Species distribution modelling (SDM) is a widely used approach to examine and predict biological responses in space and time. SDM is used to gain insights in 1) overall species distributions, 2) their past-present-future probability of occurrence, and 3) to quantify species–environment relationships. Research in the lab is focused on increasing the ecological realism of the distribution models and is developing models from both theoretical and applied perspectives. The lab is at the forefront of progress, especially in including true field measurements such as soil properties, biotic interactions, productivity, and earth surface processes in the modelling framework. Our predominant study subject is vegetation (vascular plants, bryophytes, and lichens), but we also model other taxa: birds, butterflies, amphibians, mammals, and diatoms.

Links to related articles:

• Kemppinen, J., Niittynen, P., Aalto, J., le Roux, P. C., & Luoto, M. (2019). Water as a resource, stress and disturbance shaping tundra vegetation. Oikos.
• Niittynen, P., & Luoto, M. (2018). The importance of snow in species distribution models of arctic vegetation. Ecography, 41(6), 1024-1037.
• Mod, H.K., Scherrer, D., Luoto, M. & Guisan, A. (2016) What we use is not what we know: environmental predictors in plant distribution models. Journal of Vegetation Science 27, 1308-1322.
• Mod, H., le Roux, P.C., Guisan, A. & Luoto, M. (2015) Biotic interactions boost spatial models of species richness. Ecography 38, 913–921.
• Tallavaaraa, M., Luoto, M. , Korhonen, N., Järvinen, H., & Seppä, H. (2015) Human population dynamics in Europe over the Last Glacial Maximum. Proceedings of the National Academy of Sciences 112, 8232-8237.
• le Roux, P.C., Pellissier, L., Wisz, M.S. & Luoto, M. (2014) Incorporating dominant species as proxies for biotic interactions strengthens plant community models. Journal of Ecology 102, 767–775.

Keywords: Species richness| Biotic interactions | Stacked species distribution models

The lab studies Earth surface processes, such as geomorphology, ground-surface properties, and soil thermal-hydrological conditions, and their interactions with biota and climate, by using spatial modelling methods. Moreover, the lab specializes in predictive mapping of various geomorphological features typical in cold regions, such as cryoturbation and permafrost in mires. Besides investigating the spatial and temporal variation of Earth surface processes, the drivers of soil moisture and temperature patterns are one of the main topics of the lab, as land-atmosphere interactions and their impacts on the changing environment are yet largely unknown. Additionally, ground surface carbon fluxes are a recent interest of the lab, as carbon is a principal element in the biosphere-atmosphere feedback system.

Links to related articles:

• Hjort, J., Karjalainen, Aalto, J., Westermann, S., Romanovsky, V. E., Nelson, F. E., Etzelmüller, B., & Luoto, M. (2018). Degrading permafrost puts Arctic infrastructure at risk by mid-century. Nature Communicationsvolume 9: 5147.
• Aalto, J., Karjalainen, O., Hjort, J., & Luoto, M. (2018). Statistical forecasting of current and future circum‐Arctic ground temperatures and active layer thickness. Geophysical Research Letters, 45(10), 4889-4898.
• Kemppinen, J., Niittynen, P., Riihimäki, H., & Luoto, M. (2018). Modelling soil moisture in a high‐latitude landscape using LiDAR and soil data. Earth Surface Processes and Landforms, 43(5), 1019-1031.
• Aalto, J., Venäläinen, A., Heikkinen, R.K. & Luoto, M. (2014) Potential for extreme loss in high-latitude Earth surface processes due to climate change. Geophysical Research Letters 41, 3914–3924.
• Aalto, J. & Luoto, M. (2014) Integrating climate and local factors for geomorphological distribution models. Earth Surface Processes and Landforms 39, 1729-1740.
• le Roux, P.C. & Luoto, M. (2014) Earth surface processes drive the richness, composition and occurrence of plant species in an arctic-alpine environment. Journal of Vegetation Science 25, 45-54.

Keywords: Thermal and hydrological conditions of soil | Soil-vegetation-climate interactions | Geomorphology

One of the main focuses of the lab is to bring ecological relevance to remote sensing with novel technologies used in environmental research. Our aim is to address questions regarding both biotic and abiotic environments, such as species diversity, primary productivity, and ground-surface conditions, as well as drivers controlling the accelerating global change. There is a fundamental research gap to be filled concerning both up- and down-scaling of environmental data and models, which the lab addresses by combining multiscale remotely sensed data with in situ observations and measurements and unmanned aerial missions. The The lab utilizes multitemporal data from micro- to macroscales by using, for example, Structure from Motion, thermal infrared, LIDAR, and global satellite data.

Links to related articles:

• Riihimäki, H., Heiskanen, J. & Luoto, M. (2017) The effect of topography on arctic-alpine aboveground biomass and NDVI patterns. International Journal of Applied Earth Observations and Geoinformation 56, 44-53.
• Hjort, M. & Luoto, M. (2012) Can geodiversity be predicted from space? Geomorphology 153-154, 74–80.

• Rocchini, D., Balkenhol, N., Carter, G.A., Foody, G.M., Gillespie, T.W., He, K.S., Kark, S., Levin, N. Lucas, K., Luoto, M., Nagendra, H., Oldeland, J., Ricotta, C., Southworth, J., & Neteler, M. (2010) Remotely sensed spectral heterogeneity as a proxy of species diversity: recent advances and open challenges. Ecological Informatics 5, 318-329.

Keywords: Unmanned Aerial Vehicles (UAV) | LiDAR | Hyperspectral remote sensing | Landsat | Sentinel | MODIS | AVHRR

Climate predictions to the past, present, and future are important in order to understand the effects of ongoing climate change on ecosystems, earth surface processes, and ground-surface conditions. The lab develops both empirical and mechanistic modelling methods for accurate estimation of climatic variation at local and regional scales. The aim is to add realism to current climate data by examining the micro- and mesoscale drivers of climate at the atmospheric boundary layer, such as solar radiation, plant canopies, and cold-air pooling. Past climates are studied by applying models of biotic response to study the development of climate across geological time based on fossil datasets. These past and present climate model developments further improve the predictions of future climate with different greenhouse gas scenarios.

Links to related articles:

• Salonen, J. S., Helmens, K. F., … & Luoto, M. (2018). Abrupt high-latitude climate events and decoupled seasonal trends during the Eemian. Nature communications, 9(1), 2851.
• Aalto, J., Scherrer, D., Lenoir, J., Guisan, A., & Luoto, M. (2018). Biogeophysical controls on soil-atmosphere thermal differences: implications on warming Arctic ecosystems. Environmental Research Letters, 13(7), 074003.
• Greiser, C., Meineri, E., Luoto, M., Ehrlén, J., & Hylander, K. (2018). Monthly microclimate models in a managed boreal forest landscape. Agricultural and Forest Meteorology, 250, 147-158.
• Aalto, J. A., Pirinen, P. & Jylhä, K. (2016) New gridded daily climatology of Finland: permutation-based uncertainty estimates and temporal trends in climate. Journal of Geophysical Research : Atmospheres 121, 3807–3823.
• Salonen, J.S., Luoto, M. , Alenius, T., Heikkilä, M., Seppä, H., Telford, R. & Birks J. (2014) Reconstructing palaeoclimatic variables from fossil pollen using boosted regression trees: comparison and synthesis with other quantitative reconstruction methods. Quaternary Science Reviews 88, 69-81.
• Aalto, J., le Roux, P.C., & Luoto, M. (2014) The meso-scale drivers of temperature extremes in high-latitude Fennoscandia. Climate Dynamics 42, 237–252.

Key words: Climate change | Palaeoclimate | Topoclimate

Arctic regions are particularly vulnerable to global change as they comprise of ecosystems that respond strongly to even slight changes in climate or land use, resulting in cascading consequences for Earth systems. Collectively, these effects will alter ground-surface conditions, vegetation, biodiversity, and bio-geochemical fluxes. The lab examines environmental change in the Arctic through questions concerning the interactions of biota, Earth surface processes, and climate. For example, the lab has studied the effects of different climate change scenarios on vegetation, refugia persistence, and Earth surface processes, and investigated the role of soil moisture in climate change impact forecasting. Our multi-layer study designs provide new insights into studying species distributions, ground-surface conditions, and climatic changes, and their interactions.

Links to related articles:

• Virkkala, A. M., Abdi, A. M., Luoto, M. & Metcalfe B. D. (2019). Identifying multidisciplinary research gaps across Arctic terrestrial gradients. Environmental Research Letters.
• Niittynen, P., Heikkinen, R. K., & Luoto, M. (2018). Snow cover is a neglected driver of Arctic biodiversity loss. Nature Climate Change, 8, 997–1001.
• Virkkala, A. M., Virtanen, T., Lehtonen, A., Rinne, J., & Luoto, M. (2018). The current state of CO2 flux chamber studies in the Arctic tundra: a review. Progress in Physical Geography: Earth and Environment, 42(2), 162-184.
• Niskanen, A., Luoto, M. , Väre, H. & Heikkinen, R.K. (2017) Models of Arctic-alpine refugia highlight importance of climate and local topography. Polar Biology (in press - online).
• Mod, H. & Luoto, M. (2016) Arctic shrubification mediates the impacts of warming climate on changes to tundra vegetation. Environmental Research Letters 11 , no. 12 , 124028.
• le Roux, P.C., Aalto, J. & Luoto, M. (2013) Soil moisture’s underestimated role in climate change impact modelling in low energy systems. Global Change Biology 19, 2965–2975.

• Virtanen, R., Luoto, M., Rämä, T., Mikkola, K., Hjort, J.; Grytnes, J-A., & Birks, J. (2010) Recent vegetation changes in the high-latitude tree-line ecotone are controlled by geomorphologic disturbance, productivity and diversity. Global Ecology and Biogeography 19, 810-821.

Key words: Shrubification | Permafrost | Refugia