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Povzetek: Although several studies have focused on the influence of moonlight on deer–vehicle collisions, findings have been inconsistent. This may be due to neglect of the effects of cloud cover, a major impediment to moon illumination and circannual variation in both deer and human activity. We assessed how median cloud cover interacted with the illuminated fraction of the moon in affecting daily roe deer (Capreolus capreolus) roadkill in Slovenia (Central Europe). Data included nationwide roadkill (n = 49,259), collected between 2010 and 2019 by hunters, as required by law. Roadkill peaked under medium to high cloud cover and decreased during nights with low or extremely high cloudiness. This pattern was more pronounced on nights with a full moon. However, the effects of moon illumination and cloud cover had a lower predictive potential than circannual variation, as collisions clearly peaked in April/May, July and August/September. Our results suggest that moonlight could influence roe deer movements through compensatory foraging. However, on nights with a full moon, collisions could also be affected by weather. On bright nights, roe deer might be less active due to increased human presence and sustained vehicular traffic. Then, with medium to high cloud cover and also rainfall, human presence in the environment may be low enough to increase deer movements, but vehicular traffic can still be intermediate, maximizing the risk of collisions. Finally, with overcast skies, widespread rainfall can reduce both traffic volume and human outdoor activity, decreasing the risk of collisions. Moon illumination may indeed affect wildlife–vehicle collisions and roadkill, but its effects should be quantified as a function of cloud cover. Moreover, to make studies truly comparable, research about wildlife–vehicle collisions should also account for time of the year. Policy implications. Because collisions with roe deer peak at particular periods of the year, signs should be installed seasonally. By doing so, they would warn drivers about the risk, improve drivers' awareness and increase their safety. Moreover, as collisions also increase on nights with a full moon and overcast skies, interactive warning signs that are activated by ground illumination should also be useful.
Ključne besede: cloudiness, MODIS Surface Reflectance, moon, road ecology, roe deer, Slovenia, thin-plate splines, wildlife–vehicle collisions
Objavljeno v DiRROS: 16.11.2023; Ogledov: 334; Prenosov: 152
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Povzetek: : Phenological events are good indicators of the effects of climate change, since phenological phases are sensitive to changes in environmental conditions. Although several national phenological networks monitor the phenology of different plant species, direct observations can only be conducted on individual trees, which cannot be easily extended over large and continuous areas. Remote sensing has often been applied to model phenology for large areas, focusing mostly on pure forests in which it is relatively easier to match vegetation indices with ground observations. In mixed forests, phenology modelling from remote sensing is often limited to land surface phenology, which consists of an overall phenology of all tree species present in a pixel. The potential of remote sensing for modelling the phenology of individual tree species in mixed forests remains underexplored. In this study, we applied the seasonal midpoint (SM) method with MODIS GPP to model the start of season (SOS) and the end of season (EOS) of six different tree species in Slovenian mixed forests. First, substitute locations were identified for each combination of observation station and plant species based on similar environmental conditions (aspect, slope, and altitude) and tree species of interest, and used to retrieve the remote sensing information used in the SM method after fitting the best of a Gaussian and two double logistic functions to each year of GPP time series. Then, the best thresholds were identified for SOS and EOS, and the results were validated using cross-validation. The results show clearly that the usual threshold of 0.5 is not best in most cases, especially for estimating the EOS. Despite the difficulty in modelling the phenology of different tree species in a mixed forest using remote sensing, it was possible to estimate SOS and EOS with moderate errors as low as <8 days (Fagus sylvatica and Tilia sp.) and <10 days (Fagus sylvatica and Populus tremula), respectively.
Ključne besede: phenology modelling, start of season, end of season, remote sensing, MODIS GPP, vegetation indices, threshold methods
Objavljeno v DiRROS: 23.08.2021; Ogledov: 917; Prenosov: 679
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