TY - JOUR A1 - Frommhold, Martin A1 - Heim, Arend A1 - Barabanov, Mikhail A1 - Maier, Franziska A1 - Mühle, Ralf-Udo A1 - Smirenski, Sergei M. A1 - Heim, Wieland T1 - Breeding habitat and nest-site selection by an obligatory "nest-cleptoparasite", the Amur Falcon Falco amurensis JF - Ecology and evolution N2 - The selection of a nest site is crucial for successful reproduction of birds. Animals which re-use or occupy nest sites constructed by other species often have limited choice. Little is known about the criteria of nest-stealing species to choose suitable nesting sites and habitats. Here, we analyze breeding-site selection of an obligatory "nest-cleptoparasite", the Amur Falcon Falco amurensis. We collected data on nest sites at Muraviovka Park in the Russian Far East, where the species breeds exclusively in nests of the Eurasian Magpie Pica pica. We sampled 117 Eurasian Magpie nests, 38 of which were occupied by Amur Falcons. Nest-specific variables were assessed, and a recently developed habitat classification map was used to derive landscape metrics. We found that Amur Falcons chose a wide range of nesting sites, but significantly preferred nests with a domed roof. Breeding pairs of Eurasian Hobby Falco subbuteo and Eurasian Magpie were often found to breed near the nest in about the same distance as neighboring Amur Falcon pairs. Additionally, the occurrence of the species was positively associated with bare soil cover, forest cover, and shrub patches within their home range and negatively with the distance to wetlands. Areas of wetlands and fallow land might be used for foraging since Amur Falcons mostly depend on an insect diet. Additionally, we found that rarely burned habitats were preferred. Overall, the effect of landscape variables on the choice of actual nest sites appeared to be rather small. We used different classification methods to predict the probability of occurrence, of which the Random forest method showed the highest accuracy. The areas determined as suitable habitat showed a high concordance with the actual nest locations. We conclude that Amur Falcons prefer to occupy newly built (domed) nests to ensure high nest quality, as well as nests surrounded by available feeding habitats. KW - cleptoparasitism KW - fire KW - habitat use KW - machine learning KW - magpie KW - nest-site selection KW - random forest Y1 - 2019 U6 - https://doi.org/10.1002/ece3.5878 SN - 2045-7758 VL - 9 IS - 24 SP - 14430 EP - 14441 PB - Wiley CY - Hoboken ER - TY - JOUR A1 - Werner, Andrea A1 - Werner, Andreas A1 - Wieland, Ralf A1 - Kersebaum, Kurt-Christian A1 - Mirschel, Wilfried A1 - Ende, Hans-Peter A1 - Wiggering, Hubert T1 - Ex ante assessment of crop rotations focusing on energy crops using a multi-attribute decision-making method JF - Ecological indicators : integrating monitoring, assessment and management N2 - The cultivation of plants for use as energy resources is an agricultural and industrial sector with potentially synergistic benefits related to protecting the environment and generating income. Against the background of increasing land-use changes and new agricultural approaches to the production of energy crops, we present a method for identifying future-oriented crop rotations that supports both the economic and environmental components of decision-making strategies with respect to agriculture-related policy decisions (regional mission statements). The conflicting aspects of these objectives can be addressed with the analytic hierarchy process (AHP), a multi-attribute decision-making method that was integrated here. Three models are used to generate simulations of the defined objectives over a planning period of 30 years under the current climate scenario and provide input data for the multi-attribute assessment of several crop rotations. Based on the entire evaluation process, dimensionless global priority vectors are used to indicate how well the crop rotations meet the requirements of the defined mission statement. The method is tested in a municipality in NE Germany. (C) 2014 Elsevier Ltd. All rights reserved. KW - Agricultural management KW - Ex ante assessment KW - Multi-attribute decision-making KW - AHP KW - Crop rotation KW - Energy crops KW - Regional objectives KW - Indicators Y1 - 2014 U6 - https://doi.org/10.1016/j.ecolind.2014.03.013 SN - 1470-160X SN - 1872-7034 VL - 45 SP - 110 EP - 122 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Wieland, Ralf A1 - Dalchow, Claus A1 - Sommer, Michael A1 - Fukuda, Kyoko T1 - Multi-Scale Landscape Analysis (MSLA) a method to identify correlation of relief with ecological point data JF - Ecological informatics : an international journal on ecoinformatics and computational ecolog N2 - A common problem in ecology is identifying the relationship between relief and site properties obtainable only by point measurements. The method of Multi-Scale Landscape Analysis (MSLA) identifies such correlations. MSLA combines frequency filtering of the digital elevation model (DEM) with an estimation of the optimum filter coefficients using an optimization procedure. Tested using point data of soil decarbonation from a German young moraine landscape, MSLA provided significant results. Implemented within open source software SAMT. MSLA is comfortable and flexible to use, offering applications for numerous other spatial analysis problems. KW - Landscape structure KW - DEM KW - Fourier transformation KW - Wavelet transformation KW - Singular value decomposition KW - SAMT Y1 - 2011 U6 - https://doi.org/10.1016/j.ecoinf.2010.09.002 SN - 1574-9541 VL - 6 IS - 2 SP - 164 EP - 169 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - van der Valk, Ralf J. P. A1 - Kreiner-Moller, Eskil A1 - Kooijman, Marjolein N. A1 - Guxens, Monica A1 - Stergiakouli, Evangelia A1 - Saaf, Annika A1 - Bradfield, Jonathan P. A1 - Geller, Frank A1 - Hayes, M. Geoffrey A1 - Cousminer, Diana L. A1 - Koerner, Antje A1 - Thiering, Elisabeth A1 - Curtin, John A. A1 - Myhre, Ronny A1 - Huikari, Ville A1 - Joro, Raimo A1 - Kerkhof, Marjan A1 - Warrington, Nicole M. A1 - Pitkanen, Niina A1 - Ntalla, Ioanna A1 - Horikoshi, Momoko A1 - Veijola, Riitta A1 - Freathy, Rachel M. A1 - Teo, Yik-Ying A1 - Barton, Sheila J. A1 - Evans, David M. A1 - Kemp, John P. A1 - St Pourcain, Beate A1 - Ring, Susan M. A1 - Smith, George Davey A1 - Bergstrom, Anna A1 - Kull, Inger A1 - Hakonarson, Hakon A1 - Mentch, Frank D. A1 - Bisgaard, Hans A1 - Chawes, Bo Lund Krogsgaard A1 - Stokholm, Jakob A1 - Waage, Johannes A1 - Eriksen, Patrick A1 - Sevelsted, Astrid A1 - Melbye, Mads A1 - van Duijn, Cornelia M. A1 - Medina-Gomez, Carolina A1 - Hofman, Albert A1 - de Jongste, Johan C. A1 - Taal, H. Rob A1 - Uitterlinden, Andre G. A1 - Armstrong, Loren L. A1 - Eriksson, Johan A1 - Palotie, Aarno A1 - Bustamante, Mariona A1 - Estivill, Xavier A1 - Gonzalez, Juan R. A1 - Llop, Sabrina A1 - Kiess, Wieland A1 - Mahajan, Anubha A1 - Flexeder, Claudia A1 - Tiesler, Carla M. T. A1 - Murray, Clare S. A1 - Simpson, Angela A1 - Magnus, Per A1 - Sengpiel, Verena A1 - Hartikainen, Anna-Liisa A1 - Keinanen-Kiukaanniemi, Sirkka A1 - Lewin, Alexandra A1 - Alves, Alexessander Da Silva Couto A1 - Blakemore, Alexandra I. F. A1 - Buxton, Jessica L. A1 - Kaakinen, Marika A1 - Rodriguez, Alina A1 - Sebert, Sylvain A1 - Vaarasmaki, Marja A1 - Lakka, Timo A1 - Lindi, Virpi A1 - Gehring, Ulrike A1 - Postma, Dirkje S. A1 - Ang, Wei A1 - Newnham, John P. A1 - Lyytikainen, Leo-Pekka A1 - Pahkala, Katja A1 - Raitakari, Olli T. A1 - Panoutsopoulou, Kalliope A1 - Zeggini, Eleftheria A1 - Boomsma, Dorret I. A1 - Groen-Blokhuis, Maria A1 - Ilonen, Jorma A1 - Franke, Lude A1 - Hirschhorn, Joel N. A1 - Pers, Tune H. A1 - Liang, Liming A1 - Huang, Jinyan A1 - Hocher, Berthold A1 - Knip, Mikael A1 - Saw, Seang-Mei A1 - Holloway, John W. A1 - Melen, Erik A1 - Grant, Struan F. A. A1 - Feenstra, Bjarke A1 - Lowe, William L. A1 - Widen, Elisabeth A1 - Sergeyev, Elena A1 - Grallert, Harald A1 - Custovic, Adnan A1 - Jacobsson, Bo A1 - Jarvelin, Marjo-Riitta A1 - Atalay, Mustafa A1 - Koppelman, Gerard H. A1 - Pennell, Craig E. A1 - Niinikoski, Harri A1 - Dedoussis, George V. A1 - Mccarthy, Mark I. A1 - Frayling, Timothy M. A1 - Sunyer, Jordi A1 - Timpson, Nicholas J. A1 - Rivadeneira, Fernando A1 - Bonnelykke, Klaus A1 - Jaddoe, Vincent W. V. T1 - A novel common variant in DCST2 is associated with length in early life and height in adulthood JF - Human molecular genetics N2 - Common genetic variants have been identified for adult height, but not much is known about the genetics of skeletal growth in early life. To identify common genetic variants that influence fetal skeletal growth, we meta-analyzed 22 genome-wide association studies (Stage 1; N = 28 459). We identified seven independent top single nucleotide polymorphisms (SNPs) (P < 1 x 10(-6)) for birth length, of which three were novel and four were in or near loci known to be associated with adult height (LCORL, PTCH1, GPR126 and HMGA2). The three novel SNPs were followed-up in nine replication studies (Stage 2; N = 11 995), with rs905938 in DC-STAMP domain containing 2 (DCST2) genome-wide significantly associated with birth length in a joint analysis (Stages 1 + 2; beta = 0.046, SE = 0.008, P = 2.46 x 10(-8), explained variance = 0.05%). Rs905938 was also associated with infant length (N = 28 228; P = 5.54 x 10(-4)) and adult height (N = 127 513; P = 1.45 x 10(-5)). DCST2 is a DC-STAMP-like protein family member and DC-STAMP is an osteoclast cell-fusion regulator. Polygenic scores based on 180 SNPs previously associated with human adult stature explained 0.13% of variance in birth length. The same SNPs explained 2.95% of the variance of infant length. Of the 180 known adult height loci, 11 were genome-wide significantly associated with infant length (SF3B4, LCORL, SPAG17, C6orf173, PTCH1, GDF5, ZNFX1, HHIP, ACAN, HLA locus and HMGA2). This study highlights that common variation in DCST2 influences variation in early growth and adult height. Y1 - 2015 U6 - https://doi.org/10.1093/hmg/ddu510 SN - 0964-6906 SN - 1460-2083 VL - 24 IS - 4 SP - 1155 EP - 1168 PB - Oxford Univ. Press CY - Oxford ER - TY - JOUR A1 - Zhang, Zhuodong A1 - Wieland, Ralf A1 - Reiche, Matthias A1 - Funk, Roger A1 - Hoffmann, Carsten A1 - Li, Yong A1 - Sommer, Michael T1 - Identifying sensitive areas to wind erosion in the xilingele grassland by computational fluid dynamics modelling JF - Ecological informatics : an international journal on ecoinformatics and computational ecolog N2 - In order to identify the areas in the Xilingele grassland which are sensitive to wind erosion, a computational fluid dynamics model (CFD-WEM) was used to simulate the wind fields over a region of 37 km(2) which contains different topography and land use types. Previous studies revealed the important influences of topography and land use on wind erosion in the Xilingele grassland. Topography influences wind fields at large scale, and land use influences wind fields near the ground. Two steps were designed to implement the CFD wind simulation, and they were respectively to simulate the influence of topography and surface roughness on the wind. Digital elevation model (DEM) and surface roughness length were the key inputs for the CFD simulation. The wind simulation by CFD-WEM was validated by a wind data set which was measured simultaneously at six positions in the field. Three scenarios with different wind velocities were designed based on observed dust storm events, and wind fields were simulated according to these scenarios to predict the sensitive areas to wind erosion. General assumptions that cropland is the most sensitive area to wind erosion and heavily and moderately grazed grasslands are both sensitive etc. can be refined by the modelling of CFD-WEM. Aided by the results of this study, the land use planning and protection measures against wind erosion can be more efficient. Based on the case study in the Xilingele grassland, a method of regional wind erosion assessment aided by CFD wind simulation is summarized. The essence of this method is a combination of CFD wind simulation and determination of threshold wind velocity for wind erosion. Because of the physically-based simulation and the flexibility of the method, it can be generalised to other regions. KW - Sensitive areas KW - Wind erosion KW - Computational fluid dynamics KW - Grassland KW - Surface roughness Y1 - 2012 U6 - https://doi.org/10.1016/j.ecoinf.2011.12.002 SN - 1574-9541 VL - 8 IS - 5 SP - 37 EP - 47 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Zhang, Zhuo-dong A1 - Wieland, Ralf A1 - Reiche, Matthias A1 - Funk, Roger A1 - Hoffmann, Carsten A1 - Li, Yong A1 - Sommer, Michael T1 - A computational fluid dynamics model for wind simulation: model implementation and experimental validation JF - Journal of Zhejiang University : an international journal ; Science A, Applied physics & engineering : an international applied physics & engineering journal N2 - To provide physically based wind modelling for wind erosion research at regional scale, a 3D computational fluid dynamics (CFD) wind model was developed. The model was programmed in C language based on the Navier-Stokes equations, and it is freely available as open source. Integrated with the spatial analysis and modelling tool (SAMT), the wind model has convenient input preparation and powerful output visualization. To validate the wind model, a series of experiments was conducted in a wind tunnel. A blocking inflow experiment was designed to test the performance of the model on simulation of basic fluid processes. A round obstacle experiment was designed to check if the model could simulate the influences of the obstacle on wind field. Results show that measured and simulated wind fields have high correlations, and the wind model can simulate both the basic processes of the wind and the influences of the obstacle on the wind field. These results show the high reliability of the wind model. A digital elevation model (DEM) of an area (3800 m long and 1700 m wide) in the Xilingele grassland in Inner Mongolia (autonomous region, China) was applied to the model, and a 3D wind field has been successfully generated. The clear implementation of the model and the adequate validation by wind tunnel experiments laid a solid foundation for the prediction and assessment of wind erosion at regional scale. KW - Wind model KW - Computational fluid dynamics (CFD) KW - Wind erosion KW - Wind tunnel experiments KW - Spatial analysis and modelling tool (SAMT) KW - Open source Y1 - 2012 U6 - https://doi.org/10.1631/jzus.A1100231 SN - 1673-565X VL - 13 IS - 4 SP - 274 EP - 283 PB - Zhejiang University Press CY - Hangzou ER - TY - JOUR A1 - Zhang, Zhuodong A1 - Wieland, Ralf A1 - Reiche, Matthias A1 - Funk, Roger A1 - Hoffmann, Carsten A1 - Li, Yong A1 - Sommer, Michael T1 - Wind modelling for wind erosion research by open source computational fluid dynamics JF - Ecological informatics : an international journal on ecoinformatics and computational ecolog N2 - The open source computational fluid dynamics (CFD) wind model (CFD-WEM) for wind erosion research in the Xilingele grassland in Inner Mongolia (autonomous region, China) is compared with two open source CFD models Gerris and OpenFOAM. The evaluation of these models was made according to software technology, implemented methods, handling, accuracy and calculation speed. All models were applied to the same wind tunnel data set. Results show that the simplest CFD-WEM has the highest calculation speed with acceptable accuracy, and the most powerful OpenFOAM produces the simulation with highest accuracy and the lowest calculation speed. Gerris is between CFD-WEM and OpenFOAM. It calculates faster than OpenFOAM, and it is capable to solve different CFD problems. CFD-WEM is the optimal model to be further developed for wind erosion research in Inner Mongolia grassland considering its efficiency and the uncertainties of other input data. However, for other applications using CFD technology, Gerris and OpenFOAM can be good choices. This paper shows the powerful capability of open source CFD software in wind erosion study, and advocates more involvement of open source technology in wind erosion and related ecological researches. KW - Computational fluid dynamics KW - Wind modelling KW - Open source KW - Wind erosion KW - Gerris KW - OpenFOAM KW - SAMT Y1 - 2011 U6 - https://doi.org/10.1016/j.ecoinf.2011.02.001 SN - 1574-9541 VL - 6 IS - 5 SP - 316 EP - 324 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Ghafarian, Fatemeh A1 - Wieland, Ralf A1 - Lüttschwager, Dietmar A1 - Nendel, Claas T1 - Application of extreme gradient boosting and Shapley Additive explanations to predict temperature regimes inside forests from standard open-field meteorological data JF - Environmental modelling & software with environment data news N2 - Forest microclimate can buffer biotic responses to summer heat waves, which are expected to become more extreme under climate warming. Prediction of forest microclimate is limited because meteorological observation standards seldom include situations inside forests. We use eXtreme Gradient Boosting - a Machine Learning technique - to predict the microclimate of forest sites in Brandenburg, Germany, using seasonal data comprising weather features. The analysis was amended by applying a SHapley Additive explanation to show the interaction effect of variables and individualised feature attributions. We evaluate model performance in comparison to artificial neural networks, random forest, support vector machine, and multi-linear regression. After implementing a feature selection, an ensemble approach was applied to combine individual models for each forest and improve robustness over a given single prediction model. The resulting model can be applied to translate climate change scenarios into temperatures inside forests to assess temperature-related ecosystem services provided by forests. KW - cooling effect KW - machine learning KW - ensemble method KW - ecosystem services Y1 - 2022 U6 - https://doi.org/10.1016/j.envsoft.2022.105466 SN - 1364-8152 SN - 1873-6726 VL - 156 PB - Elsevier CY - Oxford ER - TY - JOUR A1 - Ghafarian, Fatemeh A1 - Wieland, Ralf A1 - Nendel, Claas T1 - Estimating the Evaporative Cooling Effect of Irrigation within and above Soybean Canopy JF - Water N2 - Vegetation with an adequate supply of water might contribute to cooling the land surface around it through the latent heat flux of transpiration. This study investigates the potential estimation of evaporative cooling at plot scale, using soybean as example. Some of the plants' physiological parameters were monitored and sampled at weekly intervals. A physics-based model was then applied to estimate the irrigation-induced cooling effect within and above the canopy during the middle and late season of the soybean growth period. We then examined the results of the temperature changes at a temporal resolution of ten minutes between every two irrigation rounds. During the middle and late season of growth, the cooling effects caused by evapotranspiration within and above the canopy were, on average, 4.4 K and 2.9 K, respectively. We used quality indicators such as R-squared (R-2) and mean absolute error (MAE) to evaluate the performance of the model simulation. The performance of the model in this study was better above the canopy (R-2 = 0.98, MAE = 0.3 K) than below (R-2 = 0.87, MAE = 0.9 K) due to the predefined thermodynamic condition used to estimate evaporative cooling. Moreover, the study revealed that canopy cooling contributes to mitigating heat stress conditions during the middle and late seasons of crop growth. KW - canopy cooling effects KW - shading cooling KW - canopy-air temperature KW - energy KW - balance KW - the Penman-Monteith equation Y1 - 2022 U6 - https://doi.org/10.3390/w14030319 SN - 2073-4441 VL - 14 IS - 3 PB - MDPI CY - Basel ER -