Good day. I'm Max Hegblom, Editor-in-Chief of FEMS Microbiology Ecology, and it is my pleasure to welcome you to this webinar in Ecology of Soil Microorganisms. Our webinar series enabled us to highlight different topics of microbial ecology to a broad audience. Those of you who have tuned into our previous webinars knows that FEMS, the Federation of European Microbiological Societies, invests in science. We use the income from our journals to fund charitable activities and support our community. It is important to note that learned societies and their journals provide grants to scientists, organize and support conferences and summer schools, and sponsor a range of events such as this webinar series, which provides a forum for the presentation and discussion of key research enabling the flow of ideas to a worldwide audience. As an author, when you publish in FEMS journals and when as a reader you use these publications, you directly support the various activities in which FEMS invests back in science. As Editor-in-Chief, one of my rewarding tasks is to select topics and speakers for these webinars from our collection of papers. Note also that if you missed some of our earlier webinars, they are available via the FEMS OUP websites. Indeed, before we start, I wish to thank the staff of FEMS and Oxford University Press for all their work behind the scenes in making these webinars happen. Also a big change for the journal is that from January 2024, the journal will be fully open access. This means that all the archives will also be available free to read regardless of your institutional subscriptions. In addition to ensure that article processing charges do not become a barrier for authors, there are a number of discounts and waivers available, so please check the website for more detail on this. Today, our three speakers will take us on a captivating journey into the ecology of soil microorganisms and learn how soil bacteria and fungi respond to stress conditions, habitat restoration, and change in climates. Our three expert speakers will unveil some of the adaptations and roles of microorganisms in regulating soil ecosystems. First, Emily Sully from the Department of Environmental Systems Science at Eteha, Zurich, and now at the Helmholtz Center for Environmental Research in Leipzig will discuss the impact of water limitation on soil microbial communities involved in nutrient cycle. Then Nicholas Barber from the Department of Biology at San Diego State University will discuss the restoration age and reintroduced bison and how they may shape soil bacterial communities in restored tall grass prairies. And finally Anna Escalanta from Institute of Ecology in Universidad Nacional Autonomia de Mexico will present on the functional significance of microbial diversity in arid soils. After the talks, we will open the session for your questions and for discussion. So please submit your questions and comments via the Q&A link and we will get back to these at the end of the session. Also to note before we get started that if you're interested in learning more about the ecology of soil microorganisms, we have a thematic issue on this topic coming up in early 2024. So again, take a look at the journal website. But now it's my pleasure to introduce Emily Sully, our first speaker and she'll get us into nutrient cycling in soils. So Emily, welcome. Hello everybody. I will share my screen. Thank you very much, Max, for the nice introduction and also for inviting us to present our work in the FEMS Microbiology webinar today. I will talk about the impact of water limitation on soil bacterial and fungal communities involved in nutrient cycling in Scottspine mesocosms. And I would first of all like to thank also my co-authors, in particular Astrid Jaeger, who did the assessment of the microbiome for this study. So you might be wondering why we're interested in understanding the impact of water limitation on the microbiome in the soils associated specifically with Scottspine trees. The reason for this is that climate change is predicted to continuously increase the frequency and severity of drought periods, mainly due to the continuing increases in temperatures. And this is unfortunately leading to several episodes of tree mortality, which have been recorded at many sites globally. Also in Central European Alps, several in several regions, episodes of tree mortality have been recorded, where the dominant species is Scottspine, Pinocilvestris. And also reductions in tree growth and vitality have been observed in the southwest of Switzerland that you can see this area marked in red in the map. Here also from the figures, you can see that the forest is not doing well. Scottspine trees have actually been suffering from drought. And you can see from the pictures that the trees in orange are actually dying. This is not in autumn, so they're not discolouring because of autumn and seasonality, but really because they're suffering from drought and and losing vitality. The valet, the canton valet is a very bright area of Switzerland, and also in general of the European Alps, mainly because the mountains are blocking the air masses. And so this results in lower precipitation, in comparison to other areas. In this canton valet, the precipitation has not really been changing over time. However, the temperatures have been increasing, and so mainly the loss of water through evaporation from the salt has caused tree mortality episodes during the last decades. And the situation, unfortunately, seems not to be improving until the end of the next next century. Predictions of climate change are actually indicating that the temperatures will continue to increase without some efforts, mitigation efforts, by four to seven degrees. And possibly also during summer, the precipitation rates will be reduced by 40%. And this is, of course, very problematic for forest functioning, because trees also sustain ecosystem services. For instance, especially in mountainous areas, they protect against rockfall, avalanches, and soil erosion. Also, not only mature trees are dying, but also very young trees which are developing in the forest due to drought. And therefore, it is important to understand how young trees are also resistant to water limitation, to understand how forests can actually recover after extreme events of drought. Drought and water limitation doesn't only affect trees, but it also can influence the soil microbiome. In forest, organisms such as fungi, bacteria, archaea, protists actually play key functions such as decomposition, nutrient cycling, and symbiosis with trees. And an alteration of the soil microbiome due to drought might also lead to then influences, negative influences on soil health and the nutrient cycling. Water limitation does not only affect the soil microbiome directly, but it can also alter the soil microbiome through changes in physical chemical properties in soils and through alter plant parameters. For instance, due to water limitation, plants can undergo a series of physiological changes. For instance, they probably altered the amount of inputs and the chemistry of the inputs to the soil, which are very important energy source for some microbial communities, and also changes in their growth. For instance, an alteration in the root growth, usually the growth of trees is reduced due to water limitation, can also affect the amount of exudates released to the soil, which can in turn induce shifts in both in the functioning of the microbiome, but also in the community composition. So the main aim of our study was to assess the response of soil prokaryotes and fungal communities to different levels of experimental water limitation in Scottspine mesocosms. And we were also interested in understanding how changes in soil physical chemical properties and plant growth would affect the soil microbiome. We hypothesized that water limitation and alter resource abilities would induce a community succession towards an enhanced abundance of sapiotrophic tax involved in the decomposition, degradation of organic matter derived from plants, that organic matter from plants. At the same time, we expected that water limitation would decrease in biotic tax and rather increase oligotrophic bacteria and desiccation tolerant tax under water limitation. Finally, we also expected the composition of the soil fungal community to be more resistant to water limitation as compared to prokaryotic communities, mainly due to the ability of fungal communities to produce hyphal network, which allow fungal to basically scavenge larger areas of the soil for nutrients and water, of course. So to basically tackle these hypotheses, we set up a mesocosmic experiment in the greenhouse of VTH Zurich in Switzerland. We set up 18 mesocosms. You can see in quite large pots, as you can see from the image here, and the soils were filled with natural forest soil from the forest that you have seen before in one of my slides affected by drought during the last decades. And also the tree seedlings that we or saplings that we planted here had an age of three years at the time of the start of the experiment. And the experiment was set up in September 2019, and then we basically watered, we irrigated the mesocosms to field capacity for four months in order for the mesocosms to basically acclimate the new conditions in the greenhouse. And after this period, we then started the irrigation treatments. We had three treatments, a controlled treatment, which was for which the mesocosms were maintained at field capacity, and then we had two water limitation treatments, an intermediate and the severe water limitation treatment, for which the amount of water was reduced by 40 and 75 per cent. After the start of the treatments, we then sampled on a seasonal basis, and we analysed all sorts of parameters for the soils and for the plants, for instance pH, nutrients in the soil, but also growth of the plants and gas exchange. And we also analysed and assessed the soil microbiome using DNA sequencing and the QPCR methods for the quantification of fungal and bacterial ribosomal markers. And I would like to mention, again, that the analysis of the microbiome was done by Astrid Jäger, who was the PhD involved with the project, and unfortunately she could not attend the seminar today, and this is why I am presenting. As you can see from this graph, we did a very good job with the treatment, so that at the beginning of the experiment, all of the treatments had basically the same gravimetric water content in the soil. And after the start of the irrigation treatments, the amount of water in the soil started to decrease for the water limitation treatments, as compared to the control, and we always had the lowest amount of water in the severe water limitation treatment. You can also see in the graph that there was an seasonal variation over time, and this is because there is a confounding effect of temperature on soil moisture when the temperatures are higher in summer. We regulated the temperatures manually in the greenhouse to basically follow a seasonal pattern. And during warmer temperatures in summer, then there's higher evaporation from the soil and also higher evapotranspiration by the trees, and this is why the amount of water in the soil also decreases. Nevertheless, the amount of water in the control treatment was higher as compared to the water limiting treatment. You can also see that it was a bit more variable. One year of water limitation, very interestingly, did not alter the relative abundance of either the prokaryotic unfungal communities in the soils over the control course of the experiment. Nevertheless, we did see a peak of abundance for both communities in summer. And this could be likely because of the temperatures might stimulate the growth of organisms which favor high temperatures, which grow better under high temperatures. But it could also be related to the fact that plants continue to sustain their growth during the growing season. And so the higher input of carbon by the plant, which continue to sustain growth, might have also acted as a good energy source for the microbial communities, especially during summer. Nevertheless, water limitation had a very strong impact on the community composition in the soils of the mesocosms. Here you can see the cap analysis for the prokaryotic community. And you can see that basically the prokaryotic community strongly diverged among treatments. This you can see from the second axis, the y-axis, but there was a very strong diversification among treatments. And this diversification actually increased along the course of the experiment. Towards the end of the experiment, you can see towards the right side of the graph. So in the second winter of the mesocosm study, also the reclassification values of the cap analysis were much higher, also indicating that basically there was a diversification over time for the prokaryotic community. Instead, the fungal community did not show a very clear pattern, neither for the treatments nor for the seasonality or for the sampling times during the different season of the experiment. And also you can see that the reclassification values were quite low, usually lower than 50%. So we cannot basically say that there was a diversification of the fungal community for the treatments. And so this basically implies also that the fungal community is less sensitive to the conditions that we had in the mesocosms in particular. It was less sensitive to water limitation as compared to prokaryotic communities. And we relate this pattern mainly to the ability of fungal to basically create this large hyphal network to basically scavenge for nutrients and water over longer distances in the soil. Similar supporting results were also obtained by the Bipartit Association network analysis that we did. Here you can see the graph of the network for the prokaryotic community. Basically, the network which I show is indicating the clustering of communities according to treatment, so irrigation treatment and sampling time. And you can see very nicely that there was a very clear separation of the treatments for the prokaryotic community. Also, you cannot see from the graph that on the right side where we had the severe water limitation treatment in brown that the community composition was mainly dominated by Actino Bacteriota. And this makes sense because this type of organisms are actually known to be very resistant to water limitation, tolerant, and also good decomposers of organic matter. So when there's maybe less easily available carbon to be used, they can also decompose more difficult and complex organic matter. On the other hand, we didn't observe the same pattern for the fungal community composition. Sorry, not composition. For the fungal community, in fact, you can see that there was no clear effect of treatment, or at least this was less evident from the Bipartit Association network. And you can also see from the colors that the community of fungi was mainly dominated by Ascomicota. So again, it seems from this analysis quite clearly that prokaryotic communities are more sensitive to water limitation as compared to fungal communities in soils. We also did an indicator species analysis. And as you can see, quite nicely from this graph, some groups of microbes increased with water limitation while others decreased. So I would like to start with a group of, with a tax which actually increased with water limitation, as these were not so many. And you can see these at the bottom of the graphs. You can see that we observed an increase in Actina Bacteriota, as mentioned earlier. We also saw a lot of the purple dots close to severe water limitation nodes. And these are again known to be desiccation tolerant and decomposers of organic matter. We also saw an increase with water limitation of Thermoplasmatota, which are organisms which are also found in extreme environments. The taxa which were mostly affected, as you can see from this graph from water limitation, where appear to be Mucormicota, which are well-known symbionts of plants and which rely on carbon inputs from the host tree. So probably under drought there was less available carbon directly from the trees. And this is why they reduced their relative abundance and their water limitation. At the same time, Nitrospirota, which is a taxa which involved in nitrogen cycling also was reduced in relative abundance. In our study, we also observed that at the genera general level, we observed that there was an increase in desiccation tolerant and subrotopic fungal organisms. And we also observed a decrease of genera involved in nitrogen fixation and symbiotic genera. So overall, we observed quite a strong change in the community composition of our soils. Also, physical chemical properties strongly played a role on altering the composition of the fungal and prokaryotic community in our study. As you can see from this graph, both prokaryotes and fungi were strongly affected by gravimetric water content, soil temperature, as we have already widely discussed during the presentation, but also in changes in total nitrogen pH and soil organic carbon concentrations. And just to give you an idea, the pH basically was higher at the beginning of the experiment and then the pH declined over time. It remained more basic for the control treatment as compared to the other treatments. And we also observed that the pH was more strongly affecting the prokaryotic community as compared to the fungal community. And we also observed clear changes or like small changes in organic carbon and total nitrogen concentration, the nitrogen rather declined during the course of the experiment, which also led to an increase in the CN ratio of the soil, which also likely played a role in shaping the microbial community composition. So this is already my conclusion slide. And I would like to summarize a bit, the results that I showed you during the presentation. We observed that water limitation basically did not affect the relative abundance of neither the prokaryotic nor the fungal community composition during the course of the experiment. We only observed a peak during the summer season. We also observed that fungal communities were less sensitive as compared to prokaryotic communities in response to changes in soil moisture contents. We also observed that the diversification of prokaryotic communities was gradual and rather was very marked towards the end. And water limitation overall promoted the prolification of microbial groups which were tolerant to environmental stress, such as suffer of trophic taxa and rather induced a decrease in those taxa which were involved with nutrient cycling and those plant symbionts. And so overall water limitation will likely have potential effects on the soil microbiome of Scottsbank forests and will likely affect the functioning of forests due to changes in the critical functions which are provided by soil microbiome communities. And with this I would like to thank all of the people which were involved in the project, the Swiss National Science Foundation for the funding of my ambition project. And I would like to thank you for your attention and again Max for inviting us to present our work. Thank you Emily. Really interesting. I already have a whole bunch of questions to get back to but we will wait till the end and continue with the session. So thank you and just a note to everybody. I think Zoom has gone into AI mode and is loving these webinars and the talks and sending applause and reactions all over the screen and they are not being turned off. Unfortunately there's some glitch here in the system. So please go to your own reactions arrow and you can hide the various reactions that that seem to be just popping up to the very nice talks that are going. So again we'll come back to the Q&A later. So thank you Emily. So our next speaker is Nicholas Barber from San Diego State University and he's working on a really interesting system on reintroduced bison to tall grass paris and how this shift is now changing soil bacterial communities and their functions. So Nicholas welcome. Thanks so much Max. Thanks for inviting me. Thanks to everyone for joining around the world today. That was really fascinating talk Emily. Thank you and I'm looking forward to hearing from Anna as well. One thing I'll start with is that when Max invited me for this webinar I was honored and excited but I wanted to make sure he knew I'm not really a microbiologist. I came to this work very much from the ecology side. I'm a community ecologist. I've worked a lot with plant and insect communities to understand the forces that shape their communities but I began collaborating with microbiologists especially Wes Swingley shown here at the bottom and this paper I'll talk about today was in collaboration with him and other members of his lab. Does Climac who was a master student and Jennifer Bell who was a postdoc and this paper also sort of grew out of COVID times when we went into lockdown in 2020. I had to cancel plans to spend the summer doing research in Germany and was stuck at home but I was sort of fortunate and privileged to have a lot of flexibility without all the challenges and responsibilities a lot of our colleagues faced so I was able to take the opportunity to learn how to work with Amplicon data and this paper grew out of that. So I'll actually start with the ecosystem to frame this study and the questions we asked to orient everyone. Here's the lower 48 states of the US I'm way over here on the west coast in San Diego and this work took place a little west of Chicago in the US state of Illinois where you see this red star and in much of this region of the central US if you go outside of cities into the surrounding countryside most of it looks like this large-scale agriculture primarily a rotation of corn or maize and soybean but if you were to take a time machine back 150 or 200 years it would it would probably look more like this most of the center of North America the Great Plains was grasslands and this includes the eastern mesic regions of grasslands called the the tall grass prairie this enormous ecosystem stretching in a broad band from what's now southern Canada to what's now Texas and eastward toward the US Canadian Great Lakes this is one estimate of its extent these maps are very little depending on the exact definition of the habitat it's a highly diverse ecosystem with high plant diversity high plant a lot of characteristic animals but like lots of grasslands around the world this ecosystem which had deep rich soils in combination with generally high rainfall especially that eastern part of the prairie made it ideal agricultural land and so by the mid 20th century much of it was converted to row crop agriculture something like 90 percent of the habitat lost most of the remaining remnant or relic prairies are tiny patches of land mostly too small to be seen on a map like this which makes it one of the most endangered habitats in North America so then by the start of the 21st century prairies have really become important targets of ecosystem restoration to try and reestablish prairies support their unique biodiversity their functions and services so former farm fields are planted with a mix of native seeds to regrow these diverse grassland plant communities but it still requires a lot of ongoing management including control of invasive weeds and importantly from my talk today it also requires the application of regular disturbances two of these common disturbances are fire and grazing prescribed fire like you see here is applied frequently anywhere from annually to every few years because in the absence of fire that that suppresses woody plants most tall grass prairies will grow up and no longer be prairies if you saw our yumpinans talk in this webinar series last year he saw an example of this this fire mimics historical fires from lightning strikes but also importantly it mimics the fires that were set as land stewardship by American Indian tribes who used fire as a cultural practice to maintain the land in which they lived the work I'm talking about today took place in a region that's the traditional land of multiple tribes including the Peoria, Potawatomi, Ocetisakawan, Myami, Kikapu, Sok, and Meskwaki people who all lived on and helped to shape these lands the other important disturbance is grazing by large mammals historically large herds of grazing bison inhabit of the great plains but were hunted nearly to extinction in the absence of grazing disturbance many restored prairies lose plant species richness over time although many species may initially establish over a decade or two a lot of them don't persist and are often out competed by large high biomass grasses but those grasses are often preferred food by bison so bison reintroduction to restored prairies may be able to maintain higher plant species richness by suppressing those grasses and by adding heterogeneity to the environment through their activities like grazing and trampling wallowing and depositing dung and urine so a number of large prairie restoration projects have reintroduced bison over the years but it's a really big undertaking because of the resources needed so a lot of effort then goes into reestablishing these prairies and a lot of ongoing maintenance and management but restoration is often focused on on plants and animals even though as we all know soil microbes are a critical part of the system especially when restoring function as part of the the overall goals that importance is underscored by how much plant biomass is is below ground in by roots in the soil that can go meters down as shown in this famous photo by Jim Richardson and yet a lot of management choices are made based on the above ground portion of communities with the assumption that a diverse plant community means diverse assemblages of other organisms so in this study we looked at soil bacteria and asked a question how do diversity and composition of these communities change following prairie restoration and potentially in response to management disturbances from prescribed fire and the presence of these reintroduced bison we worked at natusa grasslands a large ecosystem restoration project owned and operated by the nature conservancy that includes original unplowed prairie remnants and where the staff and volunteers have been carrying out restoration since the mid 1980s each year they plant new sites usually former ag fields and they slowly expanding the reserve and the methods they use are really helpful for scientists because they use very consistent methods to seed and manage these sites with regular weed control and prescribed fire all on very similar soil textures so near the end of 2014 then they introduced a herd of bison into a large fenced unit covering about half of the preserve and within it were a range of remnant and restored prairie sites which the bison had free access to so we took advantage of this to choose a set of focal restorations that varied in age planted from 1987 to 2013 and they varied in bison access the blue sites here show where bison have access and yellow they don't and we also selected two large remnants shown in red and two nearby agricultural fields the green striped areas and these are going to rotate it between corn and soy all the prairie sites but not the farm fields get prescribed fire the schedule varies a little but on average it's about every second to year we began sampling these sites in the fall of 2013 and then spring summer and fall sampling from 2014 through 2018 taking surface soil that we pooled together from each site so we had a chrono sequence of sites from newly planted to over 25 years old at the start and we repeatedly sampled these sites so we could see how they changed individually over time and in burn versus unburned years also the bison were introduced after we completed our 2014 sampling so we have pre and post bison samples for those units from these soil samples we measured basic abiotic variables and then we targeted 16s ribosomal RNA genes using a chime 2 and data 2 pipelines to process the sequences and assign taxonomy in this study we collapsed tax at a genus level to calculate community metrics for each sample I'll show results today for alpha diversity and for community composition based on beta diversity so looking at our results let me first orient you to these next few figures starting with soil characteristics this is showing carbon nitrogen ratio of soil in restorations only just in the replanted prairies plotted here against the age of those restored prairies and all the figures I'm about to show there was a significant quadratic relationship with age so here in the years following replanting these former ag fields gained soil carbon and probably lose some nitrogen that's remaining from a legacy of fertilization and the ratio is also slightly higher with bison present those are all like I said restorations looking at overall mean values and comparing them to ag fields and to remnants um you can see carbon nitrogen ratio seems a little higher in remnants the yellow point here but the effect wasn't significant there's a similar overall pattern for soil pH in this case ag fields have a higher soil pH than the either the other query site types so then do these differences in soil conditions with age and bison translate to differences in prokaryotic diversity kind of again this hump shape pattern for both richness and Shannon diversity suggesting soil diversity increases after restoration to a point and then declines in the oldest plantings sort of like the the plant richness decline that we see in older communities here however the that apparent impact of bison on soil abiotic conditions doesn't translate to differences in microbial diversity only age effects were present and then if we look at site type on the right side of each figure there's also lower richness and lower diversity in remnants so that decline in older restorations is actually making them more similar to these low diversity remnant soils now this is all alpha diversity what about composition one issue is that the sites with bison access include both the youngest and the oldest restorations at the sites and these represent two very different site histories then in the case of older sites they're well established restorations decades old to which a new disturbance was added when bison were brought in and for young restorations these sites went through some of their earliest development with bison present those years shortly after planting when we see a lot of plant community composition changes as these long-lived perennial plants establish and spread and from earlier a week we suspected that soil microbial communities are also going through a lot of turnover in these early years but we didn't know whether that turnover would change with this new eating stomping rolling pooping disturbance out on the prairie here's an ordination from principal coordinates analysis of restoration samples so no remnants or ag fields here from just this 2013-2014 samples pre-bison each circle is a sample and if you can see the number in each circle it's the age of the restoration in years so here these are site sampled before bison were introduced just noting where they would be occurring eventually in light and dark green and samples in the sites that would remain bison free and gold at the start without bison young sites one to three years since planting in the in the light green here we're definitely distinct which which confirms some of our earlier work while all the older sites five or more years older are clustered together so the question that is what happens as these young sites get older with bison impacts present what's going to happen to them we can hypothesize different outcomes in the following years one possibility is that succession over time is a really dominant factor our previous work before bison showed up showed that age is a strong gradient so maybe over time the younger bison sites will just converge with the other site types and there's a typical prairie soil microbiome composition or maybe bison are really big drivers acting as a filter for which microbes thrive or don't and the the older and younger bison sites will converge so there ends up being distinct bison and non-bison soil communities or maybe both age and bison are drivers as I suggested earlier and bison could shift the trajectory of successional change resulting in bison sites being distinct and the compositions between younger and older bison sites again still being distinct so going back to the the pre-bison conditions what happened in the following years this is the first growing season after bison were introduced in 2015 then 2016 2017 and then in 2018 when bison had been present for three or four growing seasons we do start to perhaps see three different compositions like that third hypothesis but as additional support for that third hypothesis bear with me as I jump back to the pre-bison communities here the young sites on the right are one to three years old while just slightly older restoration older restorations marked with red stars are five six seven years old but compositionally similar to much older 10 to 20 year old sites and yet by 2018 when those young bison sites on the right and light green here are themselves five six seven years old they're remaining distinct suggesting that bison impacts it really might be playing a role in changing the succession and the outcomes of these restoration activities so we also looked at which taxa might be driving these changes we see the work I'll talk about here was was led by Wes Swingley using a machine learning approach to identify taxa with higher average information gain for random forest decision trees either across years or following bison introduction and then we could example examine the relative abundances of those taxa in relation to the three site groupings I'll just point out a few interesting highlights first a few taxa were more abundant in these younger bison sites than at the old sites here's two examples an alpha proteobacterium and a beta proteobacterium this one on the on the left here ellen 6067 is particularly interesting it's a member of the mattress of monodacy it's been documented in other tall grass soils as well as increasing in abundance along ph gradients and we did see increasing ph over time in those young bison sites but like many mattress of monodacy there also are many of them are ammonia oxidizers that respond positively to fertilization and this alpha proteobacterium in the micro pepsaceae is also abundant with fertilizers but there's no longer any fertilization in these sites except for the possibility that bison dung and urine deposition could be in the right form and maybe a sufficient amount to subsidize these microbes there were also taxa that were generally lower that were significantly lower in there we have in relative abundance in the young bison sites here's a three genera following that pattern all in the actinobacteria these genera these genera have all been found in other grasslands too and found to be rare in cultivated soils or under heavy grazing they also seem to prefer nutrient poor soils which might be what these soils look like after that legacy of fertilization goes away so some general conclusions from our results and what they tell us perhaps about grassland restoration as our restorations get older their soil bacterial diversity becomes more similar to the to the lower diversity in remnants bison don't have consistent effects on alpha diversity but they do seem to influence composition and prescribed fire had very little effect maybe because all these queries receive regular fire and rarely go more than two or three years without being burned one implication for restoration practice is that reserves that include sites with a variety of conditions different ages differences in bison presence or absence across those ages will likely lead to high beta diversity within the whole reserve because bison can drive that environmental heterogeneity which might maybe support greater overall diversity at the full reserve scale and enhance function and stability at that full ecosystem level but a couple other questions came up from this work first we use 16s sequences looking just at taxonomic composition we can ask do these taxonomic differences actually translate into differences in functional potential of these microbes and we're only looking at prokaryotes what about fungi which obviously and we saw in emily's talk are a big part of soil communities we've actually been able to address some of that in some additional work from our 2017 samples we selected the spring summer and fall samples from six restorations and then the samples in spring summer fall from the two remnants and the two ag fields and then thanks to a community sequencing program grant from the joint genome institute we're able to get 30 soil metagenomes using whole genome shotgun sequencing from these we got both taxonomic classifications and functional potential using the keg orthology database and again using both including both prokaryotes and fungi and happy to say the results of this study were just published a few weeks ago in fems microbiology ecology the qr code here can link you to the paper I want to acknowledge the lead author of this paper Kayla Mason on this paper was based on her master's thesis here at San Diego state I won't take too much time but just as a quick couple quick highlights to for some of the relevant findings in this new paper first these ordinations here are depictions of taxonomic composition at the top panel and functional composition based on keg ortholog counts in the bottom panel blue dots are restorations green are remnants and brown are the ag fields it's clear the taxonomic distinctiveness between the three site types is also reflected in their functional potential so that we might expect these different communities to support different soil functions too as one example of that when we when we look at genes encoding enzymes associated with cellulose degradation we see they're significantly higher in restored prairies and particularly are more abundant just after prescribed fire similar to what's been seen in some forest systems after fire takes place now there's a lot more in this paper I encourage you to check it out if you have time and finally I want to emphasize how much support we've had in this work especially from the staff and crew at natusa including dr elizabeth bach who is the staff ecologist and an incredibly knowledgeable soil scientist we've had lots of helpers in the field to collect soil over the years and the lab work this paper really benefited from helpful feedback from colleagues as well as editors and reviewers it funds and our financial support over the years came from several funding sources so I'm looking forward now to hearing Anna's talk as well and to our panel discussion afterwards thank you very much thank you nicolas really really interesting and we'll follow up there's already a bunch of questions waiting in the q&a so let's move forward to Anna escalante from mexico city and again looking at arid soils and what is the functional significance and microbial diversity what's happening with of course now climate change more and more reduction in in precipitation as well so Anna thank you thank you max and thank you for the invitation and I'm really honored to be here today and thank you to the all the attendees that are listening well I will just start I will talk to you about this publication from this year this is the full title functional significance of microbial diversity in arid soils biological soil crust and nitrogen fixation as a model system I want to highlight the list of authors of this paper particularly Alberto Barron Sandoval the first author and Teresa Perez Carvajal which both were master students when they started collaborating or leading this work and I'm happy to say that now Alberto is a PhD student in user Irvine and my colleagues authors of the papers also Jennifer Martini from UC Irvine, Stephen Bollock at CCCA here in Mexico and Alfonso Leija and Georgina Hernandez at UNAM as well so the the plan for this presentation today is to go through these topics or points of the paper that I want to highlight first I want to talk about a little bit about the diversity and function relationship in microbes particularly in prokaryotes and some key concepts that led to the the study first I'm sure that many of you are aware that microbial diversity is responsible for most or all biogeochemical transformations in all ecosystems but still we are debating how impactful community composition really is in ecosystem functions why well because of functional redundancy which means that different phylogenetic groups conduct similar functions in ecosystems these have at least this implication that when different communities are placed under the same environmental conditions we or many of us have assumed that these communities make function equally but we have also reflected on that the degree of to which functions and compositional changes are related in these communities may depend on the function in particular that the function of interest which might be carried out by a broad or narrow range of core co-occurring taxa for instance natural infixation is a narrow function for which not so many phylogenetic groups are capable of fixing nitrogen in contrast the composers or carbon mineralization groups are a part of a growth functional functional group also thinking about these concepts and functional significance of diversity we we post in this study that the likelihood of detecting the relationship between composition and functional processes increases when looking at functionally narrow processes such as nitrogen fixation and among highly specialized communities on this on distinct environments meaning that communities that have been exposed to contrasting conditions for a very long time like evolutionary times so with these concepts in mind we looked for a model system where we can test or evaluate this relationship between diversity and function and our model system is the arid soils and microbial communities that live in biocrosses so arid and semi-arid ecosystems are very abundant in their planet and will become more and more abundant with climate change they represent 45 percent of the planet's terrestrial surface and their biocross which are microbial communities cover 70 percent of the interplant spaces which is a lot and not only they cover a lot of space but they're the the major or main nitrogen and carbon fixers in these ecosystems and they fix 30 percent of the global biologically fixed nitrogen so it's considerable so the impact of microbial diversity in these soils the impact the functional impact might be might be quite considerable so these are the biocrosses this is like a cartoon of a biocross in some sort of sequential or succession sequence going from cyanobacteria dominated cross which is which are very thin layers dominated by cyanobacteria but there can be also moses lichens and they can evolve or success into very complex structures so this can be a succession or also there are biocrosses in different arid and semi-arid soils that they're characterized by being only cyanobacteria dominated and they never reach these these big structures on your right hand side so we were looking for cyanobacteria dominated cross because cyanobacteria main nitrogen fixers and we were looking for nitrogen fixation as a function of interest also we were looking for relatively simple in terms of composition a microbial community so we can really characterize composition and relate that to the function of interest so this is the one of the sites that we sampled and I am putting this picture on just to show you how thin these these crossed are and also to show you these tiny filaments of cyanobacteria to which soil particles are attached because of the polymers that cyanobacteria secret so these are biocrossed the cyanobacteria dominated ones and I want to tell you a little bit more about how the relationship between biocross the environment and function biocross are metabolically active only when they're wet they they're different in composition when you look at the hot and cold deserts the hot deserts receive rain during summer and the cold deserts receive rain during winter so that means that when biocross are metabolically active they experience different temperatures so rainy seasons temperatures are likely to be an important factor in biocrossed functioning so then we we thought about our the approach to evaluate this relationship and we went for a reciprocal transplant of biocrossed experiments both in the fields and in laboratory settings the rationale is based on a paper that was also published in famous microbiology ecology a while ago by Reid and martini and the rationale of this reciprocal transplants and the scenarios that we were like expecting or the possible outcomes are in these graphs we we see the different communities the dark and the light community mark here as dots and lines and different environments and at the same time the measure of a functional parameter let's say nitrogen fixation so the first scenario is that origin or composition of the communities is the main driver of the of the variation in the functional parameter which means that independently of the environment where the communities are placed are placed that the functional parameter doesn't change and it's specific to the community a second scenario is where the environment plays the main role in in the functional parameter response and lastly is the both the community or the origin of the community and the environment both played a role in the response in terms of function of the communities so we went to a sample the this cross into contrasting environments both are semi-arid ecosystems one is in this part northern part of mexico in the central northern part of mexico is cuatro cien negas in the state of coagula this is a hot desert and the other desert is a cold desert is in baja in the western north northwestern side of of mexico so they're their samples we brought them to the lab and we incubated them in different in contrasting temperatures this is just to show you the contrasting temperatures where the where the different deserts receive precipitation in the top side you can see a highlight in red the rainy season and the line the red line indicates the temperature corresponding to the different seasons and you can see that the me median temperature in the rainy season in cuatro cien negas in the cold desert is around 30 degrees and in contrast for the cold desert the median temperature in the in the rainy season is around 15 degrees Celsius so where which were our hypotheses and expectations well uh given that nitrogen fixation which is our function of interest is a taxonom is a is a narrow taxonomic function and also the potential of the biocross specialization to the specific hot and cold desert we we think that communities will not be functionally redundant and that we could actually see that but additionally we were expecting that nitrogen fixation would be higher when the crusts experience temperatures similar to their native environment due to this specialization or legacy effects also we were expecting that taxonomic and functional gene composition of the crust will respond to non-native environment in an origin-dependent way the legacy effect and finally that gene richness would decrease when crusts were exposed to non-native environmental conditions due to this also specialization and legacy effect what what was our experimental design to put these hypotheses and expectation to test well we went to the deserts we took the samples in quadrats on the on the b figure is the Baja desert and on the c figure is the 400 negas desert so it's cold and hot uh hot desert then we took the samples with these uh lead little white devices which are like a small soil uh cores or cakes of soils and we transplanted them from Baja to uh Coahuila and back um so we planted 16 cores of each of the of the of the samples and also we did control cores like ultra like self-transplanting to to control for for the manipulation of the samples uh and then or we also brought the cores into the lab and incubated them in 15 in 15 degrees and in 30 degrees as the median temperatures for the cotton and cold deserts for the transplants we maintain the transplants in the reciprocal sites for four months during the rainy season summer or winter as so the samples could experience the temperature and the and the ambient metabolically active so we could see some sort of composition changes and also functional changes and then we pulled all the the samples back into the lab to do measurements and for the lab setting we follow up the the responses and the changes in composition for 180 days we sampled at different times at 10 days and then at 90 days and at 180 days so it was t the t0 to 1 t2 1 t3 and for both experiments or for both experimental approaches we characterize community composition for the field experiment we did 16 s r na gene amplicons and metagenomes and for the laboratory setting we conducted a cheerful piece of the nif h gene and for the measurement of functioning or the functional response we performed an acetylene reduction acid for nitrogen fixation potentially so the results of these experiments we presented them in three categories one was the functional responses of the crust the other the compositional responses of the crust and then the richness responses of the crusts for the first part the functional responses I will try to convince you that we demonstrate that given the nitrogen fixation and taxonomic narrowness and potential crust specialization communities were not functional redundant and in addition nitrogen fixation was higher when the crust experienced temperature similar to native environment and these you can see in the following results and graphs here we see the the graph that corresponds to that hypothesis on the paper of read and martini where we compare the functional parameter in this case the the rate or the the effectiveness of the acetylene reduction assay and the response in that in that sense for both the cold desert and the hot desert in the reciprocally transplanted site for each one the hot desert is in dark and the cold desert is in light gray so we see that for well I have to say the here we lost a lot of the samples in the transplanting so we cannot have this part of the graph we could not do that but still we could conduct some statistics and we what we can see is the potential of nitrogen fixation dependent on both the origin or composition and site or environment and for both main effects so is the third the scenario of those hypotheses for the laboratory setting and after a period of acclimation communities showed higher but functional potential when placed on their similar temperatures to their place of origin this is particularly clear for the final time point where we measure this and so you can see for the hot desert which is this the the dark dots and lines it is they perform better in their native temperature compared to the cold desert which is the the light rate and the light and the light rate perform better in their native temperature which is 15 degrees celsius for the second part of the results in terms of compositional responses we see that both taxonomic and functional gene composition responded to non-native environments in an origin-dependent way or the legacy effects and here I am showing you the results from the reciprocal transplant experiment in the left hand side you can see in circles the hot desert samples the original samples are in dark and the post-transplant samples are in light gray for the cold desert the the dark and light is the same the dark is original and the and the gray is the post-transplant experiment but this in this case there are the triangles so you what you can see is that despite the time for of the transplant composition do not converge between hot and cold deserts they they're they're they're still more similar among them than between them and well that's that so they preserve or they're they're restricted by their original composition they do not converge and you can see the same thing in another in another way in the right hand side graph which is a clustering you see on the on the top part the the clustering of the otus and in the and in the vertical part you see the samples there are color coded for a cold desert in blue the dark is the original samples and the light is the post-transplant experiment the same thing for the red the red is for the cold desert so you can see a clear separation in composition in terms of otus between hot and cold deserts and the composition is actually mixed between original and post-transplant for the cold desert and not so so mixed for the hot desert same thing but maybe not so clear I want to just highlight that these results are for 16s and this is for the nif-htrflp so it's a little less resolution maybe and for the lab experiment you we could not see that clear cut difference in time two and in time one and time two but eventually at 180 days composition again returns to the or to the origin in a way no the hot desert is more similar to the hot desert and the cold desert is more similar in composition to the cold desert so by the end of the experiment origin and temperature accounted for almost 30 percent of the variation in composition and finally for richness responses in the frost we found that in fact taxonomic and functional gene richness decreased when biocross were supposed to non-native environmental condition and and we see this particularly or we could see this for the for the field experiment just very quickly to wrap this up on the on the left is the 16s gene richness and on the right are different nitrogen cycling pathways a richness so in both cases we compare the original and the post-transplant samples and you can see that actually in in most case when for 16s the the diversity declines when when the samples are transplanted to the reciprocal transplant experiment as we expected from the legacy effect idea and this is also true not for all for but for many of the nitrogen cycling pathways so for our conclusions of these results I would like I hope you are convinced and if not I will be happy to answer any questions hot and cold desert biocross are not functionally redundant they function differently they have different composition natural infixation potential results strongly suggest that ecological specialization may account for this non-functional redundancy in response to environmental changes understood as these contrasting environments and put to test with the reciprocal transplants both in the field and in the lab and both compositional and functional responses show evidence of these legacy effects or the site origin effect so once again I want to acknowledge our the students involved in this project Alberto and Teresa our colleagues Jennifer Stephen and Georgina another technical support that that helped very much this is Alberto this is Teresa and the funding for this project is this with that I will end and happy to join the conversation thank you okay thank you very much and yeah thank you also Emily Nicholas and we'll continue here with a little bit of questions we have a bit of time still before we need to to note the while I'm sorting through the q&a a quick question for you Anna I'm thinking of with the transplantation experiments if you would disrupt the soil how long does it take for a new biocrust to form so what's the time and that of course would also indicate I mean how long after transplantation would you maybe see a shift in the community that got transplanted well I think I have two parts of a response to that question if the crust is like destroyed it can take a hundred years to to be restored because the the growth of the microbes is very very slow particularly to reconstruct the network that that cyanobacteria the mesh that they form it takes a long time but we did not destroy the structure of the crust we actually did this core sampling to preserve the structure and then we put that very carefully in in a like a dialysis bag so we got like deposited that in the in the soil like like a tiny little cake so we were really careful with that so yeah so it's more of how that transplanted community is going to survive under now very contrasting conditions sorry I did I didn't get the first part of the question in the sense it's really how the transplanted community that is still as an intact biocrust with the species interactions in there's going to survive now under very different contrasting conditions I think they will survive I don't know well it will be interesting to go and keep sampling what's going on but unfortunately since they're like exposed to the natural environment they're probably just like with their their cows and rabbits and animals that go around so maybe if you like cage cage it you can actually follow up more we did not do that it will be interesting to be like how much time does it take to like be part of the reciprocal biocrust in the soil interesting so this is a question from Emily regarding the actinomyces that you're seeing and again they're of course known to be quite sensitive to low pH and you often see the shift of a proteobacteria actinobacteria diminishing the acidobacterioda coming up as that pH goes down so this is a question of how you fungi then also prefer the low pH condition so how do you still have so many actinomyces are they just different species that really prefer low pH or what do you know about them that's an interesting question for me to think about yeah I haven't really thought about it much so far but we basically found yeah basically an increase in with water limitation and the pH slightly declined as well under water limitation I don't know if that could have maybe stimulated also the growth of the actinobacteria under water limitation but nevertheless water limitation alone so changes in the moisture were still more relevant for the community as compared to the pH changes the second nevertheless environmental factor which was mainly affecting the community was indeed pH and actually thinking of your conclusions and you were just mentioning not major shifts in the relative abundance of bacteria versus fungi what about absolute do you have way of knowing and again this is of course also this question of changes in just sort of organic matter or nitrogen or so on how much of that could be biomass decline as well I mean you have absolute numbers of actually bacterial and fungal biomass um yeah we have actual numbers um we always compared uh so the the ratio basically didn't really change with water limitation that's what you're asking yeah with limitation experiment yeah we didn't change we didn't observe this okay and I have a question for Nicholas again in terms of shifts in or potential shifts in microbial community and also grazing do you see a shift in the plant community that could then be the driver of the associated microbiota yes definitely and there's been a lot of work in these in these prayer restorations by others and us on on how the plant community shifts with age like I said we tend to see a decline in richness and more dominance by grasses particularly warm season C4 grasses at the expense of of forbs some of our early work advice in just the first few years seems like they're that that intended effect of suppressing grasses and grass competition allowing other forbs to spread seems to be happening and particularly legumes may be responding positively some of our new data suggests that so there's certainly the shift in the plant community going on um which we expect them to be part of the the probably part of the reason we're seeing these effects in in in microbial changes too if that's resulting in changes in you know the makeup of root exit dates that are going in or the makeup of the of the litter that ultimately is is on the ground um a lot of that litter will sit there for a whole year or even in the burden years then it's you know transformed into ash that has a lot of inputs for microbes in the soil so there is a lot of turnover happening both across time along that chrono sequence but we are starting to see shifts in the plant community because of of bison impacts yes wondering also tourism in shift with responses of plants to grazing where they might produce more phenolic compounds or so on and of course now the litter quality changes as a consequence of grazing is that anything that you looked at we haven't looked at that that's certainly something i've been thinking about too of um wanting to be able to look at at a finer scale at those um yeah at how those changes and the plants might then be changing inputs that affect other microbes too certainly a lot of these um in the grasses a lot of these grasses obviously evolved with grazers um you know they're they they can respond very positively post grazing and regrow but yeah we expect there would be changes and um i'm really curious about about the root exitate changes too okay and let's see i'm looking at this this is one question on what are the implications of changes in soil microbial community structure under water stress for ecosystem resilience and actually i'd like to expand that to the all three of you in terms of okay yes we can see shifts or so on the question of redundancy so even if all the species are different do they still do the same thing so does it matter and so how would you put all of this really into this context of how resilient is the community to whether that is water stress or grazing stress or then this aridity and changes in temperature so maybe Emily you can go first yeah that's a really good question um basically we have thought about it a lot and it's interesting that basically in our mesocosm study this is similarity between of the community continued to occur so the basically the the community continued to diversify under the water treatments over time and um this basically means um yeah the community is able to sustain water limitation because we still continue to find microbes in it nevertheless the functioning probably changes i mean we didn't study functioning directly in the specific study but of course uh we saw also shift in specific communities of bacteria and so what is expected is that potentially the the functions the critical functions provided by the microbiome in the source will be altered and this will then create problems for ecosystems unless there are then changes for example in terms of the climate that there will be fewer droughts if we really do some mitigation efforts yeah so that was my answer for now yeah Nicholas why don't you continue um you know one one thing i've been curious about is if in years where we may find uh faced drought stress in this environment if it changes uh grazing patterns that because these animals have access to a pretty large area you know hundreds of hectares in size they have a lot of choice of where they particularly graze and if they seek out lower line areas that maybe aren't facing as much drought stress as upland areas where the and these sandy soils can become really dry during drought years that could sort of amplify those potential grazing effects in very specific areas and um and you know at sort of an additional level that heterogeneity by heterogeneity by changing grazing pressure at a really fine scale and maybe again drive even further these differences that we're seeing of potential grazing impacts on the on the soil microbial community at the same time the site we're working at you know the benefit of all being a relatively local compact site is that you know the the sites are at most a couple kilometers apart so they generally face the same um weather every uh during throughout the year so um it limits our ability to look at a given year of say you know our wet and dry sites because they all tend to be wet in the same year or they all tend to be dry in the same year okay uh i may have a can i ask a couple of questions um sure yeah i this is i guess it will be both for emily and nicolas um what do you think about how long the like follow-up experiments should be should be followed because for instance uh i followed my experiment for for months our 180 days and emily did the mesocosms for it was a year or something like that two years uh and well nicolas has a follow-up for many years so i guess it depends on the questions of course uh do you ever feel that you get to have a final answer of like now we we know that these communities restored or it just adapted or when do you stop and when do you actually feel comfortable when saying well now just like a philosophical question i think but it's something that i always think about what do you think emily go ahead you answer first yeah so actually the mesocosm study that i presented today was the results of one year we continued also the mesocosm study for a longer time the results were similar in the sense that the community continued to diversify over time and at the end we decided to end the experiment with with leaving the trees die and checking out what the community changes in the soils would be and of course it was a mesocosm experiment with small trees it would have been really great to keep it for a longer time uh and maybe let the trees grow a bit more than we probably would have had to transplant them to bigger pots and i think um using like one basically can have different types of experiments in combination i think that's probably going to be the best way of understanding mechanisms like combining small scale experiments such as the mesocosm experiment but also the mesocosm in the field sorry the field experiments and studies what nick has done and transplantation also is definitely a great tool for certain ecosystems for most ecosystems i would say so i think it's really important to stress um this that we need more experiment in the field but also more longer termo observations and the combination of everything together plus modeling will really be beneficial to get a better understanding but i think it's difficult to really talk about the best scales i would say um depends on the research questions that one needs to answer yeah and i would echo that i was struck to by our our three talks and this this mix of experimental approach field approaches and combinations and the different perspectives we get in terms of how long to follow it's other is a question that was posted about asking the long term changes and i i go back and forth over what long term means in in my study system that on the one hand we're looking at sites that are three plus decades old which seems very long term but these are ecosystems that are our restored sites have probably been a similar habitat for hundreds of not thousands of years and we still see even our oldest restorations that are 30 plus years old things like root density in the soil is still less than what we see in old very old unplowed original remnant sites and so although there's you know there's certainly a rapid turnover in the first few years that we see both in the plant community and in microbial community um that levels off and maybe you're not getting as much rapid change after a decade or two um there's still ongoing changes and and i don't i don't know when the end point is uh to see that um um we also often see sort of in the early years a rapid decline in in nitrogen as sort of that legacy of fertilization i mentioned goes away and then over the long term um total soil nitrogen may slowly increase again as as organic matter is is in the sort more in the soil and that root density tends to build too so there are just long term changes that may take many decades if not centuries to really um to play out no agree so i think i want to wrap up with one final question here from the q and a and this is about viruses so given that soil viruses are known to be highly sensitive to environmental condition variations are you considering investigating whether they could account for some of the shifts in microbial community uh i mean affecting both bacteria and fungi and i know i mean this is going forward because none of you had looked at the viral communities but they are microbes too and of course major influencers any thoughts well yes uh which i mean is not that i'm going to do it but it will be great to collaborate with someone that has experience on viruses that are yes there are microbes but they're like their behavior and all the techniques to study them are like very different and they're definitely drivers of both ecology and evolution so they they're part of the show and should be included that's my comment yeah i'd also love to look at this i'm in a department with a lot of virologists who bring this up a lot and my answer is often i i don't know that's a great idea we should look and do it i think that could be a really um just another additional ecological interaction we haven't considered yet and what might be helping to shape these uh the composition of these communities and of course i think also plant viruses that then interact with the uh prairie plant so yeah absolutely emily any added thoughts i totally agree with all of the comments made yes definitely important topic to to consider and this of course might be a topic for our next webinar so i would take a look at uh at papers and we're probably going to continue in the spring again with with a new topic so please keep it be posted but no i think we need to wrap up so uh thank you emily nicholas anite was wonderful to hear from you and hear more about the studies that you had published on and again thank you everyone in the audience from really what i saw over the world and again if you missed parts of this the webinar will be available on the uh under sites both vfm's and oup probably in a week or two and of course there you can also catch any of the previous webinars if you missed them so again there's information and of course you have links to the paper so you can read more so so again uh thank you everyone and uh i will see you again at our next webinar thank you all thank you thank you thank you


Hi, my name is Amitabh and today we are going to talk about enabling DRAS and OpenStack. Just a little background about Persistent. Persistent is an outsourcing product development company. We have been engaged with all kinds of applications for ISVs, enterprise, and we have been engaged with Cloud for about a few years. We have roughly around 600 people working on different kinds of Cloud technology and about 100 people working on OpenStack. Hari is here to talk about his experiences with enabling DRAS on OpenStack. Hari. Thank you, Amitabh. Hope you are doing good. So disaster recovery as a service is on an OpenStack is what we were trying to do. We tried to enable a disaster recovery as a service on OpenStack. So basically I would start from what's a DR, basically go through those things. So why do we need this in first place on a Cloud or on a on-premise or on your laptops or something like that. So disaster can happen anywhere. As you know on all our Clouds or a nodes, compute nodes, your machines can go off anytime. There could be a node failure or there could be a power failure. There could be natural disasters. There could be software errors. You don't know when your instance or a VM goes off. You must have your DR plan or at least the backup plan ready when you are when you are running typical services or business critical services on the top of OpenStack. So this talk is basically about how do we achieve a DR service on the OpenStack for the loads which are on the OpenStack as well as on your on-premise or around or on your simple private Cloud. So why do we need this DRS OpenStack or rather what I would say why draws is required on the OpenStack. See first and foremost thing is to bring new customers to Cloud. Basically that enables private Clouds or the public Clouds. If you are hosting your public Cloud or own public Cloud or a private Cloud. So if you subscribe or if you allow subscribers to ask to subscribe for a DRS, then it would bring you new customers. The second thing is like some providers or if you are running an application specific Cloud or let's suppose you have a private Cloud where in which the data is very critical you are running some customer services on it and you want to have a backup plan where in which if the node goes off you just want it to do. So then you could actually put a DRS service on a OpenStack cluster which might be a scaled-down infrastructure of your original private Cloud and then subscribe the service and subscribe these VMs to actually do. So that's co-located DR infrastructure. And next as such we all know for the business continuity. Then the DR option should be homogeneous environment. So for example if you have your DR Cloud on your OpenStack and if you have a similar DR, the destination DR also on the OpenStack then it is more susceptible for reliability. So you get the same environment here and you get the same environment there you don't need to adjust, reconfigure, retry and you don't have a doubt that it could fail. And then you should have RTO and RPO. Many applications have a different RTO and RPO application somebody needs. Again I need an instance immediately the replacement instance very immediately or somebody could say okay even if it fails for an R but immediately within R if it comes it's okay. So those are the four main areas a usual DRS service and OpenStack would solve. So let me just take through the agenda what we are going to do in this particular presentation. So first is we will evaluate what are the sources of DRS. So basically we identify the candidates wherein which you could do a DR to a OpenStack, OpenStack based private or public environments. The second is what methodologies could be used or what techniques could be used such that the OpenStack environment could be used as a DR service and what are the complexities and what are the troubles which are associated around this. And then we go through a small evaluation of what are the things today's OpenStack needs for a DR to be enabled on OpenStack. So that's one thing and then next we see what are the next steps, how do we go ahead and put a full-placed DRS service on OpenStack. So if you see the sources of a DR, a DR could be enabled for anything, it could be on a physical machines or a virtual machines which runs a traditional KVM or Zen hypervisors where you just have your machines there and you wanted to put a DR option to a private cloud, OpenStack based private cloud or an OpenStack based public cloud. Then your private cloud itself could have a DR to a public cloud. So this is one case where in which you have your applications or a workload running in a very small private cloud or an application specific cloud. So you are more concerned about the data and then what you could do is you can say okay these VMs you move it to a DR, keep your backups there and if in case your private cloud fails, you move it to the public cloud. So very basic steps here like any DR if you have to do like or not only on the OpenStack or anywhere. So basic DR is like involving on the source side you snapshot. So you either snapshot or you convert it into a way where in which you take the data packets or the changes you know basically the delta changes to the destination. So whatever is happening at the source must be in some way repeated or replicated at the destination. So that's the first step.  So the transmission media very well or trivial in these days is like you send it over a wire or a fiber cable or some kind of a process where in which you could be able to send this data from source to destination. The third thing is you send the data and you have it to the destination safe. The third thing is you have to detect that okay the source has failed and now you have to start up. So that's one more step where in which you continuously monitor it could be an Agios script or something which is monitoring the source and it triggers okay now I am failed and can you please bring it up on the other side. Next you provision from that particular place. So provisioning has certain challenges that could be the recovery time objective or point objective but those are the challenges which are there in this particular step. So let me just reintroduce the terms which many of us are familiar but for the convenience of everybody you know RTO or RPO is like RPO is the recovery point objective where in which you say okay I if the disaster recovery has happened now how much time before I could get like for example if there is a disaster at this moment okay what is the least point I could get my system from so what's what's what are the unsaved changes I'm going to lose and RTO is like if I have a disaster now and I request to give me a backup what in what time I the replacement service will be available and then delta backups are typically the changes in the data from your last recovery point or last backup point to current backup point so these are the basic things and this is what we we tried and we see it is successful so what what we do as part of it is we took a standard hypervisor which is running a KVM and spawn some virtual machines around and then we have a DRS service in a virtual appliance and then we have one more appliance which is called as a data set data VM so dras service is kind of a landing point where in which all the agents if you have a multiple agents or a multiple sources they come to your DR cloud or the cloud on which the dras is hosted and then the data packets are being sent the dras agent on the source side keeps a config has a configurable way of taking the delta changes so it could be as less as 15 seconds or it could be as good as one day as well so it captures the data delta differences and senses and on a packet on the dras service so that's the first step so dras agents request the data backup and then dras service then what it does is it sees okay what what exact data what exact endpoint is trying to do a DR or do a backup then it assigns a data VM where in which it coordinates the underlying storage to save the snapshot so in this alternative what we are proposing is we use the bootable volumes feature of the open stack okay to save the DR disks this is because because this is because of two reasons reason number one you if you use anything else your recovery time objective will be more because the moment you send a packet and you keep it up with you and while recovery you need to copy it first to glance and you need to again copy it next to to the specific node during the VM boot up so there are two copies of the same data and if you are trying to copy a trying trying to copy a machine of one TB or so it would be around half an hour so if you are considering about a less recovery time then go for the bootable volumes way this this this alternative and then after the data is backed up so somebody has to trigger the backup so that the triggering is like happens from a user or a script that the triggers the data backup when when you say okay trigger the data backup so what what the drug service is drug service does is it goes on checks hey this is this is this is a machine drug service is being has to spawn up so what it does exactly is it it mounts the bootable volume it it asks it issues an over boot commands to to the public cloud or the private cloud or a controller so then when it is issuing it does take the policies which are predefined or it could be given at the dashboard so it could be a reduced reduced flavor or a full flavor or a defined network settings or you can predefine using a config drive and the replacement instance comes up and it could do a self-check and it is available so we have another alternative for people who are not very very conscious on RTO if somebody is okay with a bigger RTO and doesn't want to use a lot of block storage okay then that's that's alternative to where in which what we do here is almost the thanks functionality is the same but instead of having two different VMs one a drug service and a data VMs scaling out together auto scaling to those we use we leverage the swift service so what it does is though it's here it's it's just the agent what agent periodically does a snapshot and takes the delta differences and pushes it to swift and after it pushes it to swift it just updates the meta meta data file saying that hey I have updates so and so on to the drug service so it keeps on going on and you could actually configure after how many DR snapshots are backed up you could match so periodically on the on the destination side these snapshots are matched periodically but usually you could keep this on and on going so what happens is so in this alternative when when there is a in this alternative when the when there is a DR request or a disaster request then the drug service detects which which VM is required to be spawned up and then what what it does is it first merges all the snapshots and makes a feasible and makes it and makes a feasible image out of it and then it first uploads to the glance and after it uploads to the merged merged image and glance and then it starts the compute to spin up the replacement VM and then the replacement VM would spin up and be available for the services this approach has a specific advantage that you don't need a support from any provider so it could be any vanilla open stack don't need a change don't need a lot of resources for the draft service itself to be run so you just need swift you just need a compute the another advantage for with this is if you are in a scenario where in which there is a very less amount of bandwidth that is available for the cloud provider so if you are bandwidth conscious of saving the data you could use the CDN services of the swift and then you could actually back up to a very near location so this will be very useful if you are if you have a machine that needs to be backed up at a very remote location or a or like a machine across the instrumentation machines or data machines across the lines of a railways or telecom points or those kind of stuff so if you really want to save data from there you just have a and you have a very small data pipe you could use a swift and which is over a CDN service and then you could do that they even then you could be able to recover that that so there are two alternatives which but in this case the RTO will be more than what is in the alternative one so there could be two ways okay but RPO this alternative will be more suitable for things where in which okay you say you back up it one one day once a day or so so the alternative one would be suitable if you want to have a frequent back backups and alternative to which is presented here will be suitable for if you for cases where in which okay once a day is fine and this is a steeper solution with respect to the first solution and next there are some challenges which we wanted to specify so while implementing this and while trying this out is one is like the huge data which is involved in when you are moving from the source to destination so if you are writing a disk in intensive programs or if you are saving a big big video files that would mean that your delta files are big and that would mean that you are going to choke the data pipe between the source and the destination cloud that's one one thing which is which it still remains that is still a challenge we didn't find a way where in which you could slice the delta backups so if if either you send the entire packet a large packet in that particular time or you don't send it but that's that's one challenge and in the RTO and RPO times at times we see requirements such like you will have to boot within less than a minute so although we we have all those things like applying these delta backups at the destination we're taking a little more than time than less than a one minute so one minute kind of a story or two minutes kind of a story of a RTO and RPO are particularly very challenging when there is a lot of data which is generated at the source and next like some people are not ready to change their open stack installations not even agent they don't want you any agent to sit in their hypervisor or anywhere that's you know that's that's one that's one challenge we wanted to still make it working so people are concerned about installing agents at the agents at the source where in which it's like a laptop or a physical services people are concerned about adding more capacity to sender you we will put things on sender so that's that's one one of the challenge we see and application coising is one thing when we when we wanted to take this DR to even applications coising where in which DR should be done in group of clusters it was always a challenge because the way you the way we use we use the single data pipe and it's like there is no way all the three machines are synchronized so it there should be some intelligence which is on the agent side also you there in which you group other clusters or group the VMs into a same group and then you when you when you do a DR on the other side you you do in a synchronous manner so that's one thing and small some small implementation issues like like trivial open stack style of implementation issues still exist like this is a flag and this is a flag and some security rules you have to add these configuration files and those things and these are the challenges part of it and I would go to next steps next steps is like we wanted to put a incubated project for DR as an open stack and then the disk replication today we what we are doing is we are using a disk replication agents on the source and destination but if we have a disk replication service such that okay can you replicate this VM as to a destination or something like that and it would be more useful from when you are doing a DR from open stack and to open stack or vice versa and then like the agents story so so today we have a challenge that if we say can you put this agent on a guest VM your guest VM people are very concerned about the security of that because they don't they didn't evaluate it or they or they didn't see what's what's in that so making the draws agents which are making draws agents public and making them as part of a open stack releases is also need to be considered such that you have the agent which is tested tested across your security and you just trust okay if you are if you are okay to run a open stack code you are okay to run the open stack agents as well so that's all from my side so do you have any questions please you talked a lot about the infrastructure piece of you know the DR moving of EM getting it to the DR side etc etc but there's other pieces involved such as network configuration and so taking a snap of a VM and moving it somewhere is pretty trivial right there's those are ways of doing it but the actual bringing the VM online and making sure that it's on the right attached to the right network in the same VLAN is there needed be the same AD server by pointing to the DNS and then it going a bit deeper the application configuration points to a certain host name convention so the D the domain name sub domain name change etc etc how are you planning to do with that that's great so so in that scenario we wanted to go to the open stack way of describing the workload so if you are we didn't talk extensively about that because this is this presentation was mainly from you know either if you are migrating from this if you are migrating from a on-promise or a laptop to the destination and here there was a piece which is called a dashboard okay in the dashboard or the API could actually have these information of the network or so but when you are doing from a open stack to open stack you could always use a config drive the way we used is a config drive or you could actually write out things around you know the APIs to support the workload description it's not just the it's not only just the network configuration we are concerned about sometimes there are attached volumes also yeah so there are many services there are also services which are there so the right way to go about is to have a workload description properly and then when you when you take it to the other cloud you just reiterate the same workload description so it's not only the disk changes because the talk actually considered concentrated on the disk changes and how do you move a VM but actually it also needs to keep track of the changes in the metadata that happens to the VM also also the owner and all those stuff yes I agree with you on that yeah thank you so in your option one you're proposing to use volume block storage did I hear you that you're proposing that the agent should be doing Delta storage into block as well so we have the you know you're doing VM deltas yes yes and so is there also the idea then of re-accumulating those deltas into us into a single boot volume periodically like you have an option to yes you know like the delta you what we should do is we should keep the bootable volumes exactly in sync so if there is a delta packet that is sent from the source you just extract it then and there so you don't you don't accumulate the deltas and then when the DR happens you don't apply them so if you get a delta you apply that so if you have you done a proof of concept on that yes and that works yes that works okay and so you've got so you're applying these deltas directly to the to the volume to the bootable volumes and in real time yeah it's real you know in a real time so I get a delta and you apply so we ensured that the source disk is exactly replicated by the Cinder disk so at any given moment when when it is consistent so the Cinder is exactly Cinder is replicating the source they both are on sync so when you boot up you just boot up from the volume so there is no copy which is involved so you can get a big you know very less RTO yeah gotcha all right so and then the agent itself you're proposing that that is that's something that you guys wrote in in your proof of concept is that correct in our proof of concept we have used a agent which is proprietary today so so we wrote you're on right right and so moving this into an open stack project how would you propose to deal with that agent capability is that is that a new service is it a component of each program of each project how would that get delivered so the whole concept of this talk is to keep that keep the changes in the each projects very less so we don't intend to change any project so we just want to put one in new incubated project and say this is going to have the services and we keep the changes in any of the projects to the minimum level possible such that we just use whatever today is on open stack but if that would mean that there are some little changes to be done we wanted to go ahead and propose that through blueprints and get it done and on the agent side agent side should should come into a ecosystem or on a public side where in which there would be agent for a physical machine windows operating system or there could be a agent for a KVM based hypervisors Zen based hypervisors for VM VM Bayer kind of stuff so all these agents you know they store their data in a different different way so it is the that intelligence that should come from there and why a different agent is tomorrow you know down the line we should be able to even backup our mobiles you know you have your mobile you install agent on a mobile you send the entire data of a mobile you have the copy some day you lost your mobile you at least have all the snapshot running on a simulator that that's the whole thought thought process behind why you wanted to put a agent per you know per kind of a device we're still trying to figure out you know how to contribute what we have and whether we need to do do a different blueprint or a different mechanism to distribute what we are writing on the agent side still working the details out but we'd like to see it go out okay thank you thanks hello our RMS interesting talk I'm interested in the testing that you guys did what quantity of VMs have you failed over and what do you perceive in what services do you perceive an open stack will be under stress during a DR failover scenario okay we tried with a five or ten VMs in our lab so then there are a couple of VMs getting backed up regularly so answering your second question definitely it is the input data input pipe and the end points where in which your VM is running so I don't think it will be stressed stress on any open stack services as such either the neutron or Nova or cinder or whatever it is but there would definitely be a stress on the network back play in which you are taking because if you are backing up several hundreds of VMs and the Delta changes particularly where if there are a huge rights on the discs and the discs are changes are big so your data pipeline is going to be loaded or stressed and if you have if you don't have the capacity planned enough to that level then your network may go slow but as such it's only a couple of Nova requests such that you don't see a big stress on running open stack services or so but you will definitely see the stress on the discs and the disc rights and disco I was and the network you know regular network traffic of the open stack did I answer your question so I have a question around you talk about how to send Delta from the primary site to the R site like you have any thoughts around how to move back the workload to the primary site after the disaster that the cause of disaster is removed do you keep deltas in the disaster site as well you just push back the deltas to the primary site or do you have to copy back all the data so we haven't done that work right yet yes we didn't do that work but that's a very good question there are some challenges which are involved so if your source is a virtual machine and if your source is a KVM kind of a hypervisor we have no problems moving that back you just move that back and rename and can turn on it as a different virtual machine you have all the changes back but you will definitely have a challenge if you if you have turned on a physical machine so there the blocks are different here the blocks are different so it depends completely on a very intelligent agent and if you are able to save that metadata also and when it comes back you will have to reapply and you should be able to reapply on the source so fail back is still debatable or at least I should I should say I haven't understood till now so I haven't have I don't have a way to answer that just a just a quick background right persistent also has a small disaster recovery as a service offering for SMB which runs out of a different division right and we are learned we have learned and leverage a lot from there and we are incorporating all some of the complexities which we have learned in this experiment which we are doing to see how we can take what we have and move it on open stack hi I'm concerned somewhat on policies what kind of retention policy you might have especially when VMs come and go effectively they no longer have any use in life and you terminate them how do you clean up the backups otherwise your Swift store is going to continually grow and eventually run out of space likewise how do you determine again via policies which ones are loved VMs versus the ones you should ignore and not do any DRs on well as a DR as a service we don't define that particular policy so it's it's up to it's up to the configurator or it's up to the user to choose which VMs to be having a DR or other so but I take the I take you a first question how much time you are going to keep your data as long as the DR is required we we just we keep the data and periodically we will merge we can merge the snapshots such that it doesn't take different different objects there so that we should be able to do it programmable and configurable so did I answer your question so one one more way to deal with this right and this is again from the experiences from our our cloud business which we are offering as a service to customers right we provide them we basically sell storage not VMs and in that particular practice that particular product right and we provide a mechanism by which we can say hey you know this is the max if you are interested in 100 terabytes worth of storage and you know at any given time you can spin up n number of VMs you know that's what we allow and and we define set of policies on what what types of VM and and snapshots can be deleted from the system it's completely customer driven at that point yeah you briefly mentioned some sort of replication engine or a generic replication engine an open stack could you elaborate a bit on that and add any thoughts about what sort of apis you might have for a generic interface to maybe different replication engines or well that's what that was the thing we are still going and we are thinking but what what we would need is like we all agree that there there must be some kind of a replication that should happen from the source and source to destination in a scenario where in this open stack to open stack the replication becomes more prominent or it is more visible from the functionality for a part of it one if I am a open stack endpoint I should have a capability to push my changes to the destination cloud so that that's one capability today today's open stack doesn't have so that we need to add that if if you are acting as a source you should be able to write to any kind of a destination okay there is a change that is happening in the this attachment you know let it be metadata so you you do a push of that and then when you are on the destination side you should be able to take different different replicator connections you know you should actually support a replicator plugins to the open stack such that you if you have a plugin and you have a replication endpoint you know you could bring third-party or a commercial solutions such that you don't need to worry about replication piece or you need you don't need to have a data channel through your network so you you can leverage the commercial very efficient things there so when you have this drafts as a service as an open stack project then you can always have a replication plugin so you define a drafts and you could have a replication hooks and in the hooks you could choose what replication will guard them or licensed or whatever whatever public open source or licensed products there so that's that's what that's how we are thinking to put that across any other questions thank you very much for attending thank you very much thank you very