| Records |
| Author |
Navas Gonzalez, F.J.; Jordana Vidal, J.; Pizarro Inostroza, G.; Arando Arbulu, A.; Delgado Bermejo, J.V. |
| Title |
Can Donkey Behavior and Cognition Be Used to Trace Back, Explain, or Forecast Moon Cycle and Weather Events? |
Type |
Journal Article |
| Year |
2018 |
Publication |
Animals : an Open Access Journal From MDPI |
Abbreviated Journal  |
Animals (Basel) |
| Volume |
8 |
Issue |
11 |
Pages |
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| Keywords |
Moonlight; Animals |
| Abstract |
Donkeys have been reported to be highly sensitive to environmental changes. Their 8900-8400-year-old evolution process made them interact with diverse environmental situations that were very distant from their harsh origins. These changing situations not only affect donkeys' short-term behavior but may also determine their long-term cognitive skills from birth. Thus, animal behavior becomes a useful tool to obtain past, present or predict information from the environmental situation of a particular area. We performed an operant conditioning test on 300 donkeys to assess their response type, mood, response intensity, and learning capabilities, while we simultaneously registered 14 categorical environmental factors. We quantified the effect power of such environmental factors on donkey behavior and cognition. We used principal component analysis (CATPCA) to reduce the number of factors affecting each behavioral variable and built categorical regression (CATREG) equations to model for the effects of potential factor combinations. Effect power ranged from 7.9% for the birth season on learning (p < 0.05) to 38.8% for birth moon phase on mood (p < 0.001). CATPCA suggests the percentage of variance explained by a four-dimension-model (comprising the dimensions of response type, mood, response intensity and learning capabilities), is 75.9%. CATREG suggests environmental predictors explain 28.8% of the variability of response type, 37.0% of mood, and 37.5% of response intensity, and learning capabilities. |
| Address |
The Worldwide Donkey Breeds Project, Faculty of Veterinary Sciences, University of Cordoba, 14071 Cordoba, Spain. juanviagr218@gmail.com |
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English |
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| ISSN |
2076-2615 |
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PMID:30463193 |
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no |
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GFZ @ kyba @ |
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2083 |
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Grubisic, M.; Van Grunsven, R.H.A.; Kyba, C.C.M.; Manfrin, A.; Hölker, F. |
| Title |
Insect declines and agroecosystems: does light pollution matter? |
Type |
Journal Article |
| Year |
2018 |
Publication |
Annals of Applied Biology |
Abbreviated Journal |
Ann. of Appl. Biol. |
| Volume |
173 |
Issue |
1 |
Pages |
180-189 |
| Keywords |
Animals; Ecology; Review |
| Abstract |
Drastic declines in insect populations, ‘Ecological Armageddon’, have recently gained increased attention in the scientific community, and are commonly considered to be the consequence of large‐scale factors such as land‐use changes, use of pesticides, climate change and habitat fragmentation. Artificial light at night (ALAN), a pervasive global change that strongly impacts insects, remains, however, infrequently recognised as a potential contributor to the observed declines. Here, we provide a summary of recent evidence of impacts of ALAN on insects and discuss how these impacts can drive declines in insect populations in light‐polluted areas. ALAN can increase overall environmental pressure on insect populations, and this is particularly important in agroecosystems where insect communities provide important ecosystem services (such as natural pest control, pollination, conservation of soil structure and fertility and nutrient cycling), and are already under considerable environmental pressure. We discuss how changes in insect populations driven by ALAN and ALAN itself may hinder these services to influence crop production and biodiversity in agricultural landscapes. Understanding the contribution of ALAN and other factors to the decline of insects is an important step towards mitigation and the recovery of the insect fauna in our landscapes. In future studies, the role of increased nocturnal illumination also needs to be examined as a possible causal factor of insect declines in the ongoing ‘Ecological Armageddon’, along with the more commonly examined factors. Given the large scale of agricultural land use and the potential of ALAN to indirectly and directly impact crop production and biodiversity, a better understanding of effects of ALAN in agroecosystems is urgently needed. |
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GFZ @ kyba @ |
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1939 |
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Babadi, S.; Ramirez-Inguiez, R.; Boutaleb, T.; Mallick, T. |
| Title |
Producing uniform illumination within a rectangular area by using a nonimaging optic |
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Journal Article |
| Year |
2018 |
Publication |
Applied Optics |
Abbreviated Journal |
Appl. Opt. |
| Volume |
57 |
Issue |
31 |
Pages |
9357 |
| Keywords |
Lighting |
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This paper proposes a new design method to create a novel optical element to generate uniform illumination within a rectangular area. Based on this model, an illuminated area is irradiated by two sets of rays; the first one irradiates the target plane after refraction from the top section of the lens, and the second one irradiates from the reflection at the side profile of the lens and then from refraction at the top part of the lens. The results show that a uniformity of over 90% can be achieved. |
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1559-128X |
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GFZ @ kyba @ |
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2046 |
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Levin, N.; Ali, S.; Crandall, D. |
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Utilizing remote sensing and big data to quantify conflict intensity: The Arab Spring as a case study |
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Journal Article |
| Year |
2018 |
Publication |
Applied Geography |
Abbreviated Journal |
Applied Geography |
| Volume |
94 |
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1-17 |
| Keywords |
Remote Sensing; Society; Human Health |
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Tracking global and regional conflict zones requires spatially explicit information in near real-time. Here, we examined the potential of remote sensing time-series data (night lights) and big data (data mining of news events and Flickr photos) for monitoring and understanding crisis development and refugee flows. We used the recent Arab Spring as a case study, and examined temporal trends in monthly time series of variables which we hypothesized to indicate conflict intensity, covering all Arab countries. Both Flickr photos and night-time lights proved as sensitive indicators for loss of economic and human capital, and news items from the Global Data on Events, Location and Tone (GDELT) project on fight events were positively correlated with actual deaths from conflicts. We propose that big data and remote sensing datasets have potential to provide disaggregated and timely data on conflicts where official statistics are lacking, offering an effective approach for monitoring geopolitical and environmental changes on Earth. |
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0143-6228 |
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GFZ @ kyba @ |
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1918 |
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Tan, M.; Li, X.; Li, S.; Xin, L.; Wang, X.; Li, Q.; Li, W.; Li, Y.; Xiang, W. |
| Title |
Modeling population density based on nighttime light images and land use data in China |
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Journal Article |
| Year |
2018 |
Publication |
Applied Geography |
Abbreviated Journal |
Applied Geography |
| Volume |
90 |
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239-247 |
| Keywords |
Remote Sensing |
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Population change is a key variable that influences climate change, ecological construction, soil and water use, and economic growth. Census data are always point data, whereas planar data are often required in scientific research. By using nighttime light (NTL) images and land use data, combined with the fifth and sixth census data of China at the county level, we carried out spatial matching on the population of each county, respectively, and established population density diagrams of China for 2000 and 2010, which had a spatial resolution of 1 × 1 km. The method proposed in this paper is relatively simple and has a high simulation precision. The results showed that during the first ten years of the 21st century, there are some remarkable characteristics in Chinese population spatial pattern change: 1) the “disappearance” of intermediate-density regions; namely, areas with a population density between 500 and 1500 persons/km2 have decreased by 41% during the ten years; 2) continuous growth of high-density regions; namely, areas with a population density of more than 1500 persons/km2 have increased by 76%; 3) an expansion tendency of low-density regions similar to high-density regions. |
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0143-6228 |
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GFZ @ kyba @ |
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2481 |
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