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Journal ArticlesMenard et al. (2015) Effects of meteorological and ancillary data, temporal averaging and evaluation methods on model performance and uncertainty in a land surface model, Journal of Hydrometeorology, e-View, doi: 10.1175/JHM-D-15-0013.1. Link to the paper Holmberg, M., Akujärvi, A., Anttila, S., Arvola, L., Bergström, I., Böttcher, K., Feng, X., Forsius, M., Huttunen, I., Huttunen, M., Laine, Y., Lehtonen, H., Liski, J., Mononen, L., Rankinen, K., Repo, A., Piirainen, V., Vanhala, P., Vihervaara, P. 2015. ESLab application to a boreal watershed in southern Finland - preparing for a virtual research environment of ecosystem services. Landscape Ecology 30: 561-577 doi:10.1007/s10980-014-0122-z. Link to the paper Akujärvi, Anu, Aleksi Lehtonen, and Jari Liski. 2016. Ecosystem services of boreal forests-Carbon budget mapping at high resolution. Journal of Environmental Management 181: 498-514. Link to the paper Forsius, M., Akujärvi, A., Mattsson, T., Holmberg, M., Punttila, P., Posch, M., Liski, J., Repo, A., Virkkala, R. Vihervaara, P. 2016. Modelling impacts of forest bioenergy use on ecosystem sustainability: Lammi LTER region, southern Finland. Ecological Indicators 65: 66-75. DOI: 10.1016/j.ecolind.2015.11.032 Link to the paper Vanhala, P., Bergström, I., Haaspuro, T., Kortelainen, P., Holmberg, M., Forsius, M. 2016. Boreal forests can have a remarkable role in reducing greenhouse gas emissions locally: Land use-related and anthropogenic greenhouse gas emissions and sinks at the municipal level. Science of the Total Environment 557-558:51-57. DOI: 10.1016/j.scitotenv.2016.03.040. Link to the paper Böttcher, K., Markkanen, T.,Thum, T., Aalto, T., Aurela, M., Reick, C.H., Kolari, P., Arslan, A.N., Pulliainen, J. 2016. Evaluating Biosphere Model Estimates of the Start of the Vegetation Active Season in Boreal Forests by Satellite Observations. Remote Sensing, 8, 580, DOI:10.3390/rs8070580. Link to the paper Pöyry, J., Böttcher, K., Fronzek, S.; Gobron, N., Leinonen, R., Metsämäki, S., Raimo Virkkala, R. 2017. Predictive power of remote sensing versus temperature-derived variables in modelling phenology of herbivorous insects. Remote Sensing in Ecology and Conservation, DOI: 10.1002/rse2.56. Link to the paper Metsämäki, S., Böttcher, K., Pulliainen, J., Luojus, K., Cohen, J., Takala, M., Mattila, O.-P., Schwaizer, G., Derksen, C., & Koponen, S., 2018. The accuracy of snow melt-off day derived from optical and microwave radiometer data- A study for Europe. Remote Sensing of Environment, 211, 1-12. Link to the paper Y. Gao, T. Markkanen, M. Aurela, I. Mammarella, T. Thum, A. Tsuruta, H. Yang, and T. Aalto. Response of water use efficiency to summer drought in boreal Scots pine forests in Finland. Biogeosciences, 14, 4409-4422, 2017 Link to the paper Raivonen, M., Smolander, S., Backman, L., Susiluoto, J., Aalto, T., Markkanen, T., Mäkelä, J., Rinne, J., Peltola, O., Aurela, M., Tomasic, M., Li, X., Larmola, T., Juutinen, S., Tuittila, E.-S., Heimann, M., Sevanto, S., Kleinen, T., Brovkin, V., and Vesala, T.: HIMMELI v1.0: HelsinkI Model of MEthane buiLd-up and emIssion for peatlands, Geosci. Model Dev. Discuss., DOI: 10.5194/gmd-2017-52, 2017. Link to the paper Susiluoto, J., Raivonen, M., Backman, L., Laine, M., Mäkelä, J., Peltola, O., Vesala, T., and Aalto, T.: Calibrating the sqHIMMELI v1.0 wetland methane emission model with hierarchical modeling and adaptive MCMC, Geosci. Model Dev. Discuss., DOI: 10.5194/gmd-2017-66, in review, 2017. Link to the paper Thum, T., Zaehle, S., Köhler, P., Aalto, T., Aurela, M., Guanter, L., Kolari, P., Laurila, T., Lohila, A., Magnani, F., Van Der Tol, C., and Markkanen, T., 2017. Modelling sun-induced fluorescence and photosynthesis with a land surface model at local and regional scales in northern Europe, Biogeosciences, 14, 1969-1987, doi:10.5194/bg-14-1969-2017. Link to the paper Ruosteenoja, K., Markkanen, T., Venäläinen, A., Räisänen, P. and Peltola, H., 2017. Seasonal soil moisture and drought occurrence in Europe in CMIP5 projections for the 21st century, Climate Dynamics, doi:10.1007/s00382-017-3671-4. Link to the paper Gao Y., Markkanen T., Thum T., Aurela M., Lohila A., Mammarella I., Hagemann S., Aalto T. Assessing various drought indicators in representing drought in boreal forests in Finland. Hydrol. Earth Syst. Sci. 20, 175-191, 2016. Link to the paper Linkosalmi M., M. Aurela, J.-P. Tuovinen, M. Peltoniemi, C. M. Tanis, A. N. Arslan, P. Kolari, T. Aalto, J. Rainne, and T. Laurila. Digital photography for assessing vegetation phenology in two contrasting northern ecosystems. Geosci. Instrum. Method. Data Syst., 5, 417-426, 2016, doi:10.5194/gi-5-417-2016 Link to the paper Mäkelä, J., Susiluoto, J., Markkanen, T., Aurela, M., Järvinen, H., Mammarella, I., Hagemann, S., and Aalto, T., 2016. Constraining ecosystem model with adaptive Metropolis algorithm usingboreal forest site eddy covariance measurements, Nonlin. Processes Geophys., 23, 447-465, doi:10.5194/npg-23-447-2016. Link to the paper Arslan, A.N.; Tanis, C.M.; Metsämäki, S.; Aurela, M.; Böttcher, K.; Linkosalmi, M.; Peltoniemi, M. Automated Webcam Monitoring of Fractional Snow Cover in Northern Boreal Conditions. Geosciences 2017, 7, 55. Link to the paper Peltoniemi, M., Aurela, M., Böttcher, K., Kolari, P., Loehr, J., Karhu, J., Linkosalmi, M., Tanis, C. M., Tuovinen, J.-P., and Arslan, A. N.: Webcam network and image database for studies of phenological changes of vegetation and snow cover in Finland, image time series from 2014 to 2016, Earth Syst. Sci. Data, 10, 173-184, DOI: 10.5194/essd-10-173-2018, 2018. Link to the paper Mikko Peltoniemi, et all, Networked web-cameras monitor congruent seasonal development of birches with phenological field observations, Agricultural and Forest Meteorology, Volume 249, 15 February 2018, Pages 335-347, DOI: 10.1016/j.agrformet.2017.10.008 Link to the paper A. L.D. Augustynczik, F. Hartig, F. Minunno, H-P Kahle, D. Diaconu, M. Hanewinkel, R. Yousefpour (2017). Productivity of Fagus sylvatica under climate change - A Bayesian analysis of risk and uncertainty using the model 3-PG. Forest Ecology and Management 401: 192-206. DOI: 10.1016/j.foreco.2017.06.061 Link to the paper F. Minunno, M. Peltoniemi, S. Launiainen, M. Aurela, A. Lindroth, A. Lohila,I. Mammarella, K. Minkkinen, A. Mäkelä (2016). Calibration and validation of a semi-empirical flux ecosystem model for coniferous forests in the Boreal region. Ecological Modelling, Volume 341, 10 December 2016, Pages 37-52. DOI: 10.1016/j.ecolmodel.2016.09.020 Link to the paper J. Lonsdale, F. Minunno, M. Mencuccini, M. Perks (2015). Bayesian calibration and Bayesian model comparison of a stand level dynamic growth model for Sitka spruce and Scots pine Forestry 07/2015; 88(3):326-335. DOI:10.1093/forestry/cpv003 Link to the paper M. Mencuccini, F. Minunno, Y. Salmon, J. MartĂnez-Vilalta, T. Hölttä (2015). Coordination of physiological traits involved in drought-induced mortality. New Phytologist 05/2015; 208(2). DOI:10.1111/nph.13461. Link to the paper Böttcher K, Aurela M., Kervinen M., Markkanen T, Mattila O-P, Kolari P., Metsämäki S., Aalto T, Arslan A.N., Pulliainen J., 2014. MODIS time-series-derived indicators for the beginning of the growing season in boreal coniferous forest - A comparison with CO2 flux measurements and phenological observations in Finland. Remote Sensing of Environment 2014, 140, 625 - 638; DOI:10.1016/j.rse.2013.09.022. Link to the paper |