Biology subjects

Niittynen, P.

Publications and source records attributed to Niittynen, P..

8 recordsLinked to original sources

bioRxiv2026

Predicting global biodiversity via Hubbell regression

Understanding global biodiversity patterns and their drivers is a prerequisite for countering the biodiversity crisis. In this paper, we introduce a novel generalized linear model, Hubbell regression, to estimate a key biodiversity descriptor, the fundamental biodiversity number. This can be converted into a set of biodiversity descriptors, including Shannon and Simpson indices, and more. Hence, quantifying the impact of environmental conditions on the fundamental biodiversity number allows us to predict the general properties of local biodiversity in any setting. In addition to having a strong mathematical foundation, Hubbell regression consistently outperformed current state-of-the-art models in predicting global biodiversity. We apply the method to arthropods, which account for the majority of terrestrial biodiversity. By parameterizing the models using samples of 1.78 million arthropods from 2415 samples collected at 135 sites spanning all continents, we pinpoint the drivers of arthropod biodiversity and its features at the global scale. We find that actual evapotranspiration is the single largest predictor of arthropod diversity and explains nearly 30% of the variation in richness. Moreover, we infer that high human activity has led to a 21.3 % and 29.2% decrease in potential insect richness in tropical and dry zones, respectively, but increased insect richness in polar regions. These insights bring a new foundation for biodiversity research and action.

ecology↗

bioRxiv2026

FennoTraits: Dataset of plant functional traits and community composition in northern European flora

We present here FennoTraits, which is a dataset of plant functional trait and community composition data which we collected from Fennoscandia across northern Finland, Norway, and Sweden in 2016-2025. This dataset has 42 049 abundance estimations and 155 794 functional trait observations from 10 traits representing 373 vascular plant species collected from 1 235 study sites within seven study areas. The trait measurements consist of size-structural, leaf economic, leaf spectral, and reproductive traits. The species represent the majority of the native vascular plant species that occur at the seven study areas, and many of the species occur in all seven areas across the two biomes and their ecotone: tundra and boreal forests. Each study area has distinct characteristics and a range of habitats: tundra, meadows, wetlands, shrublands, and boreal forests. These areas are under low anthropogenic influence, and many of the sites are within protected areas that are reserved for nature conservation and scientific research. Finally, we provide with this dataset a general description of the main trait patterns and profiles of the northern European flora.

plant biology↗

bioRxiv2026

NordicTraits: imputed species-level functional trait dataset for vascular plants of Denmark, Finland, Iceland, Norway and Sweden

The NordicTraits dataset provides the first comprehensive, imputed, and openly available species-level functional trait resource for all native vascular plants across Denmark, Finland, Iceland, Norway, and Sweden. Functional traits such as plant height, seed mass, and leaf nitrogen content are critical for understanding plant strategies, ecosystem processes including the services they provide to human society, and predicting biodiversity responses to environmental change. The Nordic region has a rich botanical history. However, the absence of a unified trait database has limited trait-based ecological research in this region that is under rapid climate change. To address this gap, we compiled and harmonized trait data from major global databases and regional sources, covering 3,099 vascular plant species. We utilized all together 205 traits in the imputation model with the source data covering, on average, 54% (5-81%) of the species. We employed rigorous data cleaning, taxonomic standardization, and a Random Forest-based imputation framework to fill the missing values, while incorporating phylogenetic information to improve accuracy. The final dataset includes 44 selected key functional traits with no missing values, including both continuous and categorical traits and enabling robust analyses of plant strategies and responses to environmental gradients across the regions diverse temperate, boreal, arctic, and alpine ecosystems. The dataset is particularly valuable for large-scale, multi-species studies, and those focusing on functional community assessments across a wide range of vegetation types. NordicTraits facilitates the paradigm shift from species-based to trait-based ecology, supporting research on biodiversity, conservation, and climate change impact predictions in northern Europe.

ecology↗

bioRxiv2024

A Gridded Microclimate Dataset from a Sub-Arctic Biodiversity Hotspot in Finland

Microclimate measurements are crucial for explaining and predicting functions and patterns in nature, yet the availability of microclimate data often poses a challenge. This study introduces a dataset comprising 63 spatially continuous microclimate surfaces for the Kilpisjarvi region in northwestern Finland. The study region is a biodiversity hotspot for arctic-alpine flora and fauna and one of the most extensively investigated regions in Northern Europe. The data were gathered through a collaborative network of microclimate loggers, encompassing 430 measurement locations that comprehensively cover the 300 km2 landscape under study. We employed predominantly well-performing Random Forest models to project microclimate variables across the study area at a 3-metre spatial resolution. The high-resolution and extensive spatial coverage of the dataset facilitates examination of microclimate characteristics and variability across this sub-Arctic region, providing a valuable resource for both theoretical and applied research, as well as for biodiversity conservation.

ecology↗

bioRxiv2021

The activity and functions of subarctic soil microbial communities vary across vegetation types

Increased microbial activity in high-latitude soils due to climate change might lead to higher greenhouse gas (GHG) emissions. However, mechanisms of microbial GHG production and consumption in tundra soils are not thoroughly understood. We analyzed 116 soil metatranscriptomes from 73 sites in the Finnish sub-Arctic to investigate how the diversity and functional potential of bacterial and archaeal communities vary across vegetation types and soil layers. Soils differed in physicochemical conditions, with meadow soils being characterized by higher pH and low soil organic matter (SOM) and carbon/nitrogen ratio whereas dwarf shrub-dominated ecosystems with high SOM and low pH. Actinobacteria, Acidobacteria, Alphaproteobacteria, and Planctomycetes predominated all communities but there were significant differences on genus level between vegetation types, as plant polymer degrading groups were more active in shrub-dominated soils compared to meadows. Given that climate change scenarios predict expansion in dwarf shrubs at high latitudes, our results indicate that the rate of carbon turnover in tundra soils may increase in the future. Additionally, transcripts of methanotrophs were detected in the mineral layer of all soils, potentially moderating methane fluxes from deeper layers. In all, this study provides new insights into possible shifts in tundra microbial diversity and activity with climate change.

microbiology↗

bioRxiv2019

Plant community functional composition and diversity drive fine-scale variability in carbon cycling in the tundra

O_LIThe functional composition and diversity of plant communities are globally applicable predictors of ecosystem functioning. Yet, it is unclear how traits influence carbon cycling. This is an important question in the tundra where vegetation shifts are occurring across the entire biome, and where soil organic carbon stocks are large and vulnerable to environmental change. C_LIO_LITo study how traits affect carbon cycling in the tundra, we built a model that explained carbon cycling (above-ground and soil organic carbon stocks, and photosynthetic and respiratory fluxes) with abiotic conditions (air temperature and soil moisture), plant community functional composition (average plant height, leaf dry matter content (LDMC) and specific leaf area (SLA)), and functional diversity (weighted standard deviations of the traits). Data was collected from an observational study setting from northern Finland. C_LIO_LIThe explanatory power of the models was relatively high, but a large part of variation in soil organic carbon stocks remained unexplained. Plant height was the strongest predictor of all carbon cycling variables except soil carbon stocks. Communities of larger plants were associated with larger CO2 fluxes and above-ground carbon stocks. Communities with fast leaf economics (i.e. high SLA and low LDMC) had higher photosynthesis, ecosystem respiration, and soil organic carbon stocks. C_LIO_LIWithin-community variability in plant height, SLA, and LDMC affected ecosystem functions differently. SLA and LDMC diversity increased CO2 fluxes and soil organic carbon stocks, while height diversity increased the above-ground carbon stock. The contributions of functional diversity metrics to ecosystem functioning were about as important as those of average SLA and LDMC traits. C_LIO_LISynthesis: Plant height, SLA, and LDMC have clear effects on tundra carbon cycling. The importance of functional diversity highlights a potentially important mechanism controlling the vast tundra carbon pools that should be better recognized. More research on root traits and decomposer communities is needed to understand the below-ground mechanisms regulating carbon cycling in the tundra. C_LI

ecology↗

bioRxiv2019

Woody plants constructing tundra soils

In tundra, woody plants are expanding towards higher latitudes and altitudes due to increasingly favourable climatic conditions. Their expansion may also occur through increases in the coverage and height of the plants. These shifts may cascade further across the ecosystem, such as in the foundations of tundra: that is, in the soils. Yet, little is known about the effects woody plants have on local soil conditions. Here, we examined if the coverage and height of woody plants affect the growing-season soil moisture and temperature as well as soil organic carbon stocks. We carried out a field observation study in a dwarf shrub-dominated tundra and built a hierarchical model. We found that, after controlling for other possible factors influencing woody plants and soil conditions (namely, topography, snow, and the overall plant coverage), the coverage of woody plants inversely correlated with all three soil conditions. Yet, we found no link between the woody plant height to the soil variables. This indicates that woody plants affect local soil conditions in various ways, depending upon whether their expansion occurs though the growth of coverage or their height. Nevertheless, woody plants likely alter the very ground of the entire tundra system and feedback into the global climate system through the water, energy, and carbon cycles of tundra.

ecology↗

bioRxiv2019

Snow is an important control of plant community functional composition

The functional composition of plant communities is a critical modulator of climate change impacts on ecosystems, but it is not a simple function of regional climate. In the Arctic tundra, where climate change is proceeding the most rapidly, communities have not shifted their trait composition as predicted by spatial temperature-trait relationships. Important causal pathways are thus missing from models of trait composition change. Here, we study causes of plant community functional variation in a tundra landscape. We consider the community weighted means of plant vegetative height, as well as two traits related to the leaf economic spectrum. Specifically, we model their responses to locally measured summer air temperature, snow conditions, and soil resource levels. For each of the traits we also quantify the importance of intraspecific trait variation (ITV) for between-community functional differences and trait-environment matching. Our study shows that in a tundra landscape 1) snow is the most influential abiotic variable affecting functional composition, 2) vegetation height is under weak local environmental control, whereas leaf economics is under strong local environmental control, 3) the relative magnitude of ITV differs between traits, and 4) ITV is not very consequential for community-level trait-environment relationships.

ecology↗