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Biochar is being discussed as a soil amendment to improve soil fertility and mitigate climate change. While biochar interactions with soil microbial biota have been frequently studied, interactions with soil mesofauna are understudied. We here present an experiment in which we tested if the collembolan Folsomia candida I) can transport biochar particles, II) if yes, how far the particles are distributed within 10 days, and III) if it shows a preference among biochars made from different feedstocks, i.e. pine wood, pine bark and spelt husks. In general, biochar particles based on pine bark and pine wood were consistently distributed significantly more than those made of spelt husks, but all types were transported more than 4cm within 10 days. Additionally, we provide evidence that biochar particles can become readily attached to the cuticle of collembolans and hence be transported, potentially even over large distances. Our study shows that the soil mesofauna can indeed act as a vector for the transport of biochar particles and show clear preferences depending on the respective feedstock, which would need to be studied in more detail in the future.
1. Microplastics in soils have become an important threat for terrestrial systems as they may potentially alter the geochemical/biophysical soil environment and can interact with drought. As microplastics may affect soil water content, this could exacerbate the well-known negative effects of drought on ecosystem functionality. Thus, functions including litter decomposition, soil aggregation or those related with nutrient cycling can be altered. Despite this potential interaction, we know relatively little about how microplastics, under different soil water conditions, affect ecosystem functions and multifunctionality.
2. To address this gap, we performed an experiment using grassland plant communities growing in microcosms. Microplastic fibres (absent, present) and soil water conditions (well-watered, drought) were applied in a fully factorial design. At harvest, we measured soil ecosystem functions related to nutrient cycling (beta-glucosaminidase, beta-D-cellobiosidase, phosphatase, beta-glucosidase enzymes), respiration, nutrient retention, pH, litter decomposition and soil aggregation (water stable aggregates). As terrestrial systems provide these functions simultaneously, we also assessed ecosystem multifunctionality, an index that encompasses the array of ecosystem functions measured here.
3. We found that the interaction between microplastic fibres and drought affected ecosystem functions and multifunctionality. Drought had negatively affected nutrient cycling by decreasing enzymatic activities by up to similar to 39%, while microplastics increased soil aggregation by similar to 18%, soil pH by similar to 4% and nutrient retention by up to similar to 70% by diminishing nutrient leaching. Microplastic fibres also impacted soil enzymes, respiration and ecosystem multifunctionality, but importantly, the direction of these effects depended on soil water status. That is, under well-watered conditions, these functions decreased with microplastic fibres by up to similar to 34% while under drought they had similar values irrespective of the microplastic presence, or tended to increase with microplastics. Litter decomposition had a contrary pattern increasing with microplastics by similar to 6% under well-watered conditions while decreasing to a similar percentage under drought.
4. Synthesis and applications. Single ecosystem functions can be positively or negatively affected by microplastics fibres depending on soil water status. However, our results suggest that microplastic fibres may cause negative effects on ecosystem soil multifunctionality of a similar magnitude as drought. Thus, strategies to counteract this new global change factor are necessary.
Soil structure, the complex arrangement of soil into aggregates and pore spaces, is a key feature of soils and soil biota. Among them, filamentous saprobic fungi have well-documented effects on soil aggregation. However, it is unclear what properties, or traits, determine the overall positive effect of fungi on soil aggregation. To achieve progress, it would be helpful to systematically investigate a broad suite of fungal species for their trait expression and the relation of these traits to soil aggregation. Here, we apply a trait-based approach to a set of 15 traits measured under standardized conditions on 31 fungal strains including Ascomycota, Basidiomycota, and Mucoromycota, all isolated from the same soil. We find large differences among these fungi in their ability to aggregate soil, including neutral to positive effects, and we document large differences in trait expression among strains. We identify biomass density, i.e., the density with which a mycelium grows (positive effects), leucine aminopeptidase activity (negative effects) and phylogeny as important factors explaining differences in soil aggregate formation (SAF) among fungal strains; importantly, growth rate was not among the important traits. Our results point to a typical suite of traits characterizing fungi that are good soil aggregators, and our findings illustrate the power of employing a trait-based approach to unravel biological mechanisms underpinning soil aggregation. Such an approach could now be extended also to other soil biota groups. In an applied context of restoration and agriculture, such trait information can inform management, for example to prioritize practices that favor the expression of more desirable fungal traits.
Although temporal heterogeneity is a well-accepted driver of biodiversity, effects of interannual variation in land-use intensity (LUI) have not been addressed yet. Additionally, responses to land use can differ greatly among different organisms; therefore, overall effects of land-use on total local biodiversity are hardly known. To test for effects of LUI (quantified as the combined intensity of fertilization, grazing, and mowing) and interannual variation in LUI (SD in LUI across time), we introduce a unique measure of whole-ecosystem biodiversity, multidiversity. This synthesizes individual diversity measures across up to 49 taxonomic groups of plants, animals, fungi, and bacteria from 150 grasslands. Multidiversity declined with increasing LUI among grasslands, particularly for rarer species and aboveground organisms, whereas common species and belowground groups were less sensitive. However, a high level of interannual variation in LUI increased overall multidiversity at low LUI and was even more beneficial for rarer species because it slowed the rate at which the multidiversity of rare species declined with increasing LUI. In more intensively managed grasslands, the diversity of rarer species was, on average, 18% of the maximum diversity across all grasslands when LUI was static over time but increased to 31% of the maximum when LUI changed maximally over time. In addition to decreasing overall LUI, we suggest varying LUI across years as a complementary strategy to promote biodiversity conservation.
Global change, especially land-use intensification, affects human well-being by impacting the delivery of multiple ecosystem services (multifunctionality). However, whether biodiversity loss is a major component of global change effects on multifunctionality in real-world ecosystems, as in experimental ones, remains unclear. Therefore, we assessed biodiversity, functional composition and 14 ecosystem services on 150 agricultural grasslands differing in land-use intensity. We also introduce five multifunctionality measures in which ecosystem services were weighted according to realistic land-use objectives. We found that indirect land-use effects, i.e. those mediated by biodiversity loss and by changes to functional composition, were as strong as direct effects on average. Their strength varied with land-use objectives and regional context. Biodiversity loss explained indirect effects in a region of intermediate productivity and was most damaging when land-use objectives favoured supporting and cultural services. In contrast, functional composition shifts, towards fast-growing plant species, strongly increased provisioning services in more inherently unproductive grasslands.
Research synthesis on simple yet general hypotheses and ideas is challenging in scientific disciplines studying highly context-dependent systems such as medical, social, and biological sciences. This study shows that machine learning, equation-free statistical modeling of artificial intelligence, is a promising synthesis tool for discovering novel patterns and the source of controversy in a general hypothesis. We apply a decision tree algorithm, assuming that evidence from various contexts can be adequately integrated in a hierarchically nested structure. As a case study, we analyzed 163 articles that studied a prominent hypothesis in invasion biology, the enemy release hypothesis. We explored if any of the nine attributes that classify each study can differentiate conclusions as classification problem. Results corroborated that machine learning can be useful for research synthesis, as the algorithm could detect patterns that had been already focused in previous narrative reviews. Compared with the previous synthesis study that assessed the same evidence collection based on experts' judgement, the algorithm has newly proposed that the studies focusing on Asian regions mostly supported the hypothesis, suggesting that more detailed investigations in these regions can enhance our understanding of the hypothesis. We suggest that machine learning algorithms can be a promising synthesis tool especially where studies (a) reformulate a general hypothesis from different perspectives, (b) use different methods or variables, or (c) report insufficient information for conducting meta-analyses.
Interactions between soil microorganisms and plants can play a vital role for plant fitness and therefore also for plant community composition and biodiversity. However, little is known about how biotic plant soil interactions influence the local dominance and abundance of plant species and whether specific taxonomic or functional groups of plants are differentially affected by such biotic soil-effects. In two greenhouse experiments, we tested the biotic soil-effects of 33 grassland species differing in individual size and local abundance. We hypothesized that large plants that are not locally dominant (despite their size-related competitive advantage enabling them to potentially outshade competitors) are most strongly limited by negative biotic soil-effects. We sampled soils at the opposite ends of a gradient in land-use intensity in temperate grasslands to account for putative modulating effects of land-use intensity on biotic soil-effects.
As hypothesized, large, but non-dominant species (especially grasses) experienced more negative biotic soil-effects compared with small and abundant plant species. Land-use intensity had contrasting effects on grasses and herbs resulting in more negative biotic soil-effects for grasses in less intensively managed grasslands. We conclude that biotic soil-effects contribute to the control of potentially dominant plants and hence enable species coexistence and biodiversity especially in species-rich less intensively managed grasslands.
Plant community assembly at small scales: Spatial vs. environmental factors in a European grassland
(2015)
Dispersal limitation and environmental conditions are crucial drivers of plant species distribution and establishment. As these factors operate at different spatial scales, we asked: Do the environmental factors known to determine community assembly at broad scales operate at fine scales (few meters)? How much do these factors account for community variation at fine scales? In which way do biotic and abiotic interactions drive changes in species composition?
We surveyed the plant community within a dry grassland along a very steep gradient of soil characteristics like pH and nutrients. We used a spatially explicit sampling design, based on three replicated macroplots of 15 x 15, 12 x 12 and 12 x 12 m in extent. Soil samples were taken to quantify several soil properties (carbon, nitrogen, plant available phosphorus, pH, water content and dehydrogenase activity as a proxy for overall microbial activity). We performed variance partitioning to assess the effect of these variables on plant composition and statistically controlled for spatial autocorrelation via eigenvector mapping. We also applied null model analysis to test for non-random patterns in species co-occurrence using randomization schemes that account for patterns expected under species interactions.
At a fine spatial scale, environmental factors explained 18% of variation when controlling for spatial autocorrelation in the distribution of plant species, whereas purely spatial processes accounted for 14% variation. Null model analysis showed that species spatially segregated in a non-random way and these spatial patterns could be due to a combination of environmental filtering and biotic interactions. Our grassland study suggests that environmental factors found to be directly relevant in broad scale studies are present also at small scales, but are supplemented by spatial processes and more direct interactions like competition. (C) 2015 Elsevier Masson SAS. All rights reserved.
Biotic plant-soil interactions and land-use intensity are known to affect plant individual fitness as well as competitiveness and therefore plant-species abundances in communities. Therefore, a link between soil biota and land-use intensity on local abundance of plant species in grasslands can be expected. In two greenhouse experiments, we investigated the effects of soil biota from grassland sites differing in land-use intensity on three grass species that vary in local abundances along this land-use gradient. We were interested in those soil-biota effects that are associated with land-use intensity, and whether these effects act directly or indirectly. Therefore, we grew the three plant species in two separate experiments as single individuals and in mixtures and compared their performance. As single plants, all three grasses showed a similar performance with and without soil biota. In contrast, in mixtures growth of the species in response to the presence or absence of soil biota differed. This resulted in different soil-biota effects that tend to correspond with patterns of species-specific abundances in the field for two of the three species tested. Our results highlight the importance of indirect interactions between plants and soil microorganisms and suggest that combined effects of soil biota and plant-plant interactions are involved in structuring plant communities. In conclusion, our experiments suggest that soil biota may have the potential to alter effects of plant-plant interactions and therefore influence plant-species abundances and diversity in grasslands.