TY - JOUR A1 - Ayanu, Yohannes A1 - Conrad, Christopher A1 - Jentsch, Anke A1 - Koellner, Thomas T1 - Unveiling undercover cropland inside forests using landscape variables: a supplement to remote sensing image classification JF - PLoS ONE N2 - The worldwide demand for food has been increasing due to the rapidly growing global population, and agricultural lands have increased in extent to produce more food crops. The pattern of cropland varies among different regions depending on the traditional knowledge of farmers and availability of uncultivated land. Satellite images can be used to map cropland in open areas but have limitations for detecting undergrowth inside forests. Classification results are often biased and need to be supplemented with field observations. Undercover cropland inside forests in the Bale Mountains of Ethiopia was assessed using field observed percentage cover of land use/land cover classes, and topographic and location parameters. The most influential factors were identified using Boosted Regression Trees and used to map undercover cropland area. Elevation, slope, easterly aspect, distance to settlements, and distance to national park were found to be the most influential factors determining undercover cropland area. When there is very high demand for growing food crops, constrained under restricted rights for clearing forest, cultivation could take place within forests as an undercover. Further research on the impact of undercover cropland on ecosystem services and challenges in sustainable management is thus essential. KW - climate change KW - land-cover classification KW - bale mountains national park KW - sub-saharan africa KW - agroforestry systems KW - biodiversity conservation KW - ecosystem services KW - topographic aspect KW - wheat-varieties Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-151686 VL - 10 IS - 6 ER - TY - JOUR A1 - Joschinski, Jens A1 - Hovestadt, Thomas A1 - Krauss, Jochen T1 - Coping with shorter days: do phenology shifts constrain aphid fitness? JF - PeerJ N2 - Climate change can alter the phenology of organisms. It may thus lead seasonal organisms to face different day lengths than in the past, and the fitness consequences of these changes are as yet unclear. To study such effects, we used the pea aphid Acyrthosiphon pisum as a model organism, as it has obligately asexual clones which can be used to study day length effects without eliciting a seasonal response. We recorded life-history traits under short and long days, both with two realistic temperature cycles with means differing by 2 °C. In addition, we measured the population growth of aphids on their host plant Pisum sativum. We show that short days reduce fecundity and the length of the reproductive period of aphids. Nevertheless, this does not translate into differences at the population level because the observed fitness costs only become apparent late in the individual's life. As expected, warm temperature shortens the development time by 0.7 days/°C, leading to faster generation times. We found no interaction of temperature and day length. We conclude that day length changes cause only relatively mild costs, which may not decelerate the increase in pest status due to climate change. KW - Homoptera aphididae KW - clock reproduction ecology KW - phenotypic plasticity KW - phenology shifts KW - insect timing KW - physiological constraints KW - day length KW - circadian rhythms KW - Acyrthosiphon pisum KW - climate change Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-148382 VL - 3 IS - e1103 ER - TY - JOUR A1 - Alavipanah, Sadroddin A1 - Wegmann, Martin A1 - Qureshi, Salman A1 - Weng, Qihao A1 - Koellner, Thomas T1 - The role of vegetation in mitigating urban land surface temperatures: a case study of Munich, Germany during the warm season JF - Sustainability N2 - The Urban Heat Island (UHI) is the phenomenon of altered increased temperatures in urban areas compared to their rural surroundings. UHIs grow and intensify under extreme hot periods, such as during heat waves, which can affect human health and also increase the demand for energy for cooling. This study applies remote sensing and land use/land cover (LULC) data to assess the cooling effect of varying urban vegetation cover, especially during extreme warm periods, in the city of Munich, Germany. To compute the relationship between Land Surface Temperature (LST) and Land Use Land Cover (LULC), MODIS eight-day interval LST data for the months of June, July and August from 2002 to 2012 and the Corine Land Cover (CLC) database were used. Due to similarities in the behavior of surface temperature of different CLCs, some classes were reclassified and combined to form two major, rather simplified, homogenized classes: one of built-up area and one of urban vegetation. The homogenized map was merged with the MODIS eight-day interval LST data to compute the relationship between them. The results revealed that (i) the cooling effect accrued from urban vegetation tended to be non-linear; and (ii) a remarkable and stronger cooling effect in terms of LST was identified in regions where the proportion of vegetation cover was between seventy and almost eighty percent per square kilometer. The results also demonstrated that LST within urban vegetation was affected by the temperature of the surrounding built-up and that during the well-known European 2003 heat wave, suburb areas were cooler from the core of the urbanized region. This study concluded that the optimum green space for obtaining the lowest temperature is a non-linear trend. This could support urban planning strategies to facilitate appropriate applications to mitigate heat-stress in urban area. KW - Surface Urban Heat Island (SUHI) KW - cities KW - buildings KW - Land Surface Temperature (LST) KW - urban vegetation KW - climate change KW - heat waves Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-143447 VL - 7 ER - TY - JOUR A1 - Asare-Kyei, Daniel A1 - Forkuor, Gerald A1 - Venus, Valentijn T1 - Modeling Flood Hazard Zones at the Sub-District Level with the Rational Model Integrated with GIS and Remote Sensing Approaches JF - Water N2 - Robust risk assessment requires accurate flood intensity area mapping to allow for the identification of populations and elements at risk. However, available flood maps in West Africa lack spatial variability while global datasets have resolutions too coarse to be relevant for local scale risk assessment. Consequently, local disaster managers are forced to use traditional methods such as watermarks on buildings and media reports to identify flood hazard areas. In this study, remote sensing and Geographic Information System (GIS) techniques were combined with hydrological and statistical models to delineate the spatial limits of flood hazard zones in selected communities in Ghana, Burkina Faso and Benin. The approach involves estimating peak runoff concentrations at different elevations and then applying statistical methods to develop a Flood Hazard Index (FHI). Results show that about half of the study areas fall into high intensity flood zones. Empirical validation using statistical confusion matrix and the principles of Participatory GIS show that flood hazard areas could be mapped at an accuracy ranging from 77% to 81%. This was supported with local expert knowledge which accurately classified 79% of communities deemed to be highly susceptible to flood hazard. The results will assist disaster managers to reduce the risk to flood disasters at the community level where risk outcomes are first materialized. KW - climate change KW - rational model KW - community KW - flood hazard index KW - West Africa KW - GIS KW - vulnerability KW - performance KW - impact KW - risk KW - mapping KW - runoff Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-151581 VL - 7 SP - 3531 EP - 3564 ER -