0000000000033759
AUTHOR
Juha Aalto
Additional file 7 of Predicting habitat suitability for Ixodes ricinus and Ixodes persulcatus ticks in Finland
Additional file 7: Figure S6. Partial dependency plots for (a) I. ricinus and (b) I. persulcatus solely based on host data.
Statistical upscaling of ecosystem CO2 fluxes across the terrestrial tundra and boreal domain: Regional patterns and uncertainties
The regional variability in tundra and boreal carbon dioxide (CO2) fluxes can be high, complicating efforts to quantify sink-source patterns across the entire region. Statistical models are increasingly used to predict (i.e., upscale) CO2 fluxes across large spatial domains, but the reliability of different modeling techniques, each with different specifications and assumptions, has not been assessed in detail. Here, we compile eddy covariance and chamber measurements of annual and growing season CO2 fluxes of gross primary productivity (GPP), ecosystem respiration (ER), and net ecosystem exchange (NEE) during 1990–2015 from 148 terrestrial high-latitude (i.e., tundra and boreal) sites to a…
Bioclimatic atlas of the terrestrial Arctic
AbstractThe Arctic is the region on Earth that is warming at the fastest rate. In addition to rising means of temperature-related variables, Arctic ecosystems are affected by increasingly frequent extreme weather events causing disturbance to Arctic ecosystems. Here, we introduce a new dataset of bioclimatic indices relevant for investigating the changes of Arctic terrestrial ecosystems. The dataset, called ARCLIM, consists of several climate and event-type indices for the northern high-latitude land areas > 45°N. The indices are calculated from the hourly ERA5-Land reanalysis data for 1950–2021 in a spatial grid of 0.1 degree (~9 km) resolution. The indices are provided in three subsets…
Additional file 3 of Predicting habitat suitability for Ixodes ricinus and Ixodes persulcatus ticks in Finland
Additional file 3: Figure S3. The range (lines) and mean (dots) of model performances over 50 model runs in each model algorithm estimating habitat suitabilities for I. persulcatus in different variable compositions: (a) environmental only, (b) host only, (c) environmental and host, and (d) environmental, host, and suitability for I. ricinus.
Additional file 4 of Predicting habitat suitability for Ixodes ricinus and Ixodes persulcatus ticks in Finland
Additional file 4: Figure S4. The relative contributions of the explanatory variables in the data set of (a) host only, (b) environment only based on the mean ensemble model.
Additional file 8 of Predicting habitat suitability for Ixodes ricinus and Ixodes persulcatus ticks in Finland
Additional file 8: Figure S7. Partial dependency plots for (a) I. ricinus and (b) I. persulcatus based on combined host and environmental data, and habitat suitability data for the other tick species.
Additional file 3 of Predicting habitat suitability for Ixodes ricinus and Ixodes persulcatus ticks in Finland
Additional file 3: Figure S3. The range (lines) and mean (dots) of model performances over 50 model runs in each model algorithm estimating habitat suitabilities for I. persulcatus in different variable compositions: (a) environmental only, (b) host only, (c) environmental and host, and (d) environmental, host, and suitability for I. ricinus.
Additional file 6 of Predicting habitat suitability for Ixodes ricinus and Ixodes persulcatus ticks in Finland
Additional file 6: Figure S5. Partial dependency plots for (a) I. ricinus and (b) I. persulcatus solely based on environmental data.
Additional file 5 of Predicting habitat suitability for Ixodes ricinus and Ixodes persulcatus ticks in Finland
Additional file 5: Table S1. The number of times each model contributed to the final ensemble in different data sets.
Additional file 2 of Predicting habitat suitability for Ixodes ricinus and Ixodes persulcatus ticks in Finland
Additional file 2: Figure S2. The range (lines) and mean (dots) of model performances over 50 model runs in each model algorithm estimating habitat suitabilities for I. ricinus in different variable compositions: (a) environmental only, (b) host only, (c) environmental and host, and (d) environmental, host, and suitability for I. ricinus.
Additional file 7 of Predicting habitat suitability for Ixodes ricinus and Ixodes persulcatus ticks in Finland
Additional file 7: Figure S6. Partial dependency plots for (a) I. ricinus and (b) I. persulcatus solely based on host data.
Additional file 1 of Predicting habitat suitability for Ixodes ricinus and Ixodes persulcatus ticks in Finland
Additional file 1: Figure S1. (a) The sampling strategy for new collections in 2021 was created based on the following criteria. Subdivisions of landscape areas (Area1–Area4), CORINE land cover 2018, a 5-km buffer around existing I. persulcatus occurrences (grey circles), and a 500-m buffer around roads were used to delimit the four sampling areas (light grey lines). For each sampling area, a random sample of 25 collection locations was created depending on the relative shares of forest and meadow categories in each area. (b) The map showing the 2021 results indicates the locations where I. ricinus was found with B. burgdorferi (s.l.)-positive locations.
Additional file 4 of Predicting habitat suitability for Ixodes ricinus and Ixodes persulcatus ticks in Finland
Additional file 4: Figure S4. The relative contributions of the explanatory variables in the data set of (a) host only, (b) environment only based on the mean ensemble model.
Additional file 5 of Predicting habitat suitability for Ixodes ricinus and Ixodes persulcatus ticks in Finland
Additional file 5: Table S1. The number of times each model contributed to the final ensemble in different data sets.
Additional file 8 of Predicting habitat suitability for Ixodes ricinus and Ixodes persulcatus ticks in Finland
Additional file 8: Figure S7. Partial dependency plots for (a) I. ricinus and (b) I. persulcatus based on combined host and environmental data, and habitat suitability data for the other tick species.
Predicting habitat suitability for Ixodes ricinus and Ixodes persulcatus ticks in Finland
AbstractBackgroundTicks are responsible for transmitting several notable pathogens worldwide. Finland lies in a zone where two human-biting tick species co-occur:IxodesricinusandIxodespersulcatus. Tick densities have increased in boreal regions worldwide during past decades, and tick-borne pathogens have been identified as one of the major threats to public health in the face of climate change.MethodsWe used species distribution modelling techniques to predict the distributions ofI.ricinusandI.persulcatus,using aggregated historical data from 2014 to 2020 and new tick occurrence data from 2021. By aiming to fill the gaps in tick occurrence data, we created a new sampling strategy across Fin…
Additional file 6 of Predicting habitat suitability for Ixodes ricinus and Ixodes persulcatus ticks in Finland
Additional file 6: Figure S5. Partial dependency plots for (a) I. ricinus and (b) I. persulcatus solely based on environmental data.
Finnish protected area network in a changing climate
Climate change is projected to cause accelerating impacts on species populations, ecosystems and the services they provide. These impacts are often likely to be negative to biodiversity. Thus traditional static nature conservation should be complemented with climate-wise conservation planning perspectives, so that the dynamic changes in species distributions and assemblages will be properly taken into account (Ref. 1). In particular, the ability of Protected Area (PA) network to support viable species populations and representative habitat types and ecosystems under global environmental changes requires urgent examination. In such assessments, it is imperative to consider also the impact of…
Water as a multifaceted environmental filter of tundra vegetation
The hydrological cycle of tundra has intensified due to accelerated environmental changes. Climatic changes affect tundra vegetation by altering water conditions (1). Plant-available water mediates climate change impacts, namely against rising temperatures and changing snow dynamics (2). Vegetation is limited by water resources, but water forms also major stress and disturbance. However, climate change impact studies often cover water inadequately in cold regions, which are assumed to be energy-limited ecosystems (3). Thus, we used statistical modelling methods to test if the inclusion of different water factors improved species distribution, species richness, and community composition mode…
The underestimated role of winter microclimate for Arctic tundra vegetation
Assessing the impacts of climate change on biodiversity and developing climate-wise conservation planning requires in-depth understanding of the key drivers of species distributions and assemblages. This is particularly important in Arctic environments which will face the most notable climatic changes worldwide. The search for main determinants of biodiversity patterns in high-latitude ecosystems has focused on growing season conditions, but there is increasing amount of evidence suggesting that wintertime conditions can be equally or even more important factors for Arctic biodiversity than summer conditions (1, 2). Yet, large uncertainties exist regarding the role of winter climate in cont…