paris, Las Vegas, Hong Kong, Shanghai). Urban areas are typically defined in terms of the level of coverage by buildings and associated infrastructure. Estimates of urban land cover are highly variable (Gaston 2010), but typical global figures are of the order of 2–3 % of land [excluding permanent ice cover (e.g. Millennium Ecosystem Assessment 2005)]. However, regional coverage may be substantially larger; figures for 165 countries vary from close to zero to 32 % (World Resources Institute 2007).
Terrestrially, the headlights of road vehicles produce substantial quantities of ALAN. On all but the busiest roads these emissions are temporally highly variable, occur predominantly in the horizontal plane, and are thus underestimated from satellite and aerial imagery. The orientation of these emissions means they may propagate over long distances. They have also progressively increased with major developments in headlight technology (Mainster and Timberlake 2003). Globally, in 2012 there were an estimated 833,342,000 passenger cars and 309,888,000 commercial vehicles (Organisation Internationale des Constructeurs d'Automobiles 2014), although it is unclear what proportion of these are used at night and with what frequency. The ecological impacts of ALAN from traffic has been little explored (Lyytimäki et al. 2012).
In the marine environment, significant ALAN is produced by shipping and offshore infrastructure such as oil and gas platforms. Particular attention has been paid to that generated by fishing fleets [especially those employing banks of lights to attract squid (e.g. Kiyofuji and Saitoh 2004; Elvidge et al. 2001)]. Although these lights are transient, much shipping is aggregated along common routes around coastlines and across oceans (Kareiva et al. 2007), and fishing fleets whilst operating over much larger extents tend disproportionately to focus activities on quite constrained areas (Jennings and Lee 2012).
Effects on terrestrial ecosystems
Natural light cycles influence the timings of numerous physiological processes. In many animals melatonin plays a key role in this (Vivien-Roels and Pévet 1993; Arendt 1998). Exposure either to even brief periods of high-intensity ALAN, or to prolonged periods of low intensity, has been shown in the laboratory to be capable of substantially altering patterns of circadian clock gene expression and melatonin production (e.g. Dauchy et al. 1997; Bedrosian et al. 2013; Schwimmer et al. 2014). In turn this can result in changes in expression of heat shock proteins, cortisol production and immune function, and increased risk of cancer (e.g. Dauchy et al. 1997; Bedrosian et al. 2011, 2013; Ashkenazi and Haim 2012; Schwimmer et al. 2014). This suggests that wild populations may also experience significant health impacts from ALAN. As yet, empirical evidence remains largely lacking, but so do studies whose goal is to obtain this evidence.
Effects on aquatic ecosystems
The effects of ALAN on aquatic ecosystems, whether freshwater or marine, have been much less frequently studied than for terrestrial ecosystems (for reviews see Montevecchi 2006; Moore et al. 2006; Nightingale et al. 2006; Perkin et al. 2011; Davies et al. 2014). This is logical in as much as the majority of sources of ALAN are themselves terrestrial, and a greater proportion of the land mass is subject to ALAN than of the oceans. However, the high proportion of the global human population that is distributed close to major watercourses, lakes and along coasts (Small and Cohen 2004) suggests that some kinds of aquatic ecosystems may be disproportionately subject to ALAN (e.g. Aubrecht et al. 2008; Davies et al. 2014). Although many of the same influences are associated both with terrestrial and aquatic ecosystems, again, we highlight selected issues that are emerging, in our opinion, as likely to be of key significance for the latter.
Natural light regimes, and notably lunar cycles, are used widely by marine organisms, either in isolation or in combination with other environmental cues, to time key reproductive activities. These organisms include polychaetes, cnidarians, echinoderms, and arthropods (e.g. Rudloe 1980; Lessios 1991; Tanner 1996; Bentley et al. 1999; Naylor 1999; Mercier et al. 2007; Harrison 2011). ALAN has significant potential to provide misleading information about when to time these reproductive activities, particularly for species reproducing in coastal waters. In turn, this could reduce synchrony of these activities amongst individuals (with consequences for fertilization success, predator satiation, etc.), and interactions with other important environmental phenomena, such as oceanographic processes and resource availability.
Much attention has been paid to the influence of ALAN on the movements of organisms in terrestrial ecosystems (e.g. Frank 1988; Beier 1995; Gauthreaux and Belser 2006; Rydell 2006; Stone et al. 2009; Polak et al. 2011). However, patterns of light are arguably more important cues for movement in aquatic systems, where alternatives (e.g. use of landmarks) may often be severely lacking (Davies et al. 2014). Indeed, ALAN has already been shown to influence the movements (local, dispersive, migratory) of aquatic groups as diverse as zooplankton (Moore et al. 2000), fish (Ryer et al. 2009; Riley et al. 2012, 2013), turtles (Philibosian 1976; Lorne and Salmon 2007; Bourgeois et al. 2009) and birds (Telfer et al. 1987; Rodríguez and Rodríguez 2009; Rodrigues et al. 2012; Rodríguez et al. 2012a, b). Of particular concern is the extent to which ALAN impacts on the vertical diel movements of zooplankton, which are argued to constitute the largest synchronized movement of biomass globally, with huge impacts on carbon cycling and ecosystem functioning. These diel movements have been found to occur even during the polar night, regulated by variation in light intensity at levels below the threshold of human perception (Berge et al. 2009). This suggests that such movements may be highly susceptible to ALAN.
Effects of ALAN on births and deaths of species and/or their movements will result in shifts in community structure. Because the influences on demographic rates are likely to be site, time and species specific (Gaston and Bennie 2014), and to lead to shifts in competitive and predator–prey interactions, it is virtually impossible to predict a priori the form that these changes in community structure will take, and they are likely to appear quite idiosyncratic. Nonetheless, these changes have indeed been documented. For example, Meyer and Sullivan (2013) detail changes in the taxonomic and functional composition of aquatic and terrestrial invertebrate communities when natural streams were experimentally subjected to ALAN, reflecting changes in the fluxes between the two faunas. Likewise, Becker et al. (2013) document changes in the trophic and size structure of estuarine fish assemblages when artificial lighting conditions were manipulated. Given the links between community structure and composition and ecosystem functions and processes, ALAN will inevitably impact the latter, although to our knowledge these effects remain to be documented.
Interactions and synergies
ALAN is, of course, only one of many anthropogenic pressures to which natural environments are subject, including habitat loss and fragmentation, climate change, excessive nutrient load and other forms of pollution, overexploitation and unsustainable use, and invasive alien species. One could potentially ask how ALAN compares in terms of the relative impact that it has. However, given that the different pressures seldom act in isolation it seems more pertinent to consider their interactions and synergies with ALAN. Here we highlight several such possibilities.
Habitat loss and fragmentation
Most consideration of levels of habitat loss and fragmentation and their effects on ecosystems and biodiversity pertains to structural changes, such as in different kinds of land cover, in the physical sizes of patches, and in their degree of connectivity or isolation (Hanski 2005). ALAN can exacerbate these effects in ways that are not apparent from the daylight images (from aerial photographs and satellite sensors) that are typically employed to make such assessments. It renders areas of structurally unaltered habitat unusable by some organisms, available to others, and creates barriers to or corridors for movement that fragment and connect landscapes in different ways (Beier 1995, 2006; Eisenbeis 2006; Frank 2006; Stone et al. 2012; Threlfall et al. 2013). Indeed, full understanding of habitat loss and fragmentation needs to account both for diurnal and nocturnal effects, which may be rather different. Given the high proportion of species that are nocturnal (in addition to those that are crepuscular and cathemeral) in some groups of major conservation concern [e.g. 69 % of mammals (Bennie et al. 2014b)], it seems likely that the full impact of habitat loss and fragmentation has often been markedly underestimated.
It has previously been observed that biotic responses to anthropogenic climate change are critically dependent on the fact that whilst temperatures are changing, geographic and annual patterns in natural light cycles are not (Bradshaw and Holzapfel 2010). Given that organisms use day length as a cue for anticipating seasonal changes, this creates strong selection pressures for altering the timing of seasonal events, some of which they are able to respond to and some of which they are not (Bradshaw and Holzapfel 2010). ALAN serves to complicate this picture. Typically it serves locally to extend apparent day lengths, and to obscure their seasonal patterns. In combination, higher temperatures and increased light levels at night may allow species that are able to utilize the night light niche to extend their hours of activity (Garber 1978; Heiling 1999) and may alter predation patterns and/or competitive interactions.
Other forms of pollution
ALAN can be seen as a stressor on the physiologies of many organisms, particularly as mediated through melatonin production. It seems likely that this will be more challenging to deal with in the presence of other forms of pollution, which are imposing other demands. ALAN can also exacerbate other forms of pollution in a more direct fashion. Stark et al. (2011) showed that artificial lights can change nighttime atmospheric nitrogen chemistry. Dim nocturnal light has also been found to inhibit recovery from leaf damage caused by atmospheric ozone in some species of clover Trifolium (Futsaether et al. 2009; Vollsnes et al. 2009).
Overexploitation and unsustainable use
The harvesting of many marine species (e.g. shrimp, squid, fish) employs the use of artificial nighttime lights as attractants, sometimes on an industrial scale (Kiyofuji and Saitoh 2004). The effects of this source of ALAN on unexploited organisms is largely unknown; however, it seems likely to be potentially marked, particularly given the responsiveness of most marine organisms to light. Some forms of terrestrial harvesting, such as spotlighting, also employ ALAN, but this is on a more localized and transient scale.
Invasive alien species
Several examples exist of invasive alien species that have rapidly adapted photoperiodic responses to their new environment [over a few decades (Gomi and Takeda 1991; Urbanski et al. 2012)]. The ability to adapt phenology to changing light regimes may be a key determinant of success in colonizing latitudes outside of a species’ historical range (Bradshaw and Holzapfel 2010), which is critical when species are introduced to new regions or spread due to climate change. Such phenotypic flexibility in photoperiodism may also be important in species response to extended hours of light due to ALAN.
What are the biological effects of skyglow resulting from ALAN? Whilst the effects of more direct lighting are increasingly well understood, those of skyglow remain poorly explored. Studies to do so are challenging, although suggestions as to how these might be constructed have been made (Kyba and Hölker 2013).
What are the effects of ALAN on photosynthesis? The widespread use of artificial lighting in growing plants under controlled conditions suggests the potential for ALAN to influence photosynthesis. However, studies of these impacts, and of those on the photophysiology of plants and phytoplankton more broadly, remain scarce and it is difficult to extract any broad conclusions (Gaston et al. 2013; Poulin et al. 2013).
Do the influences of ALAN on stress and disease demonstrated for animals in the laboratory extend to the wild? Particularly because of concerns about effects of ALAN on human health, more laboratory studies of potential ecological relevance have been conducted than for most ecological issues. However, there are undoubtedly large differences between the ALAN treatments used in laboratory settings and what the majority of organisms experience in the field, especially when those organisms are mobile.
What shape are dose–response curves for ALAN? The literature on the ecological effects of ALAN is dominated by studies in which comparison is made, observationally or experimentally, between the state of a given ecological variable with and without ALAN, or perhaps with two different forms of ALAN (usually differing in intensity, but sometimes light spectrum). Almost nothing is known about the form of dose–response curves for ALAN, and thus critically how responses are likely to change when ALAN attains different levels.
What are the impacts of ALAN on ecosystem functions and processes? Broadly speaking, most is known about the impacts of ALAN on the physiology and behaviour of organisms, less about those on population dynamics, little about those on communities, and almost nothing about the impacts on ecosystem functions and processes. Given that ALAN can influence the abundances of species and trophic interactions there seems little doubt that such effects on ecosystem functions and processes do occur.
Future prospects and management options
Central management systems in developed countries by which the timing and intensity of grid-based lighting can be controlled, already resulting in some broad-scale decreases in lighting during periods when it is not needed (Bennie et al. 2014a);
White light technologies, especially LEDs. LEDs can be modified to control the spectral composition of lighting, can require lower wattage for a given level of illumination than more traditional light sources, provide high light output for low radiant heat, can distribute light more uniformly and thus allow lower levels of lighting to be employed, are dimmable and more tolerant of switching on and off, and have long life times before failure (US Department of Energy 2012). Typical white LEDs emit considerably more light in the blue portion of the spectrum than conventional ‘white’ lighting (Fig. 4); while LED technology may allow more control over the spectra emitted, a movement towards white LED-based lighting systems is likely to lead to greater emissions within the blue portion of the spectra. LEDs also raise concerns around hazardous waste and resource depletion (Lim et al. 2011).
Off-grid lighting in developing countries, likely principally using combinations of LEDs and solar power (Mills 2005).
Maintaining and creating dark areas. Faced with progressive loss of dark areas, particularly in more heavily urbanized regions it is important to protect those that remain and where possible recover others. There are a number of initiatives to identify presently dark areas, to highlight this status, and to encourage steps by which it is maintained [UNESCO 2009; International Dark Sky Association (IDSA) 2013; IUCN 2013]. There are also initiatives to encourage communities to reduce their overall levels of ALAN (IDSA 2001). Even quite localized changes (e.g. switching off a few key lights) can serve to reduce particular impacts (e.g. Yurk and Trites 2000).
Reducing light trespass. Lighting devices generally remain quite poorly designed and/or managed for the purposes of only directing light where it is actually required. Resolving this problem provides a ready means of dramatically decreasing the impacts of ALAN at a local scale. Indeed, reduction of light trespass has been shown to reduce the impacts of ALAN on organisms (e.g. Reed et al. 1985).
Dimming. Many areas are overlit compared with what is practically required. This provides opportunities for dimming of lighting without major negative consequences for human populations. Indeed, substantial progressive dimming may be possible without these populations being able to perceive that this is the case. The introduction of LED lighting provides further opportunities, given that colour rendering may be improved at lower intensities of lighting.
Part-night lighting. Many areas are presently lit at times of day when this carries limited or negligible human benefit. Particularly following the global financial crisis, and pressure on public expenditure, numerous towns and cities have sought to reduce energy costs (and CO2 emissions) by switching off street lights in low-risk areas from late at night until the early hours of the morning (Gaston et al. 2012). The ecological benefits of such part-night lighting remain poorly understood, and may only influence a relative minority of species that use the heart of the night rather than hours around dusk and dawn.
Targeting spectra. There are doubtless substantial opportunities to reduce the ecological impacts of ALAN by employing spatially more nuanced approaches to the use of lighting with different spectral properties. Developing alternatives to presently installed systems, which have often evolved as different technologies have become available and affordable, will require balancing of multiple pressures. These include cost, practicality, human perceived and actual need, and environmental concerns. In general, there would seem to be a number of advantages to the use of reddened spectra in environmentally more sensitive areas because, relative to white or blue sources, these reduce skyglow (Kyba et al. 2012), penetrate the water column to a lesser extent, have less influence on melatonin levels and circadian rhythms of species (Bayarri et al. 2002; Lockley et al. 2003), are less attractive to some organisms (e.g. Evans et al. 2007b; Cowan and Gries 2009; Somers-Yeates et al. 2013) and less repellent to others (e.g. Downs et al. 2003, Widder et al. 2005). However, this is not always the case—reddened light may disrupt the magnetic orientation of migratory birds (Wiltschko et al. 1993) and light of lower wavelengths may be less disruptive to these species (Poot et al. 2008). Furthermore, reddened light sources have a stronger influence on plant development through the impact on phytochromes, which respond to the ratio of red to far red light (Stutte 2009).
Arguably, there is a trade-off between the economic costs and the perceived social costs associated with implementing these different strategies to managing ALAN. This constitutes the major challenge to limiting its ecological impacts.
We are grateful to two anonymous reviewers for their comments on a previous version of the manuscript, and to S. Rouillard for assistance with figures. The research leading to this paper has received funding from the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007–2013)/ERC grant agreement no. 268504 to K. J. G.
- Amaral S, Monteiro AMV, Camara G, Quintanilha JA (2006) DMSP/OLS night-time light imagery for urban population estimates in the Brazilian Amazon. Int J Remote Sens 27:855–870Google Scholar
- Arlettaz R, Godat S, Meyer H (2000) Competition for food by expanding pipistrelle bat populations (Pipistrellus pipistrellus) might contribute to the decline of lesser horseshoe bats (Rhinolophus hipposideros). Biol Conserv 93:55–60Google Scholar
- Aubrecht C, Elvidge CD, Longcore T, Rich C, Safran J, Strong AE, Eakin CM, Baugh K, Tuttle BT, Howard AT, Erwin EH (2008) A global inventory of coral reef stressors based on satellite observed nighttime lights. Geocarto Int 23:467–479Google Scholar
- Bakken LE, Bakken GS (1977) American redstart feeding by artificial light. Auk 94:373–374Google Scholar
- Ball JR, Lukianchuk K, Bayne EM (2011) Nocturnal provisioning by Swainson’s thrush. Wilson J Ornithol 123:508–514Google Scholar
- Basler D, Körner C (2012) Photoperiod sensitivity of bud burst in 14 temperate forest tree species. Agric For Meteorol 165:73–81Google Scholar
- Becker A, Whitfield AK, Cowley PD, Järnegren J, Næsje TF (2013) Potential effects of artificial light associated with anthropogenic infrastructure on the abundance and foraging behaviour of estuary-associated fishes. J Appl Ecol 50:43–50Google Scholar
- Beier P (1995) Dispersal of juvenile cougars in fragmented habitat. J Wildl Manage 59:228–237Google Scholar
- Beier P (2006) Effects of artificial night lighting on terrestrial mammals. In: Rich C, Longcore T (eds) Ecological consequences of artificial night lighting. Island Press, Washington, pp 19–42Google Scholar
- Bennie J, Duffy JP, Inger R, Gaston KJ (2014b) The biogeography of time partitioning in mammals. Proc Nat Acad Sci USA (in press)Google Scholar
- Bentley MG, Olive PJW, Last K (1999) Sexual satellites, moonlight and the nuptial dances of worms: the influence of the moon on the reproduction of marine animals. Earth Moon Planets 85–86:67–84Google Scholar
- Biggs JD, Fouche T, Bilki F, Zadnik MG (2012) Measuring and mapping the night sky brightness of Perth, Western Australia. Mon Not R Astron Soc 421:1450–1464Google Scholar
- Bird BL, Branch LC, Miller DL (2004) Effects of coastal lighting on foraging behavior of beach mice. Conserv Biol 18:1435–1439Google Scholar
- Bishop JE (1969) Light control of aquatic insect activity and drift. Ecology 50:371–380Google Scholar
- Bogard P (2013) The end of night: searching for natural darkness in an age of artificial light. Fourth Estate, LondonGoogle Scholar
- Boldogh S, Dobrosi D, Samu P (2007) The effects of the illumination of buildings on house-dwelling bats and its conservation consequences. Acta Chiropterol 9:527–534Google Scholar
- Bourgeois S, Gilot-Fromont E, Viallefont A, Boussamba F, Deem SL (2009) Influence of artificial lights, logs and erosion on leatherback sea turtle orientation at Pongara National Park, Gabon. Biol Conserv 142:85–93Google Scholar
- CIA (2011) The world factbook. https://www.cia.gov/library/publications/the-world-factbook/index.html
- Cinzano P, Elvidge CD (2004) Night sky brightness at sites from DMSP-OLS satellite measurements. Mon Not R Astron Soc 353:1107–1116Google Scholar
- Cinzano P, Falchi F, Elvidge CD (2001) The first world atlas of the artificial night sky brightness. Mon Not R Astron Soc 328:689–707Google Scholar
- Clarke JA, Chopko JT, Mackessy SP (1996) The effect of moonlight on activity patterns of adult and juvenile prairie rattlesnakes (Crotalus viridis viridis). J Herpetol 2:192–197Google Scholar
- Cowan T, Gries G (2009) Ultraviolet and violet light: attractive orientation cues for the Indian meal moth, Plodia interpunctella. Entomol Exp Appl 131:148–158Google Scholar
- Crawford DL (2000) Light pollution, an environmental problem for astronomy and for mankind. Mem Soc Astron Ital 71:11–40Google Scholar
- Davies TW, Duffy J, Bennie J, Gaston KJ (2014) Marine light pollution: nature, extent and ecological implications. Frontiers Ecol Environ 12:347–355Google Scholar
- Dice LD (1945) Minimum intensities of illumination under which owls can find dead prey by sight. Am Nat 79:385–416Google Scholar
- DMSP/OLS (2012) Night time lights data set (Version 4). NOAA Earth Observation Group, Boulder, CO. http://ngdc.noaa.gov/eog/dmsp/downloadV4composites.html. Accessed Oct 2012
- Doll CNH, Muller J-P, Morley JG (2006) Mapping regional economic activity from night-time light satellite imagery. Ecol Econ 57:75–92Google Scholar
- Dominoni DM, Carmona-Wagner EO, Hofmann M, Kranstauber B, Partecke J (2014) Individual-based measurements of light intensity provide new insights into the effects of artificial light at night on daily rhythms of urban-dwelling songbirds. J Anim Ecol 83:681–692Google Scholar
- Downs NC, Beaton V, Guest J, Polanski J, Robinson SL, Racey PA (2003) The effects of illuminating the roost entrance on the emergence behavior of Pipistrellus pygmaeus. Biol Conserv 111:247–252Google Scholar
- Eisenbeis G (2006) Artificial night lighting and insects: attraction of insects to streetlamps in a rural setting in Germany. In: Rich C, Longcore T (eds) Ecological consequences of artificial night lighting. Island Press, Washington, pp 281–304Google Scholar
- Elvidge CD, Baugh KE, Dietz JB, Bland T, Sutton PC, Kroehl HW (1999) Radiance calibration of DMSP-OLS low-light imaging data of human settlements. Remote Sens Environ 68:77–88Google Scholar
- Elvidge CD, Imhoff ML, Baugh KE, Hobson VR, Nelson I, Safran J, Dietz JB, Tuttle BT (2001) Night-time lights of the world: 1994–1995. ISPRS J Photogramm Remote Sens 56:L81–L99Google Scholar
- Evans WR, Akashi Y, Altman NS, Manville AM II (2007b) Response of night-migrating songbirds in cloud to colored and flashing light. North Am Birds 60:476–488Google Scholar
- Falkenberg JC, Clarke JA (1998) Microhabitat use of deer mice: effects of interspecific interaction risks. J Mamm 79:558–565Google Scholar
- Fenn MGP, Macdonald DW (1995) Use of middens by red foxes: risk reverses rhythms of rats. J Mamm 76:130–136Google Scholar
- Frank KD (1988) Impact of outdoor lighting on moths: an assessment. J Lepid Soc 42:63–93Google Scholar
- Frank KD (2006) Effect of artificial night lighting on moths. In: Rich C, Longcore T (eds) Ecological consequences of artificial night lighting. Island Press, Washington, pp 305–344Google Scholar
- Garber SD (1978) Opportunistic feeding behaviour of Anolis cristatellus (Iguanidae: Reptilia) in Puerto Rico. Trans Kansas Acad Sci 81:19–80Google Scholar
- Garstang RH (1986) Model for artificial night-sky illumination. Publ Astron Soc Pacific 98:364–375Google Scholar
- Gaston KJ (2010) Urbanisation. In: Gaston KJ (ed) Urban ecology. Cambridge University Press, Cambridge, pp 10–34Google Scholar
- Gaston KJ, Bennie J (2014) Demographic effects of artificial nighttime lighting on animal populations. Environ Rev (in press)Google Scholar
- Gauthreaux SA Jr, Belser CG (2006) Effects of artificial night lighting on migrating birds. In: Rich C, Longcore T (eds) Ecological consequences of artificial night lighting. Island Press, Washington, pp 67–93Google Scholar
- Gomi T, Takeda M (1991) Geographic variation in photoperiodic responses in an introduced insect, Hyphantria cunea Drury (Lepidoptera: Arctiidae) in Japan. Appl Entomol Zool 26:357–363Google Scholar
- Grant R, Halliday T, Chadwick E (2012) Amphibians’ response to the lunar synodic cycle—a review of current knowledge, recommendations, and implications for conservation. Behav Ecol 24:53–62Google Scholar
- Hanski I (2005) The shrinking world: ecological consequences of habitat loss. International Ecology Institute, OldendorfGoogle Scholar
- Harrison PL (2011) Sexual reproduction of scleractinian corals. In: Dubinsky Z, Stambler N, Harrison PL (eds) Coral reefs: an ecosystem in transition. Springer, Dordrecht, pp 59–85Google Scholar
- Heiling AM (1999) Why do nocturnal orb-web spiders (Araneidae) search for light? Behav Ecol Sociobiol 46:43–49Google Scholar
- Hölker F, Moss T, Griefahn B, Kloas W, Voigt CC, Henckel D, Hänel A, Kappeler PM, Völker S, Schwope A, Franke S, Uhrlandt D, Fischer J, Klenke R, Wolter C, Tockner K (2010) The dark side of light: a transdisciplinary research agenda for light pollution policy. Ecol Soc 15:13Google Scholar
- IDSA (2001) International dark sky communities—guidelines. www.darksky.org/international-dark-sky-places
- IDSA (2013) Dark sky park program criteria. www.darksky.org
- IUCN (2013) World list of dark sky protected areas. IUCN Dark Skies Advisory Group. www.darkskyparks.org
- Jennings S, Lee J (2012) Defining fishing grounds with vessel monitoring system data. ICES J Mar Sci 69:51–63Google Scholar
- Johnson K (1979) Control of lampenflora at Waitomo Caves, New Zealand. Cave management in Australia III: proceedings of the 3rd Australasian Cave Tourism and Management Conference, Mount Gambier. South Australian National Parks and Australian Speleological Federation, Adelaide, pp 105–122Google Scholar
- Kiyofuji H, Saitoh S-I (2004) Use of nighttime visible images to detect Japanese common squid Todarodes pacificus fishing areas and potential migration routes in the Sea of Japan. Mar Ecol Prog Ser 276:173–186Google Scholar
- Kramer KM, Birney EC (2001) Effect of light intensity on activity patterns of Patagonian leaf-eared mice, Phyllotis xanthopygus. J Mamm 82:535–544Google Scholar
- Kuechly HU, Kyba CCM, Ruhtz T, Lindemann C, Wolter C, Fischer J, Hölker F (2012) Aerial survey and spatial analysis of sources of light pollution in Berlin, Germany. Remote Sens Environ 126:39–50Google Scholar
- Kuijper DPJ, Schut J, van Dullemen D, Toorman H, Goossens N, Ouwehand J, Limpens HJGA (2008) Experimental evidence of light disturbance along the commuting routes of pond bats (Myotis dasycneme). Lutra 51:37–49Google Scholar
- Kurtze W (1974) Synökologische und experimentelle Untersuchungen zur Nachtaktivität von Insekten. Zool Jahrb Abt Syst Ökol Geogr Tier 101:297–344Google Scholar
- Kyba CCM, Hölker F (2013) Do artificially illuminated skies affect biodiversity in nocturnal landscapes? Landsc Ecol 28:1637–1640Google Scholar
- Kyba CCM, Ruhtz T, Fischer J, Hölker F (2011a) Lunar skylight polarization signal polluted by urban lighting. J Geophys Res D 116:D24106Google Scholar
- Kyba CCM, Ruhtz T, Fischer J, Hölker F (2012) Red is the new black: how the colour of urban skyglow varies with cloud cover. Mon Not R Astron Soc 425:701–708Google Scholar
- Larsen LO, Pedersen JN (1982) The snapping response of the toad Bufo bufo, towards prey dummies at very low light intensities. Amphib-Reptil 2:321–327Google Scholar
- Lebbin DJ, Harvey MG, Lenz TC, Andersen MJ, Ellis JM (2007) Nocturnal migrants foraging at night by artificial light. Wilson J Ornith 119:506–508Google Scholar
- Lessios HA (1991) Presence and absence of monthly reproductive rhythms among eight Caribbean echinoids off the coast of Panama. J Exp Mar Biol Ecol 153:27–47Google Scholar
- Levin N, Duke Y (2012) High spatial resolution night-time images for demographic and socio-economic studies. Remote Sens Environ 119:1–10Google Scholar
- Li X, Chen X, Zhao Y, Xu J, Chen F, Li H (2012) Automatic intercalibration of night-time light imagery using robust regression. Remote Sens Lett 4:46–55Google Scholar
- Lockley SW, Brainard GC, Czeisler CA (2003) High sensitivity of the human circadian melatonin rhythm to resetting by short wavelength light. J Clin Endocrin Metabolism 88:4502–4505Google Scholar
- Longcore T, Rich C (2004) Ecological light pollution. Front Ecol Environ 2:191–198Google Scholar
- Longcore T, Rich C (2006) Synthesis. In: Rich C, Longcore T (eds) Ecological consequences of artificial night lighting. Island Press, Washington, pp 413–430Google Scholar
- Lorne JK, Salmon M (2007) Effects of exposure to artificial lighting on orientation of hatchling sea turtles on the beach and in the ocean. Endanger Sp Res 3:23–30Google Scholar
- Lyytimäki J, Tapio P, Assmuth T (2012) Unawareness in environmental protection: the case of light pollution from traffic. Land Use Policy 29:598–604Google Scholar
- Mainster MA, Timberlake GT (2003) Why HID headlights bother older drivers. Br J Opthalmol 87:113–117Google Scholar
- Mazor T, Levin N, Possingham HP, Levy Y, Rocchini D, Richardson AJ, Kark S (2013) Can satellite-based night lights be used for conservation? The case of nesting sea turtles in the Mediterranean. Biol Conserv 159:63–72Google Scholar
- Meeus J (2008) Astronomical formulae for calculators, 4th edn. Atlantic Books, LondonGoogle Scholar
- Mercier A, Ycaza RH, Hamel JF (2007) Long-term study of gamete release in a broadcast-spawning holothurian: predictable lunar and diel periodicities. Mar Ecol Prog Ser 329:179–189Google Scholar
- Millennium Ecosystem Assessment (2005) Ecosystems and human well-being: current state and trends, vol I. Island Press, WashingtonGoogle Scholar
- Miller MW (2006) Apparent effects of light pollution on singing behavior of American robins. Condor 108:130–139Google Scholar
- Montevecchi WA (2006) Influences of artificial light on marine birds. In: Rich C, Longcore T (eds) Ecological consequences of artificial night lighting. Island Press, Washington, pp 94–113Google Scholar
- Moore MV, Pierce SM, Walsh HM, Kvalvik SK, Lim JD (2000) Urban light pollution alters the diel vertical migration of Daphnia. Verh Int Ver Limnol 27:779–782Google Scholar
- Moore MV, Kohler SJ, Cheers MS (2006) Artificial light at night in freshwater habitats and its potential ecological effects. In: Rich C, Longcore T (eds) Ecological consequences of artificial night lighting. Island Press, Washington, pp 365–384Google Scholar
- NASA (2012) LIS/OTD gridded lightning climatology data set. NASA EoSDIS GHRC DAAC, Huntsville, AL. http://lightning.nsstc.nasa.gov/data/. Accessed October 2012
- NASA Land Processes Distributed Active Archive Center (LP DAAC) (2013) MOD14A1. USGS/Earth Resources Observation and Science (ERO) Center, Sioux Falls, SDGoogle Scholar
- Naylor E (1999) Marine animal behaviour in relation to lunar phase. Earth Moon Planets 85–86:291–302Google Scholar
- Nightingale B, Longcore T, Simenstad CA (2006) Artificial night lighting and fishes. In: Rich C, Longcore T (eds) Ecological consequences of artificial night lighting. Island Press, Washington, pp 257–276Google Scholar
- Organisation Internationale des Constructeurs d'Automobiles (OICA (2014) http://www.oica.net/category/vehicles-in-use/
- Perkin EK, Hö̈lker F, Richardson JS, Sadler JP, Wolter C, Tockner K (2011) The influence of artificial light on stream and riparian ecosystems: questions, challenges, and perspectives. Ecosphere 2:122Google Scholar
- Philibosian R (1976) Disorientation of hawksbill turtle hatchlings, Eretmochelys imbricata, by stadium lights. Copeia 1976:824Google Scholar
- Picchi MS, Avolio L, Azzani L, Brombin O, Camerini G (2013) Fireflies and land use in an urban landscape: the case of Luciola italica L. (Coleoptera: Lampyridae) in the city of Turin. J Insect Conserv 17:797–805Google Scholar
- Pita R, Mira A, Beja P (2011) Circadian activity rhythms in relation to season, sex and interspecific interactions in two Mediterranean voles. Anim Behav 81:1023–1030Google Scholar
- Polak T, Korine C, Yair S, Holderied MW (2011) Differential effects of artificial lighting on flight and foraging behaviour of two sympatric bat species in a desert. J Zool 285:21–27Google Scholar
- Poot H, Ens BJ, de Vries H, Donners MAH, Wernand MR, Marquenie JM (2008) Green light for nocturnally migrating birds. Ecol Soc 13(2):47Google Scholar
- Poulin C, Bruyant F, Laprise M-H, Cockshutt AM, Vandenhecke JM-R, Huot Y (2013) The impact of light pollution on diel changes in the photophysiology of Microcystis aeruginosa. J Plankton Res 36:286–291Google Scholar
- Pun CSJ, So CW (2011) Night-sky brightness monitoring in Hong Kong: a city-wide light pollution assessment. Environ Mon Assess 184:2537–2557Google Scholar
- Reed JR, Sincock JL, Hailman JP (1985) Light attraction in endangered procellariiform birds: reduction by shielding upward radiation. Auk 102:377–383Google Scholar
- Rich C, Longcore T (eds) (2006) Ecological consequences of artificial night lighting. Island Press, WashingtonGoogle Scholar
- Riley WD, Bendall B, Ives MJ, Edmonds NJ, Maxwell DL (2012) Street lighting disrupts the diel migratory pattern of wild Atlantic salmon, Salmo salar L., smolts leaving their natal stream. Aquaculture 330–333:74–81Google Scholar
- Riley WD, Davison PI, Maxwell DL, Bendall B (2013) Street lighting delays and disrupts the dispersal of Atlantic salmon (Salmo salar) fry. Biol Conserv 158:140–146Google Scholar
- Rodrigues P, Aubrecht C, Gil A, Longcore T, Elvidge C (2012) Remote sensing to map influence of light pollution on Cory’s shearwater in Sao Miguel Island, Azores Archipelago. Eur J Wildl Res 58:147–155Google Scholar
- Rodríguez A, Rodríguez B (2009) Attraction of petrels to artificial lights in the Canary Islands: effects of the moon phase and age class. Ibis 151:299–310Google Scholar
- Rodríguez A, Rodríguez B, Curbelo ÁJ, Pérez A, Marrero S, Negro JJ (2012a) Factors affecting mortality of shearwaters stranded by light pollution. Anim Conserv 15:519–526Google Scholar
- Rodríguez A, Rodríguez B, Lucas MP (2012b) Trends in numbers of petrels attracted to artificial lights suggest population declines in Tenerife, Canary Islands. Ibis 154:167–172Google Scholar
- Rudloe A (1980) The breeding behavior and patterns of movement of horseshoe crabs, Limulus polyphemus, in the vicinity of breeding beaches in Apalachee Bay, Florida. Estuaries 3:177–183Google Scholar
- Rydell J (2006) Bats and their insect prey at streetlights. In: Rich C, Longcore T (eds) Ecological consequences of artificial night lighting. Island Press, Washington, pp 43–60Google Scholar
- Ryer CH, Stoner AW, Iseri PJ, Spencer ML (2009) Effects of simulated underwater vehicle lighting on fish behavior. Mar Ecol Prog Ser 391:97–106Google Scholar
- Saikkonen K, Taulavuori K, Hyvönen T, Gundel PE, Hamilton CE, Vänninen I, Nissinen A, Helander M (2012) Climate change-driven range shifts filtered by photoperiodism. Nat Clim Change 2:239–242Google Scholar
- Salmon M, Tolbert MG, Painter DP, Goff M, Reiners R (1995) Behavior of loggerhead sea turtles on an urban beach. II. Hatchling orientation. J Herpetol 29:568–576Google Scholar
- Santos CD, Miranda AC, Granadeiro JP, Lourenco PM, Saraiva S, Palmeirim JM (2010) Effects of artificial illumination on the nocturnal foraging of waders. Acta Oecol 36:166–172Google Scholar
- Schwartz CC, Cain SL, Podruzny S, Cherry S, Frattaroli L (2010) Contrasting activity patterns of sympatric and allopatric black and grizzly bears. J Wildl Manage 74:1628–1638Google Scholar
- Sharma VK, Chandrashekaran MK, Nongkynrih P (1997) Daylight and artificial light phase response curves for the circadian rhythm in locomotor activity of the field mouse Mus booduga. Biol Rhythm Res 28(Suppl 1):39–40Google Scholar
- Small C, Cohen JE (2004) Continental physiography, climate, and the global distribution of human population. Curr Anthropol 45:269–277Google Scholar
- Small C, Elvidge CD (2011) Mapping decadal change in anthropogenic night light. Proc Environ Sci 7:353–358Google Scholar
- Small C, Elvidge CD (2013) Night on Earth: mapping decadal changes of anthropogenic night light in Asia. Int J Appl Earth Observ Geoinf 22:40–52Google Scholar
- Stark H, Brown SS, Wong KW, Stutz J, Elvidge CD, Pollack IB, Ryerson TB, Dube WP, Wagner NL, Parrish DD (2011) City lights and urban air. Nat Geosci 4:730–731Google Scholar
- Stockli R (2013) NASA’s Earth Observatory—cloud fraction imagery using data provided by the MODIS Atmospheric Science Team, NASA Goddard Space Flight Centre, MA. http://neo.sci.gsfc.nasa.gov/view.php?datasetId=MYDAL2_M_CLD_FR. Accessed November 2013
- Stone EL, Jones G, Harris S (2012) Conserving energy at a cost to biodiversity? Impacts of LED lighting on bats. Glob Change Biol 18:2458–2465Google Scholar
- Stutte GW (2009) Light-emitting diodes for manipulating the phytochrome apparatus. HortScience 44:231–234Google Scholar
- Sutton PC (2003) A scale adjusted measure of “urban sprawl” using nighttime satellite imagery. Remote Sens Environ 86:353–369Google Scholar
- Tanner J (1996) Seasonality and lunar periodicity in the reproduction of pocilloporid corals. Coral Reefs 15:59–66Google Scholar
- Telfer TC, Sincock JL, Byrd GV, Reed JR (1987) Attraction of Hawaiian seabirds to lights: conservation efforts and effects of moon phase. Wildl Soc Bull 15:406–413Google Scholar
- Threlfall CG, Law B, Banks PB (2013) The urban matrix and artificial light restricts the nightly ranging behaviour of Gould’s long-eared bat (Nyctophilus gouldi). Austral Ecol 38:921–930Google Scholar
- UNESCO (2009) Starlight reserves and world heritage: scientific, cultural and environmental values. UNESCO, ParisGoogle Scholar
- US Department of energy (2012) Light at night: the latest science. http://apps1.eere.energy.gov/buildings/publications/pdfs/ssl/ssl_whitepaper_nov2010.pdf
- Van Tichelen P, Geerken T, Jansen B, Vanden Bosch M, Van Hoof V, Vanhooydonck L, Vercalsteren A (2007) Final report lot 9: Public street lighting. http://www.eup4light.net/assets/pdffiles/Final/VITOEuPStreetLightingFinal.pdf
- Vivien-Roels B, Pévet P (1993) Melatonin: presence and formation in invertebrates. Experientia 49:642–647Google Scholar
- Wahr JM (1988) The Earth’s rotation. Annu Rev Earth Planet Sci 16:231–249Google Scholar
- Wells JW (1963) Coral growth and geochronometry. Nature 197:948–950Google Scholar
- Widder EA, Robison BH, Reisenbichler KR, Haddock SHD (2005) Using red light for in situ observations of deep-sea fishes. Deep-Sea Res I 52:2077–2085Google Scholar
- Wiltschko W, Munro U, Ford H, Wiltschko R (1993) Red light disrupts magnetic orientation of migratory birds. Nature 364:525–527Google Scholar
- World Resources Institute (2007) Available at: http://earthtrends.wri.org/index.php
- Yurk H, Trites AW (2000) Experimental attempts to reduce predation by harbor seals on out-migrating juvenile salmonids. Trans Am Fish Soc 129:1360–1366Google Scholar
Open AccessThis article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.