 With all of you today, I'm sure so far you've been enjoying following the symposium. My name is Lydia Chabala and I'll be the moderator for the two hours in this particular parallel session. And I'm from the ITPS. So during the first hour, what we will do will listen to four presentations and each will be 10 minutes. And I would kindly request colleagues who are presenters in this session to stick to the 10 minutes so that we can have a question and answer session at the end. So what I would suggest is that when you have gone nine minutes, I'll send a reminder just to indicate that you are remaining with one minute. And all this really is so that we have some time for question and answer session. And it is important that in the end, we will have a 20 minutes that is allocated for question and answer session. So after the first four presenters, we have 20 minutes of Q&A. And then immediately after that, we will start with the second one hour session where we have another four presentations. So before starting, I think I would ask you kindly to check the Zoom chat for the rules and information regarding this particular session and where it will be posted. And during our Q&A session, I would request you to use the chat function in the chat box there, you can post your questions and then we'll highlight some of as you post your questions. Please indicate which presenter your question is addressed to and we'll be able to pick one or two questions for each presenter so that they are answered live. But that doesn't mean that all the questions will not be answered. All of them will be answered, but some of them will be answered via the chat function. And the host for this session for technical issues is Magdalene. She is here to help us for any technical issues so please do not hesitate to write to her directly using the private messaging option in the chat functions. And so without much further ado, I would now like to go to the floor. Ms. Mendes, I said the last name from Brazil and they are presenting to us on the topic, soil bioanalysis, a simple and effective tool to assess and interpret soil health. Please, it's your time, go ahead. Maybe she's not with us. Ms. Mendes in the room or somebody called Brapa from Brazil. Are they in the room? Okay, it seems perhaps. She's unmuting herself. It was in between. Okay. Could you allow me to share my screen? Yes, it should work out. Okay, here we go. Can you see my screen now? Yes. Okay, greetings from Brazil, everyone. My name is Edda Mendes. I'm a soil microbiologist from in Brapa, which is the Brazilian agricultural corporation for research. And today I would like to thank the organizing committee for the opportunity of being here to talk about soil bioanalysis, soil bio, which is the simple and effective tool for on-farm soil health assessments that we are using here in Brazil. Now, since July 2020, we are living this new moment in Brazil, where for the first time ever, Brazilian farmers now can assess how is the biological function of their soils by using two soil enzymes, better glucose days from the carbon cycle and aerosol for days from the sulfur cycle. And in a pioneering initiative in Brapa has capacitated eight commercial soil labs to perform soil enzymes as part of the routine commercial soil analysis. The choice of better glucose days and aerosol for days was the result of a 20 years of research in the Brazilian serratus oxysauce. Among the main advantages of using these two soil enzymes, we can say that they were the most sensitive to changes in soil and crop management practices. They are related to soil functioning, nutrient cycling, they are interpretable, precise, coherent. Then the analytical procedures involve simple and inexpensive procedures, and they can be performed directly in their dry soil samples. Also, in long-term field experiments, we were able to observe that these two soil enzymes have very strong and robust relationships with crop yield and also with soil gamut matter, which is very important from both economic and environmental aspects. In terms of how to evaluate soil sampling for soil bio is similar to soil chemical analysis. The only thing that changes is that we have two samples to soil at zero to ten centimeters soil depth. In terms of when to evaluate, it is done at post-hovers coincided with soil sampling for chemistry. And in the commercial soil labs, the soil samples can be air-dried, which really helps a lot. And in order to interpret the individual values of these two soil enzymes, we have developed an interpretation strategy based on the same principles applied to soil nutrients calibration. So basically, again, in these long-term field experiments, we have these response curves where we relate soil enzyme levels in the soil with crop yields, and soil enzyme levels necessary to reach 8% of maximum-grade yield are considered adequate. Soil enzyme levels to reach 40% of maximum-grade yield are considered low. And based on this strategy, we have developed interpretation algorithms, which allow us to calculate enzyme reference levels as a function of the clay content. And so far, these algorithms are specific for annual crops in the Cerrado Bayon. A very important component of the soil biotechnology is what we call the soil quality interpretation module, which is a web platform that connects commercial soil labs to our computer servers here at Embrapa. And by using this platform, we can automatically interpret the enzyme determinations performed by the commercial soil labs, and at the same time, we can calculate soil quality indexes. The conceptual model for the calculation of the soil quality index integrates biological and chemical indicators in three soil functions. Nutrient cycle, which is related to better because it is an aerosophatase. Nutrient storage, which is associated with soil gain matter and cation exchange capacity. And nutrient supply, which involves acidity, base supply, and fossil supply components. All these three functions are integrated in soil quality index, biological, chemical, and finally at the third to be soil quality index. All these soil quality index and all these function scores, they range from zero to one. The closer to one, the better. And it's important to say that all these soil quality index and function scores were calibrated in relation to grain yield and soil gain can matter again using long-term field experiments. So for instance, the soil quality index necessary to reach 8% of maximum grain yield was considered adequate. Soil quality grade yield necessary to reach 40% of maximum grade yield was considered low. And then we have these five colored skins range from dark red to dark green and scores punctuating between moderate and very low. They are an indication that you do have major soil health constraints and scores range from very high and high to indicate the absence of soil health constraints. Well, from now on, I'm going to show you some kind of the foremost common soil by reports that we have observed so far. And all two results that I'm going to show you from now on were obtained by commercial soil and nitrogen laboratories. Well, soil by report type one is the best one. So here we have high scores for soil enzymes and high scores for soil gain can matter. So nutrient cycle and nutrient storage are in a very good condition. This is how the soil by report looks like every line corresponds for a price in your farm. And here in the column, we do have the enzyme, enzyme measurements or game to matter, the three soil quality index and the three scores for the nutrient functions supply storage and cycle. This soil by report is from plan auto farm, which is one of the biggest farms in Brazil. We are talking here about 14,000 hectares. And this is a very nice situation because it's a win-win situation where we have soil quality associated with high yield for you have an idea. So I've been using this farm can reach as much as five tons per hectare. And we are even able to see the presence of earthworms. This is another kind of soil by report type one. You can see all the green that we have in the screen. So it is a good indication that the soil is in a chemical and biological condition. Very good. Excellent. So by report type two has a low scores for soil enzymes nutrients like and high scores for soil gain can matter. So which means that although soil gain can matter has not yet been affected. There is clearly a decline from the biological perspective. And in this case, our enzymes act as bad news early warning indicators. So it's like the farm has a bomb in its soil and it explodes sometime. So here we can see how the soil by report looks like. So F3 is okay. F2 is okay. But then it comes to nutrient side. You can see that the soil is starting a decline from the biological perspective. Again, this is another type of soil by report type two. Finally, by soil by report type three is the worst case scenario. We have low scores for soil enzymes and low scores for soil gain to matter. Nutrients, nutrient cycle and nutrient storage are compromised. So soil health is in a really critical condition. It's an example of how the soil by report type three looks like. Although F3 nutrient cycle is adequate. We can see that the soil is totally compromised in terms of nutrient cycle and nutrient storage. And this is how soil by so important because now our farmers can have a new vision of their soil that really goes far beyond simply that question of nutrient access or nutrient deficiency. Here's another example of this kind of soil by report type three. Although nutrient supply is in adequate condition, nutrient storage and nutrient cycle totally compromised. Finally, soil by report type two has high scores for soil enzymes and low scores for soil gain to matter. Which means that in this case, although soil gain to matter has been seriously compromised, the system is recovering from the biological perspective. In this case, soil enzymes act as good news early warning indicators. Here's an example. It's a farm in Bahia, 22% clay-contated oxysol, nutrient supply adequate, nutrient cycle good and in soil gain to matter nutrient storage compromised. So indicating that the system is recovering. And this is very important because sometimes the farmers need to know whether their regenerative management practices are really improving their soil health or not. So this kind of by report helps to motivate farmers to keep using their regenerative practices. Well, since it's launched in July 2020, we've been able to create a Brazilian soil health database using that soil quality interpretation module. So far, we have around 3,000 samples in this database. And by looking at the percent distribution of soil samples in the classes, very low, low, moderate, high and very high, we can see that 90% of our soil samples have punctuated high and very high for nutrient supply, which is not a surprise at all. We all knew that. We all knew that. But when we look at nutrient storage and nutrient cycle, we can see that 65% and 6% of our farms have punctuated high and very high, which is really good because it means that the majority of our farms are in a good condition. And this is the first time that our farmers have access to this kind of information. So we hope that from now on, by using soil bio, we can improve the situation. Instead of having 60 and 65% of soil samples in this condition, we can have as much as 9% or even 100%, right? We want productive soils and healthy soils. Well, as a conclusion, I would like to say that the inclusion of these intuptable soil enzymes in routine soil analysis is important for farmers to assess whether their management practices are improving, conserving or degrading soil reserves. In its present stage, soil bias defined for annual crops interserrated by only, but we are talking about 35 million hectares and is simple, practical and scalable. Currently, we have eight commercial soil labs using soil enzymes in assessing the soil quality interpretation module, but by August, we are going to have more than 70 commercial labs included in this project. And in the near future, we want to expand soil bio to other agricultural systems such as sugarcane, coffee pastures and eucalyptus. Here's a picture of all the members of the bioeducators project. These people have worked hard during these past 10 years. And I would like to thank you for your attention. Thank you very much. You were actually within time. That is excellent. We appreciate that. We have some questions for you. You can have a look in the chat function, which will be answered in the end. But now we would like to move to the next presenter. This is Miss Ashley from Cornell in USA. And the theme of discussion is uncovering linkages between soil fauna and ecosystem function using factor analysis and structural equation modeling. So please miss Ashley, if you are in here kindly and mute yourself and go ahead with the presentation. Thank you so much. I really appreciate this opportunity to share these ideas with you all today. I am currently a graduate student in the USA, and I am personally really interested in how we have and can link soil fauna to different ecosystem functions and services. And the foundation for how we address these questions really starts with how we group soil fauna together. Historically, so fun have been grouped together based on different categories like taxonomy body size terrific position and other biological parameters, but largely think about them within the context of their body size groupings. This has then been used to understand how soil fauna impact different ecosystem functions like litter decomposition and soil environment engineering. Other work has explored how these fauna groups respond to changing environmental conditions such as temperature precipitation and litter inputs. However, these fauna groupings assume that fauna impacts on ecosystem functions is tied to their shared biology is therefore boxed in by these preset criteria. These groupings don't allow us to explore how fauna community interactions or how changing environmental conditions affect household of honor impacting different ecosystem functions. So we wanted to let the environment create our fauna groups we wanted to flip that mindset, and instead of using predetermined groups allow the ongoing responses of fauna to environmental conditions to create our groups so we could hopefully get a better understanding of how fauna are impacting different ecosystem functions and services of interest. There are a couple different ways we can group community data primarily different cluster factor analysis but based on our goals common factor analysis was the most appropriate. By using exploratory followed by confirmatory factor analysis, we can create so fauna groups that are based on their overall responses to environmental conditions. I'm going to quickly walk you through this process here I'm showing you an example fauna data set where you would have any number of samples that you collected and any number of taxa that you found in those samples. And as researchers were typically imposing different treatments that are altering environmental conditions. And as we process our fauna we see who they are we know a little bit of background information about them. And the factor analysis does is it ignores all that information and it just looks at the data. It searches for patterns across the entire data set that are similar between taxa. So it can end up creating fauna groups that are a bit non traditional that we wouldn't normally think to. After creating our groups the next step is to explore how these fauna are interacting and affecting different environmental factors. There are two ways we can explore relationships in the environment but based on how we have created our fauna groups structural equation modeling was the most appropriate. There are a couple of different approaches to this type of modeling but the goal of each of them is to determine relationships between variables with directionality, which is perfect for achieving our goal of understanding how fauna are impacting different ecosystem functions. The fault process didn't occur out of nowhere it occurred within the context of a long term cropping systems uniformity trial. So many of you a bit of background on that experiment here now. The organic grains cropping system experiment was started in New York State in 2005. And until 2017 for different cropping systems were implemented, which varied in different cover crop types and frequencies fertilizer inputs and tillage types and intensities. After being in place for 12 years a legacy effects trial was conducted in 2017 to evaluate the legacy effects of these different cropping practices. To do this the entire experiment area was treated uniformly by first mobile board plowing it and dishing and herring it to prepare soil seedbed where storm sandgrass was planted and no further management was occurred before termination. During this legacy effects trial we collected a variety of different response variables, different soil characteristics, soil invertebrates in this case soil mesophony that were collected using real lazy funnel extractions and above ground plant biomass. What we really wanted to see was how these different factors in the environment were impacting crop biomass production. So we chose to use piece by structural equation modeling to explore these relationships. We knew that our soil invertebrates would be an important key to understanding these processes so we wanted to incorporate them in the model and the best way possible. And that's where the factor analysis I described previously comes into play. By applying exploratory followed by confirmatory factor analysis to our soil invertebrates data, we ended up creating two significant factors that were important in our model. This first factor fauna F1 is composed of technosophiety, acarity and phoretic hypoby, all of which are mites that followed in the order or a badda. So taxonomically they're fairly similar but functionally they're interacting with their environment very differently. Our second fauna group is even more interesting it's made up of isotomity on acarity and rhodocarity. So two different Columbolin families and a family of predatory mesostigmatic mites. But keep in mind that factor analysis doesn't pay attention to any background knowledge it's just grouping these fauna together based on their similar response patterns across the entire data set. I applied the same factor analysis techniques to our weeds community data and end up with one significant factor in our model weeds F1, which is composed of yellow nut sedge yellow foxtail and giant foxtail all grassy weeds. And we of course included soaring Sudan grass or crop biomass in our model. The next step was to figure out which characteristics to include so I applied a partial least squares regression to figure out which factors were most related to crop biomass production and ended up with four that were significant in our final model. We saw that soil moisture phosphorus microbial respiration and aggregate stability were important, which nicely ended up representing different physical biological and chemical aspects of soil health. Our final model is made up of four different component models I'm going to walk you through this first one in a bit more detail so you'll understand the schematics. This first component model shows us which factors are predictive of fauna F1 response patterns. You'll see here that phosphorus is negatively impacting fauna F1 as denoted by the great era, likely due to an agricultural systems high phosphorus levels can suppress long growth which would reduce of important food source for this bunch of birds nights. In that same vein microbial respiration, serving as a proxy for microbial community and a food source for these fauna was positively impacting them as demoted by the black arrow. Lastly, we see that soil aggregate stability positively impacted these mites by creating an important stable environment for them. And then when we look within this fauna F1 box I want to point out the two R squared values. The first one is the marginal R squared, which shows us the amount of variation in the data set of the fauna F1 that was described by just those three factors the phosphorus microbial respiration and soil aggregate stability. The second R squared is conditional and incorporates are random variables and by doing that we can explain almost 70% of the response pattern of these fauna. Now our second component component model showed us that microbial respiration was also positively benefiting this group of columbola in mites. Our next component model showed us that soil moisture positively impacted the weeds likely because these are water loving species, especially the yellow nut sedge that are able to thrive in those conditions. And our last component model and arguably the most interesting showed us which factors were directly impacting crop biomass production. Unsurprisingly, our weeds F1 group was negatively impacting crop biomass due to competition for resources. We saw that aggregate stability was benefiting crop biomass production here in New York 2017 was an exceptionally wet growing season so having more aggregate stability allowed the crop to buffer against more severe weather events. Lastly, we saw a positive impact of the fauna F1 on crop biomass production. So we put these component models together in our full model we see two direct indirect relationships come to light. This first indirect relationship shows us that soil moisture was negatively impacting crop biomass when mediated by this weeds group, because the weeds are able to out compete the crop biomass in these conditions. Our next indirect relationship showed us that microbial respiration benefited crop biomass production when mediated on through fauna F1 the two columbola and predatory mites, suggesting that multi terrific interactions between microbes columbola and these mites were benefiting crop biomass production likely through nutrient cycling or some other important mechanism. What I want to point out from this example is that by going through this process we saw a really non traditional group of fauna gave us more information about how they're impacting ecosystem functions in this case crop biomass production. What this means for soil ecology is that factor analysis is a really good technique for identifying correlation structures between tax and diverse data sets, which solely colleges typically work with, especially with men's fauna where you have mites global and other very functionally taxonomically diverse animals. By applying these groups to different modeling techniques we can better understand how fauna change in response to their environment and how this could impact how they're influencing ecosystem functions. By using structural equation modeling we can better understand these fauna community interactions and how they work together to contribute to different ecosystem services of interest. Looking forward we still need to determine which taxonomic level of identification would be best to apply the statistical techniques to our so mess of on a data set was identified down to family level but a finer taxonomic resolution may benefit us with more data and understanding. And of course we want to explore these relationships using these techniques across different environmental context to see if fauna are impacting ecosystem functions in the same manner across a global context. And I'd like to thank everyone that made this work possible, especially Dr. Matthew Ryan and Dr. Kyle wickings and our funding source, and I'll quickly leave you with my contact information and the citation for this paper if you want to follow up after this symposium. Thank you. Okay, that was my microphone thank you Ashley for that interesting presentation it was nice to see that possible that functionally similar fauna which are similar may interact differently with the environment. So we'll have a look in the chat again I think you have one question which we may ask you to answer later on. We would like to move to the next presenter, and the next presenter is Francesca from Italy. And she's looking at monitoring soil biological quality in the veneto region so I hope I'm pronouncing that correctly. Please, Francesca if you are in the room I can see you go ahead and start. Hi. Okay, you can see my presentation. No. No. Okay. And if I have a mistake in your name just you can just correct me. No it's correct. Good morning, my name is Francesca Pocaterra I'm a soil scientist and I work at the soil quality unit of environment protection agency of veneto region. For about 12 years our team has been monitoring the biological quality of the soil in our region. I'm pleased to present you the results of our work. The community of organisms living in the soil is highly sent to the soil degradation. So in 1000 2009 regional agency for environmental prevention and protection, started a soil quality monitoring program in the veneto region. The mission to investigate the soil biological quality in the region to identify references very according to different land uses and to highlight soil degradation or pollution. The soil micro arthropod community was analyzed using a soil biodiversity and quality index, called the QBS ER soil biological quality based on soil arthropod. This is based on the following concept that they either the soil quality they either the number of micro arthropod groups morphologically well adapted to the specific soil habitat. In the Starbucks soil micro arthropod groups morphological well adapt tend to disappear, and only those less adapt will remain soil organism are classified into biological form according to their morphological adaptation to soil environment. Degree of adaptation to soil habitat to depend on the presence and combination of some morphological characteristics. As you can see in the picture miniaturization short antennas and short legs for example, each of these forms is associated with a score named Emmy eco morphological index, which ranges for one to 20. The QBS ER index of value is obtained from the sum of the Emmy score of all collected group based on the principle this is more important that the degree of soil adaptation tank taxonomy. If in a taxonomic group biological form with different EMI score are present, the higher value is selected to represent the group in the QBS ER in this calculation. The organisms belonging to each biological taxon were counted in order to estimate the average density per square meter. The number of total taxa found was also considered. Since 2012 10 monitoring station have been set up in the region for in plain areas to in hilly areas and for in mountain areas. All stations are representative of the regional environment for land use soil characteristics paramaterial and climate condition. 18 different time of land use of both crop or very natural vegetation have been studied collecting present more than 204 QBS ER data. At each site information on soil characteristics was derived from semi detailed soil maps and samples were collected for organic carbon soil texture electrical conductivity MPH analysis. Climate data have also been collected from the closest weather station and for each area, one understable sample was taken in order to measure bulk density and soil moisture statistical processing has been working out with the statistical software. Significant differences between the land uses in tax abundance and QBS ER in this value were tested using the analysis of variants and all the statistical tests using parametric and non parametric methods were also promoted to highlight statistical variability in QBS ER index. As you can see in plain areas analysis of variants point out the relationship between QBS ER index and land use. The first one in red arrow crops differ from whole. It has the lowest QBS ER value. Meadows in green. Meadows, no so sorry, proves to be a good biodiversity pool in orchards and winters. And the soil between the rows are was grass covered, therefore show QBS. I value is despite the even machinery passages and fit of sanitary treatments and forest free farming was found to be the richest habitat in green in the box tank to low human impacts and I biodiversity shrub entry species. Looking at the micro arthropod communities. Akari might is the largest group followed by Collembola and him an opera less taxa with high biological quality a few individuals per square meter are present in arable crops. In meadows, there are more taxa and with him any 20 index and specially protura and deplour. In plain areas, the main factor influencing QBS ER index is land use arable crops have the lowest QBS ER index number of taxa and density per square meter. The effect of some parameters where it was additionally tested texture, pH and organic carbon but only courses so it tested and highest soil salinity were found to provide a lower biological quality. areas wine art and the seedless forest have been studied. The seedless forest showed the higher QBS ER index and number of other part, but the differences were not statistically significant probably due to the short period of observation monitoring only two years. The forest with calcareous substratum present biological quality higher than the seedless forest with acid substratum. In mountain area. Most common forest land use were studied in plain areas meadows and pastures were considered. It is quite clear that forest present biological quality higher than meadows that are more disturbed. Due to the acid litter soil of spruce wood is less hospitable for the microathrapod community that beach forest. This factor is also come. Oh, sorry. This fax is also confirmed by a test that we made by considering two samples beach litter seems to be more hospitable for after pot the conifer wood litter. In a beach liters we find higher QBS here, more total taxa and a more of triple of article per square meter summarizing our conclusions reference QBS here values have been established in different vent region and end users. As already mentioned the in this was found to be helpful to highlight potential solid addition or pollution. And so, arable crops at the low QBS year values due to the environment impact of farming. Meadows are the reservoir of biodiversity and biological richness in orchards and winters, despite to the even machinery trading and phytosanitary treatment, due to the grass cover between roles in the agricultural land uses. And the coexistence of different habitats as the higher protective value for biodiversity, as well as practices preventing landscape simplification as a farming edge and wooded areas. In the last few years, different agronomic techniques effect on biological quality have also been studied, such as minimum tillage so sitting and organic matter. Increase through digest supply. And so it's all and thank you for your attention. Thank you very much Francesca for that very interesting presentation on so quality indices was interesting to see that arable crops at the lowest indices quality. I kindly look through in the chat function after our next presenter we will have a Q&A session. And so the next presenter for this part one is Lydia. This should be my namesake miss Nicola Lydia from University of Pavia in Italy. And the name of the topic is the biodiversity of soil micro funger in Colombia. So please Lydia if you are in the room, share the screen and go ahead. Maybe move closer to the microphone. Of course again try again. Yeah, although it's quite fun. Maybe I use the better now. Better. Yes. So, it's Lydia Nicola. And I work as a researcher at the University of Pavia in Italy. Today I want to talk to you about the biodiversity of soil micro fungi in Colombia. Why do we study cell fungi cell fungal communities are at the base of carbon and nutrient cycles in soil. So they are vital for a good net primary productivity. Fungi in soil can have different roles. They are mainly wood and litter the composers. But they can also be symbiotes of plants like endophyte and mycorrhizal symbiotes, or they can attack enemies of plants like entomopathogenic fungi, nematophagus fungi that attack nematodes and hyper parasite fungi. So studying soil fungi is fundamental for a sustainable use and management of the agro environment. Colombia is in South America and has one of the highest biodiversity rates in the world. It has been estimated that it could host more than 200,000 fungal species. There have been some studies on fungi in Colombia, but the research was discontinuous and the focus was mainly on macroscopic fungi. The aim of our work was to provide an overview of the current state of knowledge on soil micro fungal biodiversity of Colombia, in order to establish a starting point for future investigations on the Colombian territory. So basically we did an online literature search on Colombian soil micro fungi, both in English and in Spanish. Then we divided our results according to the six natural regions of Colombia. So we have the insular region, the Caribbean region, the Pacific region, the Indian region, the Orinoquia, and the Amazon. We found out that the studies on soil fungi of Colombia reported a total of more than 300 identified micro fungal species belonging to 126 different genera. If you recall, I said just before that the estimation of fungal biodiversity in Colombia is more than 200,000 fungal species. So we really have a long way to go and a lot to do research. Here you can see a map of Colombia, where each point is a sampling point of a published article on soil micro fungi. And each point is color coded according to the region. Here in purple, you can see the sampling points for the Indian region, where 16 papers were published on soil micro fungi. So you can see that this region was quite well researched. The other regions, the Caribbean, Orinoquia, and Amazon had only five or seven papers each, so much fewer papers, and also much fewer sampling points. But we can see that in the Amazon, the sampling points are quite numerous and widespread. So even if there are only seven papers, they managed to describe this wide area quite well. For the Pacific region, only two papers were published, while for the insular region, the soil micro fungi were never researched. So we have no information. Then we can look at the number of taxa found, and we see that most of them, most of the taxa found for Colombia were actually found in the Indian region with more than 300 taxa. Then we have the Amazon, Orinoquia, and Caribbean region with 40, 50 taxa each, and finally the Pacific region with only seven taxa. Then we can look at the biodiversity, so at the relative abundance of micro fungi at film level. We can see that the most abundant phila in Colombia were glomeromicota here in green, and ascomicota here in dark red. Then we had some mucoromicota in blue, basidiomicota in pink, and mortierellomicota in yellow. So we think that this diversity we see among the regions is not due to the difference in climate or soil usage, but at the moment is due to the different techniques used for fungal identification. In fact, the techniques for fungal identification is very important. As you can imagine, most of the biodiversity found in the Indian region was found just in one article, this one, that used a method called metabolic coding that is a molecular method that allows the analysis not only of the cultural fungi but also of the uncultural ones. So it allows to take a picture of the site community as a whole. So the most found fungal genera found in Colombia were lomos and acaudospora that are arbor scholar micro riser. And then there were some genera that are ubiquitous in soil like penicillio, mortierella, aspergillus, fusarium, and tricoderma. And then the knowledge about the biological diversity of soil micro fungi is vital for a developing country like Colombia. We've seen that some areas were quite well studied, studied like the Andean region that is the central region and the most populated one. So it's easier to reach for the researchers, while others are virtually unknown like the Pacific and insular region. So it is necessary to do studies on the soil micro flora all over the country to better characterize the fungal flora of Colombia. Then we noticed that most studies focus only on arbor scholar micro riser that are plant roots in biomes. And they are very important for plants but numerically it is quite a small group. So a new focus on two other fungi groups needs to be done like cellulolitic and linear cellulosic fungi or potential biocontrol agents. So further studies on soil micro fungi will contribute to the optimization of our ecosystems, the recovery of highly entropied area and the conservation of natural ecosystems. All problems that are very compelling in a developing country. This work was done in collaboration with the professor Angela Landinez Torres of the Castellanos University in Latunha, Colombia, and my colleague Professor Sorvetosi of the University of Pagliani, Italy. If you're interested in more we published this work on the International Journal of Environmental Research and Public Health, and you can reach me at my email address. Thank you very much for your attention. Thank you very much, Lydia who helped us save some time it's quite tight to keep time. So what we will do now I see a hand up. I would like to suggest the colleague there with the hand up is it as is to kindly type your concerning the chat function so that we are able to keep within the stated time. The question really to each presenter there several in the chat, I will start with the first presenter. There was a question from Frank there. Who noted some negative. Sorry, who noted that who is asking, did you find any direct or indirect influence of red predatory mice on the other soil founder. The question is for for Ashley, not for the first presenter this is for Ashley. So please in a minute, can you answer that question did you find any direct or indirect influence of predatory mice on the other soil founder Ashley left the room. I'm here sorry I couldn't unmute myself. Our modeling was really focused on seeing what was driving crop biomass production so while we saw that the road to charity were affecting and interacting with the column below the isotomedy and on a charity. We didn't see any other effects and that might have been due to the timing through applying based on our goals for that study but yeah no other effects. Thank you very much Ashley. And the next question again from the chat function it was from Jacob image he's asking there. This is for the end of Monday's. I hope that is the correct pronunciation of your name. Can you apply the technique that you were showing us there to all soil types and also in different countries. And also were you able to explain the high yields that way. We can use this approach has been used in other countries such as China, India, India, India, India, India, India, India, India, India, India, India, India, India, India, India, India. Great. Thank you. Well, we can use this approach has been used in other countries such as China, India, and Canada. Then they were able to successfully established reference level for soil enzymes in these countries. So it is possible but local key is research because the reference levels for soil enzymes or any other microbial indicator will change as a function of soil type and climate conditions. So local research is key. And this approach has been tested in China, India, and Canada. Regarding the low soil again matter soils being productive. The key is the best management practices here in Brazil we have seen the soils that sometimes are more productive than clay oxysols with let's say more than 6% of click on. So again, best management best management practices are the secret. And yes it is possible. Thank you very much. And the next question will ask Francesca, it came from Lina. The question there was how do you sort out the organisms to an EMI numbers. And also, can we consider the answer reports to be good indicators of soil health. The question there was, we can consider antropods to be good indicators of soil health, for example. But what about other soil qualities can antropods still be considered as good indicators I think it's a combination of the question from Lina Wells and Trisa Chapman. So please Francesca if you can have a one minute or so response to those. Okay, we think that biodiversity is always anonymous with good soil health. We use the index as a references to identify soil degradation. So, this is a index widely used in Italy to assess soil biodiversity source. Yes. It is a synonymous of good structure but good porosity to, for example. And for the second questions. We classified the anthropod with his adaptation to soil. For example, no wings, no eyes, depigmentation, all factors that indicate the eye EMI, eye index. And some of these index is more eye is more quality in the soil. Thank you very much for that. I think for our last presenter Lydia, perhaps we've been able to look at the chat. One question. What are the main traits studied in identification of these organisms. Sorry, I can. Okay. We, for now, we started just the identification of fungi is done in two different methods mainly morphologically so with with a microscope and in this way we look at the shape of spores the shape of several things. And it is a very time consuming identification and very hard. So now we are switching to molecular identification so we use just a PCR to identify a region that can let us know the species. In particular, now we, we are doing meta meta barcoding so we use, we are able to see with the whole DNA of a community to see all the fungi present in that community. Thank you very much. So I know there are many questions that have come up in the chat box. Please colleagues who are giving presentations take time to answer the questions particularly those ones addressed to you. It's important for colleagues who want to clarify further. So have those questions answered, answered. I have one hand still up. I think I will allow that should be a burning issue that has kept the hand up. Is it's madam or sir. It's very difficult for me. What is your comment, a quick one. Okay, it seems maybe the hand is, is up by accident. So at this time, I would like us to move to the next hour. Again, the rules that are the same. We have the four presentations back to back 10 minutes for each presenter, and then we ask, we have a Q&A session at the end colleagues who are presenting in this next session and kindly requesting you to keep your eyes on the chat box so that you see there are specific questions addressed to you that you may want to consider in case I have not asked it in the Q&A session. So right away, we are moving to miss Ika. Thank you. Thank you. She's presenting on drivers of short to medium term leader decomposition across biomes. Please go ahead. Hello everybody. Can you see my presentation. Yes. Yes. I just see that I move much further than I wanted. I am Zoll ecologist by training at the environmental agency Austria and I'm coordinating the global a little decomposition study T composition on which I would like to share with you results on drivers of short to medium term. Leta decomposition processes across biomes. Why does leta decomposition matter. Leta decomposition contributes a lot to soil formation and but also to the gas exchanges between the atmosphere and biosphere around 60 pentagram carbon is released annually from the leader and soil organic matter decomposition. But leta decomposition also contributes to the greenhouse gas production like and to all, which is about six to eight teragram nitrogen per year released. Roughly speaking, we can say if we have quite fast turnover, then we have probably a positive effect to the climate warming and if we have a moderate or slow decomposition than we would rather have a carbon sequestration. Today, I would like to show you the results from the global to regional levels collected to this decomposition initiative where I would like to show you the patterns and drivers at the global scale, but then use experimental approaches to go more into detail and to see what are the direct and indirect impacts in the forest ecosystems, but also what other drivers are how to disentangle drivers on such huge gradients environmental gradients in the grassland ecosystems. And briefly this global litter decomposition initiative we call it tea composition because we work with standardized later, namely commercially available tea, we use for this green tea that decompose fast and rubbish tea that decompose slowly. And what we do we basically read them tea back and buried under the ground and collected after certain time and measure the mass loss. The initiative has started in 2016 and so far we have 570 sites involved in the in the in the study and around 300 sites in aquatic ecosystems. Here I would like to share you the results from three month incubation period you see on the y axis the remaining mass and on the x axis you see the biomes climatic zones, organized from from cold to warm. In the green you have the composition of the green tea and in red of Roy Bush team. Basically what you can see that average remaining mass of Roy Bush keys is 72% and of green tea 40% across all biomes which means green tea decompose across all biomes similar way. So what which parameter or mostly contributes to the explanation of this pattern that we have seen and we see that the little type explains about 65%. And that green tea decompose fast is also probably due to very high amount of soluble compounds, especially after three months. And that's because it's faster faster decomposition. But when you look at the climate it's quite lower amount of explanatory power. You, you should bear in mind which I didn't mention at the beginning is that we started a very harmonized approach, meaning that started in southern and out in Hermes at the same time of the year. In the case in summer, and the whole three months incubation was data were obtained during the summer which means we didn't have any extremes that could maybe lower or dump at the decomposition. Therefore the climate effect was rather small. But then we look at the nitrogen deposition at this early stage. This was also quite low. Jump over to the one experimental setup where we look at the litter decomposition at the regional scale across the Europe. Here, we tried to see how climate change air pollution, especially nitrogen deposition in different soil with different land use legacy would affect the litter decomposition again using the standardized litter. So here I wish tea and green team. For this, we have run a structural equation model. You see again here the data for three months, and it's organized according different soil types. We have you have your oligotrophic method traffic and you traffic soils. It tends that you have these stressors or drivers, and then to the right, the different type of these. What is common for all the three type of soils is that we have direct and positive impact of temperature and light on plant plant cover, but plant cover then again has rather negative impact on the decomposition of green tea, which although we have at the beginning positive effect of climate, then this effect is turned around to them to the plant cover. We also see that the different type of soils, the effect is a direct and indirect effects are strongly differently strongly expressed and I don't have time to go in detail of each arrows, but this is very interesting to see very clearly that different type of soil matter. Yeah, as I said, positive direct effect offset by indirect effect to the industry plant cover and that different soil conditions influence the litter decomposition is basically the main message. And then we had another method course of study study also through the whole Europe, where we tried to disentangle what is the effect of climate soil plant cover on the, but also microbial community through the soil on the litter decomposition. And these methods of cosmos we call it phytometer meet from local soil and standard soil and they have also standard plant composition is a widespread grass species that were planted on both standard soil and on the on the local soil and bunch of parameters were measured but I would like to present you only the composition of the team. I know that's a quite overwhelming table but just to guide you through. We have here the composition data after 12 months are here are the different drivers in the beginning climatic variables, then we have more drivers related to the microbial activities and then principal component of bacteria and principal component for fun guys. The first two green ones relates to the composition of green tea wants in local soil and in darker color and to the standard soil, and the same here for that rubbish team. Basically, what it says and which model best explains the decomposition on different type of tease is when we involve the contributor contribution on microorganisms. So I think in the previous to a study we have seen how different type of soils affect much the decomposition but here when you go one level deeper into the organism then you see that these models are quite strong and then if you look up to the climatic variables to sum it up. In this case we could see that at the early stage, the composition, little quality was the most driving factor, but the climate was moderate, probably also due to incubation during the summer times, but here I have to stress is just one view of this global study because the global study runs over several years and we have, we will have a long term data. In the original scale for the forest ecosystems, we could see that direct effect from the climate could be reversed to the plant cover, which has exerted rather negative influence on the decomposition in the forest ecosystems. And if we look at the original scale in grassland ecosystems, you could also see that microbial composition was much stronger explanatory variable on the decomposition of both little types, especially in the soil. Here we are waiting for more in-depth analysis that we can understand much better relationship, what is the difference in standard soils comparable to the local soil. What are the perspectives I think I could shortly introduce this idea of using standard litter and value of getting this harmonized data to really be able to make intersite comparisons, but also comparisons across different networks. I also mentioned that we have around 570 sites already collaborating this network, but still we have underrepresented areas, which is quite pity because the methodology is so suitable, especially for the areas where we don't need a lot of resources. And we always have not so much data, let's say Russia in southern America and Africa. So we will be happy if the community would like to join and collect the data on the decomposition in this area, which is also find that since the methodology is very simple. It can be also used to educate kids in the school what are the functions of the soils, but also you would collect the data in this initiative to teach the graduate student to work with the global data and also learn how to tackle issue on the global challenges. So at the end, this is the website link, please have a look. We have also protocols in different languages and contact myself, if you would like to contribute. Thanks a lot. Thank you very much for that interesting presentation, Ika, looking at drivers of leader decomposition. And I think you mentioned that soil type as well as little type where things that are among drivers of leader composition. Colleagues if you have questions for her please type them in the chat function. Now we'll soon be moving to our next presenter I can see it's ready there, almost sharing the screen already. Yeah, and the theme of the presentation is leader decomposition and organic matter turnover by so far now in a sustainably managed only group Mr. Andriano sofa from Italy please. It's your time. Yeah. And I hope that you can hear me and see me. My presentation is focused on leader decomposition due to the activity of soy fauna in an ecosystem, a Mediterranean ecosystem is an olive grow the manager in a sustainable way. And this ecosystem this grow is located in Ferrandina is in the south of Italy. It's a beautiful grow in a hilly area. It's a mature olive orchard with the plants that have almost 100 years old, and it was split in two parts. It's sustainable and the other half conventional. So we have followed this. This field since 2000. So it's now 21 years of differential management. And in the sustainable plot we adopted a no tillage, guided fertilization and drip irrigation. So we treated municipal wastewater light winter pruning and the pruning receive material was cut and left on the ground as much. So a lot of carbon inputs in this in this plot. The other plot that was totally different it was managed according to the local management practices. So it included the soil tillage, minor fertilization, empirical irrigation with a lot of water, heavy pruning and pruning residues were burned and removed from from the field. So now we have compared these two systems and the games of the study where a to focusing on the importance of natural potential of soils, especially from a biological point of view in the Mediterranean is that we analyzed that is very low level of soil organic matter and soul fauna can contribute to ameliorate the soils, especially in source soil for nice. So you will see later is improved by sustainable management. So the soil fauna, especially of mocha fauna. It's important, not only for food production for agricultural production but also for a wide range of ecosystem services. We also followed the physical chemical parameters carbon and natural dynamics. Later and soil organic matter the composition, and we compared this these parameters between the two systems. We hypothesized that a better management, a friendly management are sustainable management eco friendly management can enhance can improve the abundance of macro fauna and this macro fauna has very deep efforts significant effects on soil fertility. And we, at the beginning we studied the, of course, the most important parameters for chemical fertility is so sort of any carbon and sort of soil total nitrogen, and in the sustainable systems system. So the levels of sort of any carbon and sort of total nitrogen were higher compared to the conventional these are the data after 18 years of sustainable management, you can see the difference in the presence of litter, only the sustainable plot where there are cover crops, while the conventional plot was in the conventional plot the soil was totally completely better. So, in 18 years we observed a very significant increase of soil organic carbon. And usually this is normal because when a soil is cultivated we lost more than 50% of organic carbon, and it is possible to reverse this trend, applying sustainable practices. But what is the contribution of soil fauna to this process for understanding for trying to understand this, we as counted heartworms. So in different points of the orchard, the total weight of heartworms and the main weight of earthworms were calculated or measured. So you can see the difference here between the two systems, and also the total weight and mean weight of other mocha fauna. This was measured in 25 centimeters per 25 per 25 blocks of soil. And we measured also bioturbation and using the mesh bags with and without holes. These holes allowed the microphone, the entering of microphone in the mesh bags. These mesh bags were filled with a mixture of artificial soil. And this was, why? Because it was possible to observe the tunnels and the bioturbation of micro fauna, especially of earthworms, in the artificial soil that it is completely white. And it was possible to see the biogenic structures of the earthworms, so the entity of bioturbation. So we measured this, you can see here the biogenic structures in the artificial, within the artificial soil, inside the artificial soil. And these were the soil cores recovered after one year. You can see here some of them. And the dry weight of biogenic structures that are related to bioturbations to microphone activity. We are particularly interested in this, in this kind of mesh bags with holes. So we measure the activity of earthworms, because the holes were about approximately one centimeter of diameter. At the same time, we also calculated soil organic matter decomposition using a liter, a characterized liter from the same field, same oil growth. And we measured the composition compost, constant, that was higher in the sustainable plot compared to the conventional one. This either after 90 days and after one year of the composition, you can see here some of the liter bags that we used. Why soil furnaces is so important because soil macro porosity that is indicator of physical fertility is higher in the sustainable plot and this macro porosity is due to agricultural techniques but also to macro fauna activity. You can see here some thin sections of soil at 10 centimeters, 10, 20 centimeters deep. And the white parts are the macropos compared to the compacted and conventional soil where macro fauna was less abundant. So this parameter is very important because on this parameter, this parameter also affects soil storage, water storage into the soil. So you can see the difference here of water storage, soil water content in the two systems per hectare and the cover crops also allowed less soil losses, so less erosion. In conclusion, soil chemical and physical quality are important, but soil biological activity, especially the activity due to soil fauna, but also to microorganisms, to bacteria, to fungi, is very, very important. Because soil fauna plant interactions are very important because they affect soil crop reduction, but also a wide range of ecosystem services. The role of soil fauna should be seriously taken into account in land management strategies, especially in very vulnerable soils like Mediterranean soils, arid soils. And so soil fauna is a key role in soil quality and fertility. This role is extremely important because soil fauna is affected by chemical fertility and physical soil fertility, but also affect soil chemical physical fertility. And the benefits of sustainable practices are various. They can be commercial, ecological, institutional. There are a lot of benefits for the farmers. You can see here the cumulative yield of olives in the first year of the experiment, considered higher olive yield in the sustainable plot. So I thank you for attention. This is our research group and this research was inspired and within a queso cost action. And I also invite you to the second international electronic conference of plant science where I will be the chair. So if someone is interested in this conference can contact me. And really thank you for the attention. Thank you. Thank you very much for that interesting presentation. I hope you can hear me. I'm having a challenge. Magdalene, can you hear me? I can hear you, yes. Yeah, so thank you very much. So the presentation was very interesting. They are showing the key role that so far in the ecosystem services and sustainable land management. It was interesting to see how areas where sustainable land management are being practiced have higher carbon nitrogen and biotabation compared to where there was no sustainable land management in the conventional system. So please have a look in the chat to address. I think I saw one question. At this time, we would like to move to our next presenter. Our next presenter is forgive me colleagues if I don't put your title doctor prof and all others. I, it's Mr Frank Ashwood from the UK and he's giving us a station and developing a systematic sampling method for earthworms in and around deadwood. So please, this is your time. Go ahead. Great. Thanks. Can you hear me okay. Yes. Yeah, thanks everybody for who tuned in for this. I know you've got lots of choice this afternoon. And I just got about 10 minutes. I'll try and wrap it up quicker if I can to make time. But yeah, I work for Forest Research in the UK. My name is Frank Ashwood. And I just want to talk about my attempt to develop a systematic method to look at earthworms in deadwood. So why are we interested in deadwood? Well, hopefully everyone appreciates how important it is for soil biodiversity in forest systems. It's both food and shelter for a whole range of invertebrates, including earthworms. There's a whole load of earthworm species that might not actually live in soil but might actually live in deadwood and other habitats above ground. The problem is we don't actually know a great deal about them because most of the traditional approaches we take to looking for earthworms involve looking in the soil. There's as yet no quantitative methods for systematically looking for earthworms in non soil habitats. And as a result, we might be missing out on information about their distribution of these these species that don't live in soil. We might be assigning wrong kind of conservation statuses to those and we might not really be getting a clear idea of the ecological value, the true ecological value of deadwood. So this was a pilot study that I developed a couple of years ago now that was trying to overcome that lack of methodology. And the aim was quite simple. It was just to try and develop and trial a systematic method for looking at looking for earthworms in deadwood, but also then compare that against traditional approaches that would just look in the soil. The location for this study was in Southeast England in the UK in Alice Holt Forest, which is part of the environmental change networks long term monitoring sites, and identify 12 stands of oak so quirkus rober. And in each of those stands, I marked out a 10 by 10 meter plot. And then within that surveyed all of the deadwood for volume in that in the area, and then selected five pieces that I was going to systematically investigate, and then dig five soil pits, traditional soil sampling pits for earthworms. And then beneath the five bits of dead, deadwood that I was going to look at in each plot. I also dug a soil pit to see what earthworms were living in there. All of the deadwood that I surveyed, I'll talk about bit more in a moment was in a decomposition class three and four now. I don't expect many people to know about this but there are ways that you can associate and classify decaying wood based on how degraded it is. And from the literature and other pilot studies. It really seems that earthworms don't move into decaying wood until it's medium to late in the decay process once all the other invertebrates have got in there and made the bark loose and decompose the words so I focused on on those types of decaying wood. I've got references at the end that you can go and look this up. So the methodology was pretty simple. As you can see in the plot in the top right there the schematic and first off those five x is those are where we generally dug soil pits so we excavated the soil, like in the previous talk 25 centimeters by 25 centimeters and hand sorted that for earthworms. We then took measurements on soil moisture and soil temperature because those are very important environmental parameters for earthworms. We then, yeah, we collected the earthworms from there and preserved those. We then found five pieces of deadwood that we were interested in studying, measured the temperature beneath the bark of those with the same probe, and also collected the organic material that accumulated beneath the loose bark because that's kind of like the soil environment that the earthworms live in in the deadwood. We also measured the deadwood for surface area and volume. And we moved it aside and dug a pit beneath there took the same soil measurements. And then in the deadwood itself we dismantled it, we looked in the moss any loose bark, and where possible we looked inside the decaying word as well to try and collect the earthworms, which we preserved and then took back to the lab for identification to species level and also to determine the biomass of the earthworms that were within the decaying word. So coming on to results. This is a table just of the abundance the average abundance of the earthworms in those three habitats, and I'll just quickly run through a few points. Just to say, firstly, the soil habitat itself just the open soil was significantly greater in earthworm abundance and biomass as we might expect. And it had a large number of species found there. But we found about six species in the soil that we didn't find in deadwood. Conversely though we did find an earthworm species in the deadwood surveys that we didn't get in the soil. So this was this species here isenia fettida. It's a composting earthworm it's called the tiger worm here in the UK. People in Europe and North America might be familiar with this one stripy it lives in your compost bins. And also we, there's another species by mastos isenia which is another surface living earthworm that's associated with trees, we found significant greater numbers of that in the deadwood as well. Here, the deadwood has been associated, the deadwood earthworms have been worked out for the surface area of the deadwood so that it could be compared to the surface area of the soil data. Teasing apart the, the earthworm community data a little bit further just to look at the life cycle or life stages of the earthworms that are happening in these habitats. It was really interesting to see that actually, the deadwood had a much greater a significantly greater proportion of juvenile earthworms in it, compared to the surrounding soil habitats and correspondingly a reduced proportion of adults. And what that suggests is that the deadwood was providing a refuge and a habitat, particularly for juvenile earthworms, before they then move out into the soil habitat as adults. So the main findings, the main results. One earthworm species was found in the deadwood only, and there were six species found in the soil only, as I mentioned in the first table. On average, the deadwood added around 20% of the total earthworm abundance data for that 10 meter squared forest plot, and about 10% of the overall biomass, biomass data so quite a good contribution from the deadwood that we surveyed to our picture of what's in the forest. As I said in the last slide the deadwood also had significantly greater percentage of juvenile earthworms, and that was associated with the specific environmental conditions that we found in the deadwood. So beneath the bark in the organic layer, the organic material that accumulated there where we found most the earthworms you can, you can see it in that middle image at the bottom there that dark stuff. It was around 78% moisture content which is really high compared to significantly higher than the 24% moisture content in the surrounding soils. It was also one degree C warmer on average, which is important when considered that we were looking at this in in autumn so it was quite cold. And that helps to explain why those juvenile earthworms were there in such greater abundance because juvenile earthworms are particularly vulnerable to moisture and temperature. And it looks like the deadwood was providing a much more comfortable environment for them. Interestingly, we found that the soil beneath deadwood was actually less habitable than the surrounding soil for earthworms there was a much reduced earthworm populations there. And that needs more investigation. But this was one of the first studies, I think, where people have actually where we have associated earthworm density and deadwood per meter squared of the surface area rather than the volume of the deadwood which is what most people do. And considering that most of the earthworms were living on the thin just beneath the thin layer of bark. It makes more sense to do it by surface area, and also has the benefit that earthworm, normal soil earthworm calculations are provided per area of soil so it makes them directly comparable. So I urge anyone else that does this kind of thing to consider that approach. Just to conclude and then I've got a couple of take home points. And we did find that including deadwoods in our woodland surveys improved our idea of our estimates of the earthworm populations flows woodlands, and also gave us an additional species for our species richness calculations. Oh, hi. Someone's taken over screen sharing. Please not yet. I'll get back. Thanks. Yeah, so was I yes so the deadwood surveys though because we found a lot more earthworms in the soil than in the deadwood and more species in the soil than we did in the deadwood. I'm not suggesting that we should go out and serve a deadwood only. But it's more to be considered as a holistic addition to traditional soil sampling surveying for earthworms in forest systems. We're going to finish with a couple of next steps for anyone who might like to collaborate so there is a little bit more. This was done two years ago and I haven't been able to put any time into it since. And there are some other experiments going on there in the Netherlands, bargaining and they're doing some really interesting stuff. If anyone from there is here today wants to talk that would be great. Let's back up again if I can. Maybe we can roll out into alternative micro habitats beyond deadwood so looking at stones and rock holes and other interesting places the earthworms may live. The technique could also be applied to other invertebrates so we can look at springtails mikes and other important soil invertebrates. And also just to get an idea of what earthworm species really are utilizing deadwood, because we can only identify adult earthworms. And one thing that could be done is take cocoons from deadwood and either incubate those up to adult stage or also just DNA sequence them and see what earthworm species are utilizing those habitats. So thank you very much please feel free to get in touch. I'm far too active on Twitter so you can find me on there. And if you want to look at the papers. The code on the left there is the original research publication which is open access in forest ecosystems. And then this was represented for younger audiences in the in the really good frontiers for young minds saw by diversity edition recently so you can find that following the link there. Thanks very much. I'm impressed that you had a paper for young minds. As you found juvenile. Thank you very much it was an interesting presentation there we noted from your work that actually there was one particular species of earthworm that was exclusively deadwood compared to what was in this web. So I think there is one question for you in the chat please have a look at it and try to answer it before we have a live interaction. Hello colleagues we have come to the last presentation please hang in there so that we listen to this last presenter on soil biodiversity and physical hydraulic function. How earthworm and launch route interaction contribute to ecosystem services Mr Jamal now it's your time please go ahead. Hi everybody, you hear me. Yes, we hear your screen. This is Jamal Hala from Iraq of Morocco. And today I'm going to talk about sorry, just to move this. I'm going to talk about how earthworms and rent routes interaction contribute to ecosystem services into soil water regulation. As most of you know, earthworms process the soil, and as they are eating dirt they are making boroughs that makes what that brings water deep into the ground to the aquifer or to the drainage system at this water flow. And this is actually on earthworm species. There are some species, any six for example here, they have more impact on vertical flow than lateral flow, other species like on DJX species, it's like a balance between vertical and lateral flow for the EPGX they act more on the soil surface the upper 10 centimeter surface and they have more effect on lateral flow than vertical flow. And this, this water is brought to the soil and they help to buffer extreme events, timing and magnitude at field scale and at regional scale. And the problem is that most laboratory works that have that have been done until now the the main experiments in conditions where the the earthworm boroughs are connected to a drainage system. So this is not always the case because earthworm boroughs they have ends. So the water within the boroughs is more a matrix flow than conditions flow. What do I mean by positive conditions flow? If we consider here this earthworm borough as a tube, as a tube with both sides open, we can see in first case here that when in conditions when boroughs are not connected to a drainage system, the flow within the vertical flow within the borough is more depends more on core diameter. In second case here, when the borough has an end, the flow within soil is more matrix flow, it depends on the matrix characteristics on the length of the borough, the diameter and on other characteristics like soil organic matter and meetings other. So in this little crucial detail is not taken into consideration in many studies. So here this is what we did in our experiment. Also earthworms they live in covered area where they interact with the plant roots and plant roots they have also impact on soil water flow as earthworms do but not at the same extent. But they make by of course that really that control water flow within the soil. So here what we did is that we tried to see this interaction between earthworms and plant roots on soil water flow and soil physical characteristics. We tried this on different species of earthworms. So we made lab experiments with two earthworms species interstates and chlorotica. This is a vertical borough in earthworms and this is a lateral borough in earthworms and another field experiment. So this talk is see is separated into parts. The first part I'm going to talk about our results on lab experiments and secret part about our field experiment. For the lab experiment, we did the first experiment was on earthworms which was combined to winter wheat. And so the experimental design was of 48 columns with soil textures and without earthworms and without plants. We did same experiment for interstates with vertical borough in behavior and for chlorotica with lateral borough in behavior. And the columns were put under red lights. We measured for radiation. We irrigate them. We irrigate the plants and we put the horse manure to feed the earthworms at 15 degree Celsius. After 16 weeks, we measured unsaturated hydro-conductivity, saturated hydro-conductivity, soil water release cures, water stable aggregates, water holding capacity and plant shoot biomass. So what did we find? Here chart shows the unsaturated hydro-conductivity and saturated hydro-conductivity in the experiment where vertical earthworms were tested. The y-axis here show the main hydro-conductivity and x-axis shows the different tensions applied to measure the saturated hydro-conductivity. So each tension here is corresponding to a flow within a particular pore size. We will only focus here on saturated hydro-conductivity when all the pores of soil are filled with water. What we see here is that actually water flow in the presence of interstates, it was more controlled by plant roots. However, the interaction between plant roots and earthworms has the most impact on water flow. This was only significant in sandy-loan soil. For the eclortica with lateral burrowing behavior, we found that there is that earthworm that actually controlled water flow within soil. We can see that all the columns where only earthworms were added or are in interaction with the plant roots, they have very high water flow. The value of hydro-conductivity is far more greater than the one for interstates. This chart here shows the pore size contribution to water flow. We'll focus here on sandy soil and only on pore wider than three millimeters. So what we can see for eclortica that at the end of the experiment, the water flow within pore wider than three millimeters was the same for when earthworms interact with wheat and when only earthworms were added to the columns. For interstates, the water flow was more controlled by wheat, either with interaction with earthworm or without. Here, the chart here shows the water holding capacity for interstates. We can see that there is an impact of wheat, the presence of wheat in the columns. But the impact of the interaction is not really significant except for the soil. For eclortica, we can see that there is an interaction between earthworms and wheat roots has a very big impact on water holding capacity within all the soils. For water stable aggregates, again, for interstates, no significant differences, but for eclortica, we can see that the interaction has a very significant effect on water stable aggregates. So this is the second experiment, the field experiment. So the aim of this study was to determine the effect of earthworms on soil recovery when arable soil is converted to lay. The aim actually was to clarify the extent of which the action of earthworms as distinct from other practice management give rise to improve the soil characteristic. As you can see here, the experiment was made on monoliths in strip place here. So this was done, the monoliths were extracted from four arable soils containing strips here. I can explain after why these strips were made after the discussion. So the soil was taken here, we made many measurements and the soil that feels has a historical arable practice. So what we have done here is that we took seven monoliths, we define them at minus 20 degrees for three weeks, then we grow clover and wheat on them, we put fences, and then we separate them in four fields here. There are three monoliths which were frozen but did not contain any earthworms, three monoliths where earthworms were added and one control. And yes, this is the earthworm diversity which was added to the monoliths with earthworm addition. So we have made two inoculation of earthworms during the year. And the monoliths were put at the end of lay strips. And during the experiment we measured seasonal hydro conductivity and plant shoot biomass. And at the end of the experiment, we actually measure water release cures, water holding capacity, bulk density and other characteristics. So here is this chart shows the earthworms diversity found in the monoliths at the end of the experiment. So what we see here is that in monoliths with earthworms addition, we found actually the same numbers of earthworms as we put in the first at the start of the experiment. The species, the diversity was different. We see that there are many on the GX earthworms than other species compared to start of the experiment. For monoliths, we're only where that was defunited without earthworm addition, we found that there are some earthworms in here. Most of them are EPGX, maybe they have colonized the monoliths even if we have put the defense over them. This chart here shows the hydro conductivity during seasonal change in hydro conductivity during the experiment. I will move to the end of the experiment that we can see that there is a very significant difference in hydro conductivity between start of the experiment and the end of the experiment. Here also there is an increase in hydro conductivity, but it was not significant. Chart shows the water release curve. We can see with the addition of earthworms, the curve shifted to the right and the water at saturation is significantly higher than the other treatments at field capacity also. The water available to plants was also significantly higher than other treatments. For water holding capacity, it increased by 9% for work density. It was not significant between treatments, but for organic matter it increased by 9%, water stable aggregates by 15% and total nitrogen content by 3.5%. Maybe you can conclude. For the mean clover, we can see that at the end of the experiment, the clover biomass has increased by 58%. At the end, we can see that the combined effect of earthworms and wind through it showed the greatest effect on soil properties and also that lateral burrowing earthworms like clotica has more impact than vertical burrowing. Maybe because we have changed the setup of our experimental design. Also, for the field experiment, our results suggest that earthworms play a direct and significant role on the improvement of soil quality when arable was converted today and this is why we should boost earthworm populations in our practices to ensure successful, sustainable and reclamation on soil quality improvement. Thank you very much for your attention and these are the published paper during this work. Thank you. If you want, just keep in touch and I will give you all these papers. Thank you very much. That was an interesting presentation there showing the effect of earthworms on soil as well as soil monster characteristics. Thank you very much. It's very tight to keep time on online presentations, but we try. So I'll ask, maybe not all questions, but each presenter perhaps may have a minute or so to just answer or clarify. I know you've already handled most of the questions in the chat. So I'll ask them around just for the benefit of the other colleagues who didn't have a look in the chat. There was one question from Mr Dewey. Forgive me for the names again. The question was the address to Mr Ashford and the question there was how did you measure earthworm population density on dead wood per square meter. So dead wood is not evenly spread the areas. Yeah, it's a good question. Sometimes we're deadwood is quite hard to calculate the surface area because it's irregularly shaped so we did our best to treat it a bit like a cylinder. The calculations were based on the surface area of the deadwood itself rather than the soil that it was on. So if you take the length and the diameter of the deadwood and assume a cylindrical shape or a cone shape, then you can work out the surface area. The earthworms were living under the bark that was on the surface of the deadwood. Ecologically it makes sense to treat it that way as well. And it was quite useful because we calculate earthworm density in soil in the same way. So you can actually make them directly comparable, which is useful. Thank you very much for that answer. Thank you for the questions we didn't fall. I think I saw it answered also in the chat. Then there was one question that was addressed to Adriano, it was from Rasmien Javad. The question there was what was the role of kaolin in the mesh bags. Thank you for this question and the kaolin and the addition to sand formed a kind of artificial soil. This artificial soil has the same texture, approximately the same texture of the soil, the normal soil, but it is white. When we recovered this soil, these cylinders, we observed the activity, the bioturbation activity of the earthworms inside this artificial soil. It was very clear visible because it was brown on a white background. At the same time we managed to recover the biogenic structures secreted by the earthworms. So it is a way to observe clearly the bioturbation in a white background. So I think that was clear and I saw it also taken care of and we have another, maybe last question is, it was addressed to Ika, who was talking about the composition. I think it was the work was done in Europe. The question there was from Giotto, I think, how viable is it to apply the work on later decomposition and other latitudes. As I mentioned, we have run the study across 570 sites worldwide and also in different climatic zones, even in the high Arctic and the mountain region. So basically method you can apply everywhere, even in the aquatic ecosystems. Great. One last question has come for Jamal, being a last presenter, I'm sure people didn't get a chance to digest your presentation, but there's one last question, did you investigate the behavior of earthworms in composted soils? Actually, we did investigate the effect of earthworms, not the behavior, it's not my work to do the behavior, but we have seen some behavioral actions that we, as I said that some of us were actually, there is no, some of us were defonated. And after that, we saw that, yeah, we found the EPGX earthworms in them, maybe they were cocoons inside that were not affected by high frozen conditions in the freezer. But, and also, we didn't actually, we just work on arable soils, not on composted soil. I don't know if this answers his question. Thank you very much. So colleagues, it has been a very interesting session. We've learned quite a lot interesting work going on. So quality indices, monitoring the drivers of litter decomposition, how so found that can contribute to sustainable soil management. Then there is the biodiversity of the micro fungi, where we learned that more research actually is needed, and also the, the, the role of fauna in ecosystem functions and there was one interesting question which was raised, is there a database for soil organisms and biodiversity, does one exist already. So there's much work that has gone on, but also we learned from some of the papers that were based on review articles that particularly the one on micro fungi that work actually has gone on, for example, to map the biodiversity of the micro organisms. So there's a lot of work that still needs to be done. So it has been an interesting session. I hope we've made some contacts, some networking, I think in the chat links and papers were shared so hopefully we'll be able to link together. Before I close, maybe Isabella you'd like to say something, Isabella is one of the main organizers of the symposium. Before I just bring the session to a close, would you like to say something? Isabella, are you there? Okay, I'm seeing that Isabella is not there yet. So I would ask Magdalene, is there anything that you have from the organizers? Thank you very much colleagues for joining. Please be ready to join tomorrow also. It has been an interesting session. So we would like to close today's parallel session and thank you for keeping the time. It was not easy, but we made it. Thank you colleagues. Enjoy your morning, afternoon or evening depending on where you are. Bye bye. Thanks Sidiya.