Global data on earthworm abundance, biomass, diversity and corresponding environmental properties

Publisher Copyright: © 2021, The Author(s).Earthworms are an important soil taxon as ecosystem engineers, providing a variety of crucial ecosystem functions and services. Little is known about their diversity and distribution at large spatial scales, despite the availability of considerable amounts of local-scale data. Earthworm diversity data, obtained from the primary literature or provided directly by authors, were collated with information on site locations, including coordinates, habitat cover, and soil properties. Datasets were required, at a minimum, to include abundance or biomass of earthworms at a site. Where possible, site-level species lists were included, as well as the abundance and biomass of individual species and ecological groups. This global dataset contains 10,840 sites, with 184 species, from 60 countries and all continents except Antarctica. The data were obtained from 182 published articles, published between 1973 and 2017, and 17 unpublished datasets. Amalgamating data into a single global database will assist researchers in investigating and answering a wide variety of pressing questions, for example, jointly assessing aboveground and belowground biodiversity distributions and drivers of biodiversity change.Peer reviewe

Global data on earthworm abundance, biomass, diversity and corresponding environmental properties

Earthworms are an important soil taxon as ecosystem engineers, providing a variety of crucial ecosystem functions and services. Little is known about their diversity and distribution at large spatial scales, despite the availability of considerable amounts of local-scale data. Earthworm diversity data, obtained from the primary literature or provided directly by authors, were collated with information on site locations, including coordinates, habitat cover, and soil properties. Datasets were required, at a minimum, to include abundance or biomass of earthworms at a site. Where possible, site-level species lists were included, as well as the abundance and biomass of individual species and ecological groups. This global dataset contains 10,840 sites, with 184 species, from 60 countries and all continents except Antarctica. The data were obtained from 182 published articles, published between 1973 and 2017, and 17 unpublished datasets. Amalgamating data into a single global database will assist researchers in investigating and answering a wide variety of pressing questions, for example, jointly assessing aboveground and belowground biodiversity distributions and drivers of biodiversity change

Multi layered modeling of particulate matter removal by a growing forest over time, from plant surface deposition to washoff via rainfall

Airborne fine particulate matter (PM) is responsible for the most severe health effects induced by air pollution in Europe. Vegetation, and forests in particular, can play a role in mitigating this pollution since they have a large surface area to filter PM out of the air. Many studies have solely focused on dry deposition of PM onto the tree surface, but deposited PM can be resuspended to the air or may be washed off by precipitation dripping from the plants to the soil. It is only the latter process that represents a net-removal from the atmosphere. To quantify this removal all these processes should be accounted for, which is the case in our modeling framework. Practically, a multilayered PM removal model for forest canopies is developed. In addition, the framework has been integrated into an existing forest growth model in order to account for changes in PM removal efficiency during forest growth. A case study was performed on a Scots pine stand in Belgium (Europe), resulting for 2010 in a dry deposition of 31 kg PM 2.5 (PM < 2.5 μm) ha−1 yr−1 from which 76% was resuspended and 24% washed off. For different future emission reduction scenarios from 2010 to 2030, with altering PM2.5 air concentration, the avoided health costs due to PM2.5 removal was estimated to range from 915 to 1075 euro ha−1 yr−1. The presented model could even be used to predict nutrient input via particulate matter though further research is needed to improve and better validate the model

Particulate matter removal by ecosystems matters: introduction of an improved model, applied to a Scots pine stand

Airborne fine particulate matter (PM) is responsible for the most severe health effects induced by air pollution in Europe. Vegetation, and forests in particular, can play a role in mitigating this pollution since they have a large surface area to filter PM out of the air. Many studies have solely focused on dry deposition of PM onto the tree surface, but deposited PM can be resuspended to the air or may be washed off by precipitation, dripping from the plants to the soil. It is only the latter process that represents a net-removal from the atmosphere. To quantify this removal all these processes should be accounted for, which is the case in our modeling framework. Practically, a multilayered PM removal model is developed. The considered processes are depicted in the figure below. In addition, the framework has been integrated into an existing forest growth model in order to account for changes in PM removal efficiency during forest growth. A case study was performed on a Scots pine stand in Belgium (Europe), with calculation of particulate matter removal per halfhour, resulting for 2010 in a dry deposition of 31 kg PM2.5 (PM < 2.5 µm) ha-1 yr-1 from which 76% was resuspended and 24% washed off. For different future emission reduction scenarios from 2010 to 2030, with altering PM2.5 air concentration, the avoided health costs due to PM2.5 removal was estimated to range from 915 to 1075 euro ha-1 yr-1. The presented model could even be used to predict nutrient input via particulate matter though further research is needed to improve and better validate the model. (Schaubroeck et al., 2014; Environmental Science & Technology

Multilayered modeling of particulate matter removal by a growing forest over time, from plant surface deposition to washoff via rainfall

Airborne fine particulate matter (PM) is responsible for the most severe health effects induced by air pollution in Europe. Vegetation, and forests in particular, can play a role in mitigating this pollution since they have a large surface area to filter PM out of the air. Many studies have solely focused on dry deposition of PM onto the tree surface, but deposited PM can be resuspended to the air or may be washed off by precipitation dripping from the plants to the soil. It is only the latter process that represents a net-removal from the atmosphere. To quantify this removal all these processes should be accounted for, which is the case in our modeling framework. Practically, a multilayered PM removal model for forest canopies is developed. In addition, the framework has been integrated into an existing forest growth model in order to account for changes in PM removal efficiency during forest growth. A case study was performed on a Scots pine stand in Belgium (Europe), resulting for 2010 in a dry deposition of 31 kg PM 2.5 (PM < 2.5 μm) ha−1 yr−1 from which 76% was resuspended and 24% washed off. For different future emission reduction scenarios from 2010 to 2030, with altering PM2.5 air concentration, the avoided health costs due to PM2.5 removal was estimated to range from 915 to 1075 euro ha−1 yr−1. The presented model could even be used to predict nutrient input via particulate matter though further research is needed to improve and better validate the model

Multilayered Modeling of Particulate Matter Removal by a Growing Forest over Time, From Plant Surface Deposition to Washoff via Rainfall

Airborne fine particulate matter (PM) is responsible for the most severe health effects induced by air pollution in Europe. Vegetation, and forests in particular, can play a role in mitigating this pollution since they have a large surface area to filter PM out of the air. Many studies have solely focused on dry deposition of PM onto the tree surface, but deposited PM can be resuspended to the air or may be washed off by precipitation dripping from the plants to the soil. It is only the latter process that represents a net-removal from the atmosphere. To quantify this removal all these processes should be accounted for, which is the case in our modeling framework. Practically, a multilayered PM removal model for forest canopies is developed. In addition, the framework has been integrated into an existing forest growth model in order to account for changes in PM removal efficiency during forest growth. A case study was performed on a Scots pine stand in Belgium (Europe), resulting for 2010 in a dry deposition of 31 kg PM_2.5 (PM < 2.5 μm) ha^–1 yr^–1 from which 76% was resuspended and 24% washed off. For different future emission reduction scenarios from 2010 to 2030, with altering PM_2.5 air concentration, the avoided health costs due to PM_2.5 removal was estimated to range from 915 to 1075 euro ha^–1 yr^–1. The presented model could even be used to predict nutrient input via particulate matter though further research is needed to improve and better validate the model

Editor, International Journal of Maritime Engineering, vol.158 Part A3

Cell proliferation is the main driving force for plant growth. Although genome sequence analysis revealed a high number of cell cycle genes in plants, little is known about the molecular complexes steering cell division. In a targeted proteomics approach, we mapped the core complex machinery at the heart of the Arabidopsis thaliana cell cycle control. Besides a central regulatory network of core complexes, we distinguished a peripheral network that links the core machinery to up- and downstream pathways. Over 100 new candidate cell cycle proteins were predicted and an in-depth biological interpretation demonstrated the hypothesis-generating power of the interaction data. The data set provided a comprehensive view on heterodimeric cyclin-dependent kinase (CDK)–cyclin complexes in plants. For the first time, inhibitory proteins of plant-specific B-type CDKs were discovered and the anaphase-promoting complex was characterized and extended. Important conclusions were that mitotic A- and B-type cyclins form complexes with the plant-specific B-type CDKs and not with CDKA;1, and that D-type cyclins and S-phase-specific A-type cyclins seem to be associated exclusively with CDKA;1. Furthermore, we could show that plants have evolved a combinatorial toolkit consisting of at least 92 different CDK–cyclin complex variants, which strongly underscores the functional diversification among the large family of cyclins and reflects the pivotal role of cell cycle regulation in the developmental plasticity of plants

Effects of tree pollen on throughfall element fluxes in European forests

The effects of tree pollen on precipitation chemistry are not fully understood and this can lead to misinterpretations of element deposition in European forests. We investigated the relationship between forest throughfall (TF) element fluxes and the Seasonal Pollen Integral (SPIn) using linear mixed-effects modelling (LME). TF was measured in 1990–2018 during the main pollen season (MPS, arbitrary two months) in 61 managed, mostly pure, even-aged Fagus, Quercus, Pinus, and Picea stands which are part of the ICP Forests Level II network. The SPIn for the dominant tree genus was observed at 56 aerobiological monitoring stations in nearby cities. The net contribution of pollen was estimated as the TF flux in the MPS minus the fluxes in the preceding and succeeding months. In stands of Fagus and Picea, two genera that do not form large amounts of flowers every year, TF fluxes of potassium (K+), ammonium-nitrogen (NH4+-N), dissolved organic carbon (DOC), and dissolved organic nitrogen (DON) showed a positive relationship with SPIn. However- for Fagus- a negative relationship was found between TF nitrate-nitrogen (NO3−-N) fluxes and SPIn. For Quercus and Pinus, two genera producing many flowers each year, SPIn displayed limited variability and no clear association with TF element fluxes. Overall, pollen contributed on average 4.1–10.6% of the annual TF fluxes of K+ > DOC > DON > NH4+-N with the highest contribution in Quercus > Fagus > Pinus > Picea stands. Tree pollen appears to affect TF inorganic nitrogen fluxes both qualitatively and quantitatively, acting as a source of NH4+-N and a sink of NO3−-N. Pollen appears to play a more complex role in nutrient cycling than previously thought