This is my email ID and the topic of today's discussion is Sternberg's Theory of Intelligence. For further update, kindly join my telegram group, explore education. This video will be bilingual and this video will be useful for UGC-NET, CTECH, UPTECH, KBS, NBS and other sort of teaching examinations. So before we start this topic, a quick review of what we have studied about intelligence till date. We started with the history of intelligence, then the concept of IQ, then the theory of theory. We studied that the theory of intelligence was mainly divided into two parts. There are two approaches to study theories of intelligence. The first is the psychometric approach and the second is the information processing approach. In the psychometric approach, we studied many theories and ended the topic. In the information processing approach, we also covered one theory, the theory of multiple intelligences, which has been given by the Harvard gardener. Today, we will study the second theory in the information processing, Sternberg's theory of intelligence. It is a very important theory and you can say that in the last 10-15 years, it has become more popular in the last 10 years. This question is asked and it is also a bit typical to study it. So we have to remember many things. So in the objective, if you want to work with recall, then you will be able to put a tick on the answer. And if you are going to give theoretical examinations, then you should know the good content. So, first of all, we know who Robert Sternberg is. He is an American Psychologist and Psychometrician. An American Psychologist and Psychometrician and he is Professor of Human Development at Cornell University. He is a professor of Human Development at Cornell University. His major contribution to psychology is, sorry, the triarchic theory of intelligence. So from here, we will understand that the name of this theory is triarchic theory. Apart from this, he has a lot of contributions to psychology, such as creativity, wisdom, and he also shared his viewpoint on love and hate. But we will only study triarchic theory here. And how important it is that you can understand a review of general psychology survey, which was published in 2002. He ranked Sternberg as the 60th most cited psychologist of the 20th century. That is, in the 20th century, only the 60th number of people have been cited. And this is the 60th number of people who have been cited the most. So we can understand how popular this theory is. Okay, now let's know how Robert Sternberg is defining intelligence. We will be able to take a little viewpoint on how he has seen intelligence. We have understood so much that it is under the information processing approach. This means that we will know how an intelligent person processes information. That is, we have to study processing. Okay, so according to him, intelligence as mental activity directed toward purposive adaptation to selection and shaping of real world environment relevant to one's life. Means, according to him, the intellect is a mental process which is purposive adaptation. That is, they are talking about uncertainty, they are also talking about purpose. But he included the real world environment, which most of the psychologists had not included yet in his definition, in his viewpoint, in his conception. So there is selection and shaping. That is, the environment has to be made according to itself, relevant to one's life. That is, according to your life space, you have to select and shape the real world environment. Okay, then he agreed with Gardner. Since both the people come into the information processing, there is a similarity somewhere between the two. He also believes that intelligence is much broader than a single general ability, G. For example, Gardner is opposing G, that only G can not be done according to multiple intelligences. Similarly, he also says that intelligence is much broader, something is much bigger than G. But he says that Gardner suggested that some intelligences are better viewed as individual's talents. But he says that many people are telling, like what Gardner is telling, he is telling linguistically, he is telling musically, he is telling naturalistic, interpersonal, intrapersonal, kinesthetic, he is saying that as far as they are concerned, according to the standard, it is more of an individual's talent. There are less types of intelligence. So this is his viewpoint. Let's talk about Gardner. But where does he show similarity with Gardner? Where he says, yes, intelligence is much broader than G. Okay. Then, Sternberg's conceptualized intelligence is much broader. He defined it in terms of the ability to achieve success in life. Meaning, for him, for Sternberg, both intelligence and success are going in one direction. It is not that we are very intelligent and successful in life. As such, he denies that a lot of IQ tests are applied to us. Our IQ is getting very good. But we are unsuccessful in life. This means that he does not have the right understanding of intelligence, according to Sternberg. He says that intelligence should not be there so that we can be successful in our life according to our personal standard and within one's sociocultural context. And he has kept society and culture with him. If a person is successful according to his personal standard, then he is intelligent. Okay. Then, the ability to achieve success depends on the ability to? Whom will the ability depend on? To capitalize on one's strength, on one's strengths, and to correct or compensate for one's weaknesses. And we will improve our weaknesses. That is why, Sternberg's definition Sternberg's definition is called TRIA's theory. Successful intelligence is also sometimes known as successful intelligence. So, if we are asked who is talking about successful intelligence, we will put Sternberg in particular. Okay. This is the first theory. It is divided into three sub-theories. Before this, there was no sub-theory of any theory. So, what is their sub-theory? Look here. This is a componential sub-theory. It is an experiential sub-theory and contextual sub-theory. They have told the components of this theory, of this theory, of this theory, and of all their sub-components. So, let's find out which three sub-theories are confidential, experiential or contextual. This theory is comprised of three sub-theories. Componential, experiential. Sorry, these are two-componential. It should be contextual. Then, each sub-theory is their sub-theory. They have put it together with each intelligence. That is why they are talking about the theory of intelligence. So, we will go to their sub-theory later. So, let's find out whose components they have analytical or academic intelligence corresponding to them. Experiential sub-theory is their creative intelligence. Contextual sub-theory is practical intelligence. Componential sub-theory is meta-components, performance and knowledge acquisition. Experiential sub-theory is novelty or automation. Contextual sub-theory is adaptation, selection and shaping. Okay. Then, let's pick up a component. Componential sub-theory is it outlines three structures and mechanisms that underline intelligent behavior, categorized as meta-components, performance components and knowledge acquisition components. Since it is componential, let's talk about the components. What are the components? Meta, performance and knowledge acquisition. Then, what are the components? Structure means that underline intelligent behavior. If any intelligent behavior shows an individual, it needs three components. Meta, performance and knowledge acquisition. What will a person do in meta-components? He will decide. He will make a strategy.  He will allocate his mental resources and monitor them and evaluate them. After meta-components, performance components are coming. I said that it is high-rare. What will be the performance components? The components will be encoded. You will put some combinations and permutation combinations and comparison. Then, knowledge acquisition will come. We will select some and make some combinations and comparison. Then, we will act accordingly. According to Sternberg. Let's understand this. What are meta-components? Meta-components are higher-order mental processes that determine which performance and learning components will be used as well as the sequence in which they will be used. Meta-components are higher-order mental processes. It is the most important to understand which performance components will be used and why they will be used as well as the sequence. Then, what are the performance components? These are lower-order processes. What will be included in this? Encoding, Combination, Comparison and Response as shown in the picture. Then, what is the knowledge acquisition component? These are lower-order processes. What does it discover? Knowledge and information are needed to solve the problem. Which knowledge and information are needed to solve the problem? Intelligent behavior is required to solve the problem. So, Sternberg and Davidson have explained three types of selectivity. This is in the picture. Selective encoding, Combination, Comparison. Selective encoding means involving sorting relevant information. What will we do here? Selective combination means combining information. How to combine information from isolated pieces into a unified whole. That is, we will create a single component that has a meaning. What we will do in Selective Comparison? Involving comparison of relatively newly acquired information to information acquired in the past. In the past, the information used and the new information that we are using now are being compared. So many types of mental processing are going on in accordance to Sternberg when we are showing intelligent behavior. Okay. Then comes the experiential theory. So, what do we call experiential theory? The experiential theory proposes that it can be interpreted along a continuum of experience from novel to highly familiar task situation. That is, it is saying how intelligent behavior is showing the continuum of experience. That is, it is going on in continuation. There are only two poles. One pole is the novel. That is, we have to do something new. So, how do we behave now? And it is highly familiar. So, what happens in this? When a person is presented with a novel and unfamiliar problem, that is, we have a new problem in front of us, such a problem which is unfamiliar to us. We have not had that problem. So, they need to use their intelligence to find new ways of solving that problem. So, what do we do? We will use our intelligence so that we get a solution for it. Then, as an experience becomes more and more familiar. That experience has become familiar. It shifts from novelty to automation. That is, we will take out the solution in the same way. This that people have completed many times becomes automated requiring less conscious thought. That is, if we face the same situation again and again, that situation is not normal for us. Now, we can take out unconsciously its reactions, its actions. Okay, then this sub theory relates intelligence to the external world in terms of what behaviors are intelligent and where. That is, when we are outside the world, which behavior are we showing to the intelligent and where we are showing. Then, it addresses the relationship between the behavior in a given situation and the amount of experience of the individual in that task's situation. Why? Because the experience that we are taking to the other side. That is why its name is experiential sub theory. And what it says is that according to it, people are creatively intelligent to the extent that they can cope with relative novelty and automatize. Routine aspects of tasks so as to devote more resources to novel stimuli in their environment. What does it mean? That people are creatively intelligent. At that time, the world cannot cope up when they are in a relative novel situation. How to automatize them? How their resources and environment are. That is, our whole body, our whole goal is to automatize from novel. That is, new problems are familiar to us. Why? Because we are involving so much experience in it. We are putting creativity in it. Then, contextual sub theory, which is called practical intelligence. So, according to the standard, it deals with the mental activity involving attaining fit to context. That is, we have to fit according to the context. That is, adaptation means in the real world, the way the situation is, the practical person is told that the way the situation is, we will react the same way. This is practical intelligence. And according to Sturmbur, this is a very important component of being intelligent. And until now, theories or the IQ test are not asking us about practical intelligence. So, we will keep practical intelligence only then we will be successful according to Sturmbur. Whereas, the old theories were not talking about it. They were making people unintelligent. Okay? So, this is the difference. It states that a person's intelligence is heavily influenced by their day-to-day environment. When we are talking about our daily death, it will also decide how intelligent we are. We are able to deal with our daily life. So, it will be said that we are intelligent only then we can do it. And it is based on their need to adapt to their environment. So, we quickly adapt according to our needs. Adapt their environment to them. And how we adapt our environment to them. And to make the most of their surroundings. That is, the best output we can make out of our environment is, we are practically intelligent in accordance to Sturmbur. What else am I saying? It specifies that intelligent behavior is defined by the socio-cultural context. That is, they took the society and the culture along with the intelligence which the old psychologists were not doing. In which it takes place and involves adaptation to the environment. Selection of better environments and shaping of the present environment. That is, we have to select and shape the environment according to our needs. It is the ability to adapt to everyday life by drawing on existing knowledge and skills. As much as we have existing knowledge, as much as we have knowledge, as much as we have caution, what do we have to do with that? We have to make our daily life unique according to our needs. Then, through the three processes of adaptation. What are the three steps in adaptation? Shaping, Selection and Fitting. We have to adapt, shape and select. What will happen? We will be the best fit-in according to the environment. Then, we come to the types of intelligence. If we understand everything, then we will understand the intelligence because it has an according. For example, the component is called analytical or academic and experiential is called creative and contextual is called academic or academic or academic intelligence. Then, we will understand that it is book smart. You can say that the test of intelligence was measuring only analytical intelligence. People having this type of intelligence are often called as book smarts. It is the ability to break down problems into component parts for problem solving and analytical thinking is required to solve problems and to judge the quality of ideas. What is creative intelligence? It is the ability to deal with new problems and generate innovative ideas and solutions. It is needed to use the ideas and their analysis in an effective way once every day life. What is the benefit that we are very educated but we are dying every day that we are not able to solve problems. So, practical intelligence is equally important. What is it called? Off and known as street smarts. It means that if we go anywhere in the street then we will not have any problem. Last but not least, successful intelligence. He wrote a book Successful Intelligence How Practical and Creative Intelligence Determine Success. I think it is the book of 95-97. I did not mention it in this book. Then, what did he write in this book? According to him, Successful Intelligence is more multi-faceted. It is multi-dimensional. We have a general intelligence and we will be successful. What is it called? Creativity, Adaptability, Practicality, Intellectual Risk Taking. We do not have to take risks. We have to take risks after thinking, thinking and calculation. Interpersonal Skills and Perseverance will be called Successful Intelligence. He had said that to be successful intelligence is to think well in three different ways. If we are able to think well analytically, creatively and practically, then we are successfully intelligent. Otherwise, only analytical intelligence is valued on tests and in the classroom. He also notes that intelligence is incremental. Our ability to learn grows with learning itself. What does it mean? What does it mean? What does it mean? What does it mean? Incremental. As much as we learn, our ability to learn increases. We can summarize that human intelligence is the cognitive ability to learn from experience to reason well correctly to remember important information that we can remember and to cope with the demands of daily living and if we are able to cope with the demands of daily living then we are intelligent. Mr. Sternberg is saying this. So I have completed a very important topic of Robert Sternberg's intelligence and I have tried that this topic will be understandable to you all. So thank you all and don't forget to like and subscribe my channel if you like this content and the way of understanding and to find this channel in telegram scan to join this type explore education and join my telegram group to get learning materials if you want ask your query there and you can provide feedback to me too there. Okay? Then compromise it.


Kevin, I guess what's been like the past couple of days, weeks I guess at this point outside of the facility with all of this stuff going on and now that you guys are back into the facility, how much different is your week of preparation as opposed to any other that you've had? Yeah, I mean, it was tough. Obviously, I mean, last week we kind of treated as, you know, as a bar week is what it was. But obviously, you know, going through the different emotions of, you know, guys getting tested positive, understand that it's affecting our teammates and their families and our families as well. But also trying to really stay engaged and trying to make sure that, hey, we don't really know where we're gonna play this week, next week, you know, watching all the comments and what other teams and players and coaches saying I ran a league about if we should forfeit games. So we definitely took, I took note of that for sure. But yeah, it was tough. But at the end of the day, man, I'm very excited and happy that we're back in the building today. They're seeing a couple of guys, you know, just showing up to the locker room and stuff like that. So it's fun, we're happy to be back and try to come here and focus on winning the ball game.  So yeah, that's gonna be different. So we're gonna have different protocols we're gonna have to go about. But at the end of the day, you know, we're not gonna make any excuses, man. We're gonna come here and focus on what we need to focus on and that's winning the ball game. Now, Jim. KB, what have you been able to do leading up to this game, you know, whether it's on Zoom meetings, watching film, you know, getting ready where you're not so far behind the eight ball as you hit the practice field today?  All this week, we've been doing Zoom meetings. Obviously haven't been able to work out anywhere other than, you know, my backyard and my house and my Peloton bike. But at the end of the day, you know, it is what it is. Like I said, I kind of treated last week as a bar week. I feel like my legs are fresh. I feel fresh. And I was excited. Just been trying to stay mentally locked in and I think that's gonna be the biggest thing heading to this game, making sure that we're all mentally on the same page. So when we go out there, we can play fast and aggressive. Tron. Yeah, KB, what are the next couple of days of preparation look like for you? Because I know you're a guy that likes to really hone in on details and see them. So how do the next couple of days look for you?  But like you said, man, that's why I'm so thankful to be back in the building today because honestly, I mean, I will speak from myself for sure. I know, you know, going to a game without any practice is not really being around the guys, not being able to, like you said, hone in on details, being on the field, at least for walkthroughs or something. It'd been tough. So to be back in the building, be able to do some different things with the guys, have the communications and stuff like that. It's gonna be really good for us. So that's gonna be main focus for the rest of the week, man, just hone in on details, getting back to talking to each other, communicating not just on Zoom means, but actually, you know, face to face with each other. So that's gonna be key. So I'm happy we're gonna be able to do that. Concealing your face when you talked about making a note of what other people have said, does that kind of make you guys dial in even more and become more focused? Like is that something that you could use just as another tool to hyper and intensify your focus? Yeah, most definitely. Because like I said, man, I've been obviously I've been doing them, but sitting at the house. So, you know, watching different stuff on the media, saying things about the team. And I mean, we obviously know, man, we're still in a pandemic. I mean, obviously the protocols that we had and that we have, they're not foolproof, but at the end of the day, they're supposed to help mitigate the risk and things like that. So, you know, to see a lot of the comments that I seen, you know, around the league, like I said, I took note of that for sure. And I'm definitely, it's definitely gonna motivate me for sure to let the guys know about what, you know, what people have been saying. I'm pretty sure they've seen it, what people have been saying about us as a team. I mean, at the end of the day, we're three and no. And, you know, we're trying to go four and no at the end of this week. Mike, you already? Hey, Kevin, I'm just curious if there's any, you know, looking back on the last 10 days and now with the league and the PA conducting investigations, if there's any, for lack of a better term any regret on gathering off-site from amongst some of your teammates?  Obviously, I wasn't really caught in investigation. I would say they're doing a review, you know, about, you know, the protocols and the stuff that we followed or not. So, you know, I really can't comment on that until, you know, that finish of that investigation. I know we've been fully transparent about everything we've done from the players to coaches and everybody. We all talk to the NFL. We all talk to the NFL PA and let them know about everything that's been going on the past 10 days. So, like I said, once the NFL make a comment, then I'm pretty sure, you know, we'll be back on here and I'll have a comment then. Emily? Hey, Kevin, how much, you know, responsibility do you take to get the guys mentally prepared at being in that leadership position? I know that Mike Rables spoke about the mental health component to all of this. How much are you checking in on guys and making sure they're doing well? Yeah, that was a big thing. You know, checking in with the guys. I mean, hopefully we'll be able to get some of the guys back for this game. I'm sure we won't be able to get everybody. I've checked on a couple of guys throughout the past 10 days. Some guys that I knew that tested positive. Just check on, just see how they was doing. See how they was feeling. You know, it was definitely tough, but as a leader on this team, now that we're back in the building, I do take responsibility to make sure that we're all really upbeat and we're positive. Obviously these aren't the best circumstances. We're not, you know, we're obviously, I wouldn't say we're at a disadvantage, but we're not in the same position as every other team in the league, which, you know, strict the protocols, not being able to practice the past two weeks. But, you know, at the end of the day, we're going to have to look, you know, look at the positive situation, happy that we're back and understand that, you know, every, we're not promised another opportunity. We're not promised another practice. We're not promised another game. So we got to take full advantage of every time, everything that we're doing and be really intentional about every single rep that we can get throughout this weekend for the rest of the season. Luke. Kevin, there's obviously a lot of momentum that comes with a three-and-oh start. And I would imagine at least some of that has maybe been derailed from all of this.  Yeah, I mean, they're definitely a physical bunch. We've played in the past two years and every single game has been physical. They've been close. Honestly, I would kind of look at, you know, in the NFL, I think every week is different. I don't think, you know, one momentum from one week pretty much carries on to the other. I think you had to build momentum throughout the week. And I think that's one of the main things we're going to have to do starting today, making sure that we're building that momentum as we get back on the field and kind of knocking the dust off a little bit, as I would say, as far as like the communication and a little small things about being on the field, getting our position specific drills in and stuff like that. So yeah, I mean, obviously, therefore, no, we're three-and-oh. Somebody has to have one loss at the end of this week and hopefully it won't be us. Kayla? They got mine, Robbie. I'm good. Terry? KB, you talked about being able to get back in the building and what that means for you. And in regards to the things that went on last week, it was maybe part of the impetus of thinking that that needed to happen in terms of getting together, done for the fact that simply the Steelers game was still on the schedule at the time and had it been moved? Like I said, I don't really have any comments on any off the field or out of the building facility workouts. Like I said, I mean, it's under review right now. So once we get some further information on that from the NFL, then I'll be able to comment on that. John? Yeah, Kevin, I hope this question is a little bit different than the last one, but just wondering about when everything shut down on the 29th, can you talk about your kind of mindset and maybe your teammate's kind of mindset again, knowing that you still felt at that point like there was gonna be a game coming up and kind of what your mindset was in terms of needing to be ready, I guess. Yeah, I mean, I think everybody's mindset after end, I guess, once they finally... So obviously once the first test, obviously, we were still supposed to be playing the game. And I think that was everybody's mindset until we wasn't gonna play. And after that, like I said, we treated as a bye week and I guess guys rest their body and stuff like that. And now we're here with the Bills. So like I said, as far as off the field and out of facility workouts, I guess I can't really comment on that, but other than that, we're here with the Bills, man. We're ready to play, really focused. We're trying to win a ball game and that's the main thing. Yeah, and along those lines, obviously we're gonna see some new faces and some guys with less experience, whether it's in your position group or otherwise, you tell them about what kind of opportunity this is for them that they might not get otherwise. Man, it's a huge opportunity. I think it's a huge opportunity for every single body on his team, the fact that we're back playing football, back to playing another NFL game. So I know we're blessed to do every single day that we come in this building. We always have the next man up mentality in this building, rather than at any position. And I don't think it's something that I had to really preach to a guy that may not play that much, that's gonna get their first opportunity to play. I think it's something they've been probably working for their whole entire life to be able to, if not start or get snaps in the NFL game. So I'm pretty sure they're gonna be thinking about that all week. So I don't think I really have to preach that too much. But at the end of the day, man, I'm gonna be happy for whoever's gone out there and play. We're gonna expect them to play at a high level and that's just what it's gonna be. Thank you. I got time for a couple more, Paul. Hey, B, has the league been fair? Do you feel the league has been fair up to this point while you guys have worked to be transparent?  So, yeah, I don't know. Like I said, when I was speaking on about comments that I've seen in the media or different teams or players and different stuff that I've been seeing, that's what I was talking about. But as far as the NFLPA, as far as their review and stuff like that, yeah, I mean, I think they're doing their due diligence is what they're supposed to do. You know, this is a serious matter as far as the pandemic and COVID-19. So I would definitely think that they're being fair. Kyle? Yeah, when you mentioned sort of taking note of things that have been said, using it as motivation, what was there one thing in particular that really kind of bothered you that someone said about you guys? Yeah, I mean, I'm willing to put nobody's name out. There are any teams or stuff like that, but you know, just certain comments about, you know, we should forfeit it. You know, just different comments like that kind of frustrated me because like I said, we're in a pandemic. This is something that I just believe that if you, if anybody went into the season thinking that, you know, there weren't gonna be a couple positive tests or outbreaks somewhere of all 32 teams, I think that was kind of foolish to think. I mean, obviously we're not trying, we wasn't trying to be the team that had the outbreak. We're not trying to get COVID-19.  But I definitely took note of that because I'm like, if it will happen to somebody else, you know, what people be saying the same thing. So. Last one, Jim. Okay, but you've had bi-weeks before. This is the first time you've had a situation in season where you've gone two weeks straight really without practice. And can you use momentum that you got to get to three and over? In a lot of ways, is it kind of like starting over? Yeah, man, I think you have to start all over. I think it's kind of like every single week you start your preparation, you start your routine all over again, and you build momentum for that week to get into the next game. I don't really think that, you know, from one week or to another, you really, you know, keep momentum going. It's all about going out there, trying to execute the best to your ability and doing what your coach to do throughout the week. Cause every game plan is different. Every week is different. The keys to the game is going to be different. The details to the game are going to be different. So yeah, I mean, that's going to be the man that gots to build a momentum as best as we can to get all the little details that we can about this game plan. And it's going out there and playing. I mean, obviously we haven't played in two weeks, but, you know, I think guys should be emptied up. I think we should be able to get some guys best, some guys should be fresh. So man, what you're going to go out there and give it our all. Hello, I missed one. Chris Harris, last one. Yeah, thanks. Hey, KB, just wondering what you think, you know, so you guys have made it two straight days now with no positive tests, but there's still three more days to go. And given what you went through last week, is it almost like we're not taking anything for granted and we'll just see what happens?  I think the only thing we can control is what we can control. And that's just by staying positive. Obviously it has been a lot of positive news the past 10 days. So the fact that we're back in the building, we're going to use that as, you know, as some positive things to focus on. And you know, whatever happens, happens.  But at the end of the day, man, I can only control what I can control is my energy today in the building, being positive and just trying to be a leader for the team.


So welcome everybody. It's a great pleasure to introduce Daniel Amor, who is a postdoc at MIT. Daniel is one of these brave physicists that has been trained in physics and then moved to do also experiments in biology and try to combine theory with experimental data. Then it started in Barcelona physics, and then these PhD in experimental sciences and sustainability in Giroa, and then after a postdoc with the consulate in Barcelona moved to MIT four years ago. And today is going to talk about how microbial communities responds to perturbations. So before I leave the floor to Daniel, I just want to remind the rules for these webinars. So there are no strong rules. You can typically, you can just unmute yourself and ask a question during the talk, if that's fine with Daniel. So just ask a question during the talk, we try to keep it as interactive as possible. So with that, thank you very much Daniel for accepting our presentation. Thank you Jacopo. It's a pleasure for me to give this seminar today and I'm looking forward to the discussions after a while. Before I begin, am I sharing the screen correctly? Is this the, are you now seeing my, okay, because yeah, it's, it doesn't appear as when we tried before, but if it's working, it's great. Okay. How do microbial communities respond to perturbations? I'm here today to speak about this question and I wanted to first begin by looking back at the first time in history in which this question made sense at all. And our story begins in France back in the 1860s. At the time they was, there was a huge crisis in the wine industry. And many, many bottles of wines were spoiled after storage. And it was so bad that Napoleon itself called repastor and asked him to find a solution for this problem. At the time repastors has already shown the world that fermentation was not the purely chemical process that everybody had in mind. Instead, tiny cells or tiny yeast cells were responsible for the fermentation of the precious alcohol. So this time he's facing the challenge of saving the wine industry. And for the first time in history, he takes a lot of samples of wine and starts looking at wine at the wine and under the microscope. And here's what he finds out. So it was usually easy for the winemakers to obtain the alcohol because from the group juice, the yeast that already were leaving in the skin of the grapes start their activity and they produce, they turn the sugars into alcohol. And after the fermentation, they naturally decrease their activity and when everything goes well, the wine can be stored and it will taste good for a long while. However, he also found out that in some cases one of the microbes that was already in the wine would take over after fermentation and will turn the wine into a sour wine. Or in other cases, it was another microbe that will turn it into a cloudy wine or a slimy wine. And for each of the different maladies of the wine, he was able to find a particular microbe that was causing that malady. That was already a great discovery at the time, but he obviously didn't stop there. He was looking for a way to prevent this. And he, after a lot of experiments, he found out that this was the best thing to do. It was a perturbation which consists in increasing the temperature of the wine just after the fermentation up to 50 degrees. When you do that, the abundance of the microbes in the wine goes down very significantly and it was enough to, in most of the cases, prevent the emergence of any of the maladies. So this was actually the origin of fermentation. Many of us might know, at least I thought before that fermentation started with milk, but actually it didn't. It started with wine and then it was transferred to other processes. But if we look at it from an ecological perspective, is one of the first cases in which somebody intentionally drive and engineer the state of a microbial community. So from the different stable states that the system could reach, Pasteur was directing it into the most desirable state, which is the good wine. And today we know already many different ways, the good ways of producing wine. However, when it comes to predicting the response of a complex microbial community to a perturbation, we are still pretty unsophisticated. So let me show you an example related to a complex community that is the microbial community living in our gut. So here we have a study in which the scientists were tracking the composition of the microbiome of a human individual. And the different lines shown groups of important taxa in this community. So what we see is that four weeks at the beginning, the composition of these groups is pretty stable. But one day this individual got an infection. I think it was Salmonella. And from this infection, you can see how one of the groups goes up because it's the pathogen belongs to this group. But then in a process of about two weeks, they was clear. However, in the during this process, there was an alteration of the abandon says of the other microbes that responded to this change in the community. And the study continues for many, many weeks after and we see that it reaches a different kind of stability. So the composition doesn't look the same as it was before the infection, but it suggests that it has reached a different stable state of the community. However, in these cases, the community is so complex, and we have so little control and limited ability to do experiments with the human gut community, obviously. So overall, it's very difficult to disentangle the mechanisms that are driving these transitions. And beyond human health, we have a huge problem nowadays with the human activities and climate change challenging our ecosystems. And in many cases, we know that ecosystems can also display alternative stable states. Some of these stable states are also linked to microbial activity and one good example is the one of lakes. So here we have a picture of a lake in its oligotrophic state in which the Newton concentration is low and the biodiversity is high. However, because of human activity, sometimes fertilizers come into the lake and after that phytoplankton can experience a bloom and consume all the oxygen, which will kill the fauna. So we have we transition into this undesired state that in which the biodiversity is very low and the nutrient concentration in this case is very high. So again, this is also an example of a stable state and the system shows some hysteresis here because once you once you reach this stable state is very difficult to come back to the previous one, even if you stop throwing more fertilizers into the lake. And there are many other examples such as in our coral reefs that are challenged by the increases in temperature and pH of the environment. And in ecology, many of much of the work has been done with a focus on microorganisms when we are talking about the effects of climate change. But given that microbial communities are at the very heart of many ecological functions and can support biodiversity. It is becoming more and more clear that it's necessary to also study the effects of these changes in the environment on microbial communities in different in our different ecosystems. So my research focus on studying how microbial communities respond to perturbations. And before I go into the specifics of the talk, I will just give you in a nutshell a scheme of how I usually approach this this my research. So natural ecosystems have a very high complexity. And usually this is correlated also with a very low controllability when you want to do experiments. And on the opposite side of a natural ecosystem, maybe the most simple ecosystem in which you have a lot of controllability that you can think about must be a test tube in which you put one or just a few species. And when you do these, in many cases, you are able to to study the interaction network between the species how they interact also with their environment. And, and you can really have a powerful, you can reach good predictions about what is driving the dynamics of the system. So this is how I usually start my experiments. And then once I learn about the simple system I increase the complexity of the network of interactions within the microbes, or even also in the environment. For example, more recently, I've been studying microbial communities inside a more the gut of a worm, which makes the environment to be more dynamic and more complex. So all of this research I do it in in constant feedback with theoretically driven hypothesis. So I will start with a simple model that tries to capture a specific phenomenon. Then I design an experiment to see if I can, I can observe this and depending on my observation. In many cases, I have to rethink my model because because it obviously you don't get it right at the first time. And so in. So, in order to apply these these approach to our research we see which is the usual approach that we take at the go lab at MIT. My background helped me quite a lot into this because I started my, my PhD in in biological physics with Joachim Ford at University of Girona, and there I was a study of biological invasions by doing reaction diffusion equations model for, for several populations like virus infecting a cell or, or trees expanding into a new territory. This background was very helpful when I joined Rikarsole, Rikarsoles lab, because there I started doing experiments for the, for the first time. It was very fun. I liked it a lot and we started to manipulate engineer some bacteria and manipulate their interactions so that we will see also what impact these interactions can have on the special patterns that they form when they are expanding into free space. So that's, that was just an actual of how I ended up at the go lab. And today I'm going to talk about my, my current research in, in a jet force lab. So for the rest of the talk, I'm going to focus on two research topics. The first one. I'm talking about how communities respond to perturbations. I'm going to focus on a biotic perturbation. So I'm going to alter the composition of the, of the community directly. I, I will show a remarkable case in which an, an invader can enter a community and induce a transition to one, an alternative stable state of the community, even in cases in which the invader is not able to survive this transition. And later I will focus on a different kind of perturbation specifically and a biotic perturbation in which we threatened this community with an antibiotic shock. And in this case, I will, I will be showing some ecological drivers that you can use to control the outcome of this antibiotic shock that might be, that might be threatening different ways, each of the species that we have there. Okay, so I'll begin and as, as I was saying, this is what I've done with Jeff Gore and my first experimental community is going to be made by this by stable pair of species in which I have a corino bacterium and a lactobacillus that are inhibiting each other. We have learned also that the mutual inhibition is given by an antagonistic interaction that these microbes have with the pH. So one of the microbes is increasing the pH, sorry, decreasing the pH which means increasing the proton concentration in the system. And when it does that, it's also benefiting from this change in the environment, while the other tries to increase the pH because a higher pH is beneficial for itself. So we can also see this when we culture these two microbes in isolation. So if you have a test tube with only the green species, you will see that the pH goes up and then it stays up. And these, and this helps this microbe to grow and, and live in good conditions. If you start with the orange microbe, you will see the pH to go down and the microbe is able to keep the pH at a low value. So now we move into the community. So what, what does this interaction do to these, to these microbes when we put them together. So my experiments are usually daily dilution based experiments. So I start by inoculating some microbes at a low density in fresh medium when, and then they can consume the nutrients and grow. And then grow to saturation and the next day I take a sample and I put them into fresh medium again. So we go into the cycles of growth and saturation and growth and saturation. So for this community, what I see is that when I start with a relatively high abundance of the orange microbe. You can overcompete is the green microbe and then take over the population. So the main interaction that you find here is the orange inhibiting the green. However, at a low initial relative abundance of the orange, we will see that its abundance goes down because the green microbe is taking over the system and therefore the dominating interaction is the green one inhibiting the orange one. So this by stability is actually robust to some degree of migration. So even if I put a low amount of fresh cells entering the system every day, the, the two stable states of the system do not change. In other words, I have a by stable community that now I can play with it and perturbing different ways to see how I can obtain transition from one to the other stable state. I was introducing earlier my first perturbation in which I'm going to focus on is going to be an invasion perturbation. So in one of the dilutions. In addition to the migrant cells I'm going to in inoculate a small amount of an invader cell as species that don't belong to this community. And when you do that, there are in ecology to classical outcomes that have been broadly described and one of them is the establishment of the invader. This happens when the invader is able to grow well and compete well with with the local community. And it leads to its establishment. In other words, it happens when the invader is a bad competitor compared to the local community and then it ends up going into extinction. And this is known as community resilience. In most of the cases it's assumed that if a community is resilient to an invader after the invader is extinct, you just return to the previous stable state. However, there's been a largely overlooked scenario in addition to these two, which is the case in which you have an unsuccessful invader. So it doesn't compete well and it's going to towards extinction. But during the time the invader remains in the community. It's affecting the interaction with the other two microbes. So at the end you could have a transition to the alternative stable state of the system. We have called the transit invader. And in now within our experiments about invasion perturbations, we were wondering whether we will find such a case. And actually we did. And it was very exciting for us. Let me show you this experiment in which we start with the orange micro dominate in the community in a stable way. We introduced pseudomonas chlorophyse as an invader, and we can see how pseudomonas goes up during the first hours. And by doing that, we also see an increase in the population of the green micro. And after just two cycles. Pseudomonas is reaching the extinction, but in, but the competition between the local microbes have totally changed. And at the end of the experiments we have observed a transition into the alternative stable state of the system. And now the population of the orange micro is very low. It means that we can see this invader as a perturbation that drive the system from one of its stable states to an alternative one, even if the invader did not survive. So here we wanted also to know about what will be the mechanisms driving this transition. At the beginning, I've told you that the orange micro have an interaction with the pH in which it's trying to increase the pH and benefiting from that. The opposite is true for the green micro which tries to, to, to, sorry, to increase the pH. I'm not sure if I said it well before, but basically this one increases proton concentration this one decreases proton concentration. And the interaction that the invader has with the pH is different. So this micro will benefit from a low pH. However, its metabolism is increasing the pH. And when we measure the pH during the invader experiment, what we observed is that the orange micro was keeping a low pH in the system. And right after we introduce the invader, we saw a dramatic shift in towards a high pH. And once it high pH, the green one was a better competitor than either of the other two. So here we have a mechanistic explanation for what happened to our simple experimental community. And our next question was, could we observe this in a more complex community. And driven by, by this motivation. I started a completely new set of experiments. And in here, what I, what I did is to take a soil sample from the yard that it's just in front of our lab. And I transferred this sample into our test tubes. And again, continue with this daily dilution. So even if there are many different species coming from the soil and I don't have too much control over them. When I did this experiment, I observed that for many different replicates, each line here, it's a different replicate. The community will go through an initial transient phase of some pH fluctuations, but eventually many communities, not all of them. Here are more or less 50% of the ones that I tried. And the other 50 were not stable at the end of this amount of cycles. But for this 50%, I could see how it looks like after a few days they have reached some stability. And when I looked at the composition of them, I could also observe that for each of the different pHs, I was obtaining a different community there. I'm going to focus now on this one in cream color and blue color here, because for this one, I, I performed the next experiment. I'm going to try to see if they are also stable states of the system by introducing some amount of migration between them. So I did this and I observed that even if in my daily dilutions, some of the cream microbes were coming into the blue community, the blue community didn't shift to the alternative stable states and vice versa. However, in the same conditions, I applied an invader to the, to the community with a lower pH. And it's the same invader as before with my experimental community. And what we can see is that after doing the course of a few cycles, the pH goes up and it stays in the range that is characteristic of the cream community. So not only this, but we sequence the community at the 16th level. And then we could, we could observe what was the composition of this community. And indeed it was, it was dominated by the bacillus genus during the first days. And then I introduced the invader. And this pseudomonas goes up and down. And after this, we can see how we have transitioned to a to an alternative community that it's in this case, governed by Pantoea. So here, again, I have this invader induces a transition to Anna towards an alternative stable state. And it's a good moment to summarize my first part of this talk. So I've been showing that environmentally mediated interactions are important drivers of community dynamics. Sorry. Yeah, yeah. There is a question by Matteo. Yeah, so. Oh, okay. I'm sorry. My speakers go off if there's no sound coming in a while. So I'm not sure how much time have you been. No, I wanted to ask a question first. Yes, I was about to say that it's a good moment for questions. So please go ahead. Yeah, so the last example are the communities homogeneous in the sense that are they dominated by a single species. Yes, that's that seems to be right. So, yes, so when I look at the composition of these communities in terms of colony morphologies and also where the different strains lead the pH for the blue community there's some heterogeneity. So I can see three different kinds of morphologies in in these bacillus strains. And some of them are more associated to a pH that it's around six. And the other ones more around four and a half or so. So there is some heterogeneity in this community. However, they are very close relatives because the 16 s sequence ended up being the same for all of them. And for the other micro as well so Panto is largely dominating this community. And I only have very, very low fractions of other species that include all of the other species that were in the soil community but they are, they are kept at very low levels. I have another question. Yeah, at time zero when you sort of have this invasion of pseudomonas. Do you also sort of put a little bit of Panto air or not. So, yes, yes, exactly. So this was done under this migration condition. So I, if I only do migration, this is the outcome. But if I do migration, in addition to the invader, then I observe this, this transition. Right.  So that's what I will expect. I don't remember if I ever did that experiment, but an alternative possibility could be that pseudomonas takes over. Right, because you could think that if there's no Panto air, the pseudomonas is able to overcompete the bacillus and then stay there. So I would say the one that drives Panto air could be the one that drives Panto air. So can I ask a question as long as we're in a question period. This is Simon. We presented an equilibrium view of communities but a standard view of ecological communities is that there's a successional process. Following a disturbance there might be early successional species that will come in and will influence the later development ultimately to be replaced and those species themselves could be initiating the disturbance. So what we're seeing here that the ones that are transforming we can think of as early successional species that are transforming the community. Yeah, I think that's right. That's also a way to to see it. If we will have like if for whatever reason this pseudomonas was not there from the beginning or or it cannot really change the environment in the way that it's supposed to until the bacillus is there. Then we stayed in one state of the community. Then this is as you as you are mentioning Simon, this is a case in which we have a succession and this succession is allowed by this invader that engineers the environment. Thank you. So I was about to summarize. I think the question have helped into that so basically I've shown that these microbes. In general microbes can interact with their environment so that they change the environmental conditions and this has a feedback into the behavior of the micro itself and it's an important driver of community dynamics. As a remarkable example of this I have been showing this case of the transit invader who switches the community from one stable state to another one out surviving the transition. And now I'm going to go into the second, the second part of the of my talk. So, as, as I was introducing earlier invasions is not the only way in which community can ship from one stable state to another. The many other perturbations are also interesting in the case of microbial communities. Antibiotics are especially interesting one for for the obvious biomedical applications. So, before I go into what I did experimentally, let's see about what kind of problems are we facing. So, here, if we think about a complex community, such as the one inhabiting in our, in our gut. So, the, the human gut microbiome. We can see that there are many factors that can influence the state in which the community is. So, here, we can think about the reasonably diverse community that inhabits the gut and, and the diversity and the state of it is going to be determined by different factors such as diet and species coming into the diet and whether you have functional redundancy or not. And then many other host factors such as the age and the environment of the factor of the of the host story. So in these cases to these complex communities in many cases we are applying an antibiotic therapy. And when this happens as a collateral damage from the antibiotic the God suffers and and and we can see a decrease in the diversity of the microbes. So some of these microbes will just go extinct. And others could start dominating the community either during that time or afterward. So in these different phases before doing an antibiotic and after an antibiotic there are all these different factors that can contribute to whether the final community can recover to the previous state. Or it goes into a different one and having a different state in this case can change the function of the community so have an impact on so in the health of the of the host. But, but again given the complexity of the system is difficult to to find a specific mechanisms that that can help us to predict in which cases some patients do not recover and in which cases the patient will recover the previous gut health that they had. So at the heart of this problem is that the research on antibiotics has mainly be driven by studies on single species instead of communities. So when you are trying to test an antibiotic you usually have a pathogen or specific species in mind. What you try is to see if these species is susceptible to the antibiotic. So here is how here's a minimum inhibitory concentration has a that it's the usual tool to assess susceptibility. So what you do is you start with with an inoculum of microbes in test tubes, and you have a gradient of the concentration of the antibiotic. So that you will wait for a little bit of time and you see in which conditions they the microbes growing in which don't. And in this case we have seen that this one here is the minimum in minimum inhibitory concentration so here is the concentrations at which the microbes were already not able to to grow. And the antibiotics the microbes here can just no grow, not grow, or they can also experience death, but this doesn't change you assess the susceptibility of this micro. Even that this is the most usual tool, a classical hypothesis to try to predict what will happen to the community is that the more susceptible species maybe they are going to experience the harshest consequences from from an antibiotic exposure. But of course in ecology, we know that resilience against perturbation is is driven by many different factors. For example, here I'm showing this cartoon in which I have a community with different microbes and and there are signs of by stability, but these these by stability can be shaped by ecological conditions. Ecological factors such as the pH as I was showing before, but also temperature or nutrient availability, even migration so the amount of new cells that enter the community per unit time. And such factors can influence both the shape of the stability landscape and how deep are the valleys of stability, but also resilience which is how strong a perturbation can be and the system will still recover the previous stable state when you remove the perturbation. So in order to assess this interplay between ecological drivers and the susceptibility to antibiotics. I went back to my experimental community. And I started by assessing the susceptibility of my two microbes. So I did this minimum inhibitory concentration, I say, and I observe that the green microbe was more susceptible to the antibiotic. And we can see here that the minimum inhibitory concentration to stop growth of the green microbe is much lower than the than the orange. So based on this, if you make this classical hypothesis, you will see Oh, well, maybe then the orange microbe is going to display the more resilient state. So I started then. Yes. In this case, when you say resilient, you mean what is the basic of attraction. So depending on the initial condition. I mean, how wide is the set of initial condition for which you go to the tractor with the orange species, or you mean how fast you go back to the tractor. I mean, yeah, in this case is for now it's going to be more like a binary thing, whether the stable state will return to the original composition or not. So, actually, I'm going to, I'm going to be talking about relatively hard or strong antibiotic perturbations, but more like my, my current experiments are studying about the resilience in this in this kind of sense about. Okay, now if I vary the strength of the perturbation of the antibiotic what's going to what's going to happen, but for now I'm just going to make a case for for relatively strong antibiotic perturbation and whether the community is resilient or not in terms of whether we observe a transition or not in the stable states. So we, from here, we were predicting that maybe the stable state dominated by this more susceptible species will be will be less resilient to the to the antibiotic shock but what I observed in doing this experiment in which the community starts in the green in the stable state dominated by the green species. And one day I transfer it into the antibiotic and I see how this is harming the community. Then I remove the antibiotic and I let them recover. I see that the green one comes back and dominates the system again. So in this case the this state is resilient to this antibiotic shock. And when I did the same starting from the alternative stable state dominated by the orange one I applied a perturbation. And when I leave them recover what I see is that the green is taken over and eventually over competing the green micro. So somehow these these goals against a classical hypothesis based on just the susceptibility. And in order to try to understand this better we we began by by starting a simple model that maybe could capture what's happening in our community. In particular, I started with a modified version of the load couple terror model. And here I have two species. I'm I call them F and S because of reasons that will become apparent later and for each species. So species F has a growth rate are F and it experienced logistic growth so the saturation of growth at high densities. And there's also another term for the interaction between the species. So the species S is inhibiting the species F and vice versa. To better capture the dynamics in my experiments we have a constant migration rate which is the same for both species and the death rate that it's going to be applied during for only for a fraction of time. And this will be an antibiotic associated growth rate. So what it means is that the death rate is going to be zero until I apply the antibiotic in which I'm going to have different growth rates. And in particular I'm going to consider that the green one is more susceptible to the grad and the death rate is is higher for this one. And after the antibiotic we go and after the shot we go down to zero death rate again. So if everything else is equal between these two species then the classical hypothesis will work here because you can state with the green one dominating the system and you apply the perturbation which starts killing the microbes. But then after the perturbation the orange one wins the competition against the green one which has been more harsh more harmed by the antibiotic shock. Alternatively we can consider what you will expect in general in microbial communities and it's that you have different growth rates. So now I'm going to consider that F has a faster growth rate than S and if you do that in the same conditions that before then what you can observe is the opposite. So even if you start with the less susceptible species dominating you apply the antibiotic shock which reduces the population abundances. But then after this the green micro can grow faster than the other one and end up dominating the community. So this led me to the question of whether this will be consistent which where what I was observing in my experiment. So is it the green micro really growing faster than the other. And if so we could make a prediction that these should work for many different kinds of antibiotics because it looks like the importance of the growth rates can override the importance of the susceptibility so it's not about one particular antibiotic. So now I went back into the lab and I measure growth rates in several replicates and actually we observe that the green micro was a faster grower so this was looking good. But then I also tried many different antibiotics. And in most of the case in most of the cases the green one was always was most more susceptible when when doing this minimum inhibitory concentration assays in isolation. But when I perturb them in communities. I also see that the transitions were usually going towards the green micro with with a few exceptions. So this is an indication that the simple model could be capturing what is happening to this community. So here again is a good moment for questions. This this should be a takeaway message that the first growth increases the resilience against antibiotic shocks in a community context. And if if that was enough, this should be the thing to remember from the second part of the talk. So if you are still with me for five more minutes I will show you how migration can also tune these growth rates and hence the the antibiotic response. Is there any questions so far. Okay. So, when I was measuring the growth rates I also observed that my that the green micro was a beating some signatures of cooperative growth. And that is that for different initial cell densities, I will observe a different growth rate for the green micro while the orange micro was mostly growing at the same growth rate no matter the initial density. In the model this is usually captured by applying an effect which which consists in an additional term into the growth rate of the micro in this case the fast micro the fast grower. And this Ali effect. When we use this form of the Ali effect what we see is that capital growth rate will grow, but then, sorry, go down as you go down in the initial population density before comparison the the orange micro is it's experiencing only logistic growth here. And this happens when we introduce these into our into our theoretical model. So, before we were in the absence of couple of these was my modified set of equations for the lot capital terrible model. And what I'm showing here is how the basing structures are for the for the two stable. Wherever you start in this initial population density range, you will end up with the green one dominating in this in this region of the face space. However, if you if you go into a higher initial abundance of the orange one then you can reach a stable state dominated by the orange. And I'm showing here, it's a, it's an example of a perturbation an antibiotic that it's harming both of the species at the same rate. So depending on whether this is the case or not you will have different inclinations of the arrow. But here, if you are in the stable state you freedom, the microbial community in this way, then you leave them recovery, and it could come back to the initial stable state. If the perturbation is harsher, then there is a risk of crossing the, the interface be two basings of attraction and then is when you can observe the transition towards the green one dominating. So how this changes when you have Ali effects. So if we draw the same phases space here, we will see how these is boundary between the two phases curves in a different way. And now the basing of attraction of the orange microbe is much bigger than the, the one for the green microbe. So we have this prediction that cooperative growth can change the resilience of alternative stable states. And the next question is, could I apply this to observing my system, a change in the direction of these transitions. And the answer could it look like that like the answer could be finding the migration, because migration establishes a floor in the population densities. So let's imagine a harsh perturbation of the antibiotics so only a few cells survive, and then I dilute them into fresh nutrients but I also have some amount of migrants that are going to come and they are going to be responsible as well for the repopulation of the system. If I increase migration, even if the rates of migration that the fraction of the migrants are the same for both the species, we will have a higher initial population density right after the shock. And given the cooperative growth of the green species, it could this could have an effect on the on the difference in growth rates between the two of them. And after doing this analysis I realized that I my migration grade will set up a floor in the population densities that was more or less over here. So the prediction was that maybe if we load a duration rate we will reduce the difference in the initial growth rates after the antibiotics and maybe for many antibiotics we will observe a transition in the opposite direction. Sorry. Yes. So what you're saying is when migration sets the floor of population density and observe only effect I need to be at a small enough population. And therefore I see that effect if I have a low enough migration. Is that what you're saying. Excuse me, I didn't hear well the second part of the question. I mean, what I don't understand is how these. I mean, what is the connection between migration and right. Okay, so imagine. Let's imagine an extreme case in which the the the antibiotic is killing the whole population is that's the extreme. And then what happens the next day is that you don't transfer any cell from here. But there is the migration rate that so some cells will come into the system because of the migration rate. If the total migration rate is low. Then you will have an initial population density that maybe it's around here. So you have this growth rate for one species this growth rate for the other. So if you increase the migration rate a little bit, maybe you are going to start from here, or from here. And this is going to change. I was trying to understand that in terms of the parameters of the model with the effect. So what you're saying is that you should compare the migration rate with a with, which appears in this. Yes, yes, that's right. If the migration rate is more than enough, then you are, you can see the effect of the effect. If it is large enough, you are already above. Yes, yes, you're right. Yeah. Exactly. Yeah, yeah, yeah, the migration rate will set up where you are in this score if you. Yeah. Yeah. Okay, so the last thing to check was whether we could lower the migration rate and and see if this had an effect on the reaction of the community to antibiotics. And just a reminder, when I was in my original migration rate, which now I'm going to call the high migration, great condition. The orange microbe was able to sorry, the green microbe was always able to take over the community after an antibiotic shock, no matter which state I begin with. So high migration means that you have transitions towards the green microbe dominating the system. Now I did the same experiments at a low migration rate. And we actually observed a transition towards the orange microbe. So I begin with the green one. I applied a perturbation. The migration rate is low. So the green microbe is a still a faster grower, but the difference is lower. And we have to take into account also the inhibitor interactions between them. So these allows the microbe the orange microbe to over compete. It's the other species. We also observed that if you start with the orange microbe dominating the system, you end up with the orange dominating the system. So this not only happened for one antibiotic, but for many of them. So when I, when I lower the migration rate and I apply different antibiotics to this community, I will observe transitions predominantly going to the orange microbe. Or in some cases, both the stable states remain resilient to to the to the perturbation. So no changes. But if I apply a higher migration rate, then I'm going preferentially to the green microbe. Sorry, can I ask a question? Yeah, so I see error bars on your plot. So you are averaging on different realizations. So yeah, these experiments. So three, three different experiments for each of the blocks. But in all of three in all of them you observe the same outcome or can you observe also metastable outcome? So for the ones that I'm plotting here, I always observe the same outcome. I do not observe metastable outcomes in the long term. If metastable means that none of them is going to dominate and they are going to exist more or less of the same fraction. What I can observe, depending on the on the strength of the perturbation, because if the perturbation is very weak and you only put a little bit of antibiotic, then this is not going to do anything to the microbe. So you at some range, you don't observe transitions and then you start observing transitions and I'm showing that the migration rate can also reverse the direction of these transitions going to the green or going to the orange. So when you are in experimental parameters that are in between this decision, sometimes I observe that that if I do three replicates, one will go in one direction and two will go in the other direction. Okay. But it's just for very small ranges of parameters. Thanks. And yeah, so this this was all just to summarize, I was showing how environmentally mediated interactions can be an important driver for community dynamics. And then this can lead to remarkable dynamics such as the one from the transit invader who induces a switch from one stable state of the community to an alternative one. And we could, in this case by studying simple communities in the lab, isolate specific mechanisms that can drive this transition. And, and finally, beyond this environmentally mediated. There are also other ecological drivers that we could study more in depth and exploit to control the outcome of microbial communities after perturbation suggest antibiotic shock. And with this, yes, and, and as I was mentioning to Jacob or right now the second part of my talk is ongoing work and what I'm doing right now is going into these regions of parameters in which the different factors are more equilibrated in their impact. So what what happens, the susceptibility is more or less as important as the difference in growth rate, for example. And with this, I would like just to thank you. Thank you, my, thank you, Jeff, which is my, my current advisor, but also my previous advisors, from which I learned a lot from all of them, and my, my colleagues and collaborators Christof who is an author in in the paper about the transient invader and many other friends that are helping me very in my everyday life, like Martina and Jonathan Friedman and many others. That I would like to thank question to answer any questions that you may have. Thank you. So we have time for a few questions. Yeah, I have one question. Yeah, on the first experiment. So you said that the mechanistic interpretation for why the invaders shifts the community to the other stable state is that the invader increases the pH. So I was wondering if you tried just to change the pH in the community without putting the invader and seeing if it has the same effect. Yeah, yeah, we did that in and it has exactly the same effect with with the pH you can control in an intuitive way where you drive the community so low pH you go to one micro dominating and high pH shock and you get the other one. Hello. Hi. Another question is not directly related to your talk but just want to know if there are studies on if you control the new trends, like in a periodic way, that's kind of more like what we do daily know with the food coming in and so on. If we go if we change this hours for example making irregular or even with some fasting period. What would be your prediction, whether it's going to be a significant change in the composition of the microbiota or you know, and maybe it's two general question but I want to know, you know, no, no, it's Yeah, it's a it's a good question. I'm thinking about the impact so my view of the the effects that new has on microbial communities. Usually, I think that a higher nutrient availability increases the competition strength between the species. So when you, when you have a lower availability to nutrients, the microbes not only might grow slower, but also they some of them might be lacking some nutrients. So they relay on on mutualisms. So one micro would be using this chemical that they cannot find in the environment. You increase the nutrients and the nutrient availability and then you remove these dependencies because they just take it from the environment. And now they are just competing to grow and overtake the system. So, instead of changing the concentration if you change the timing of it. Yeah, I think it's going to depend as well as what happens once you reach some saturation and some of them might be secreting toxins that are bad for the others. So it definitely changes the, it definitely changes the composition and the stability. But I wouldn't be able in an abstract way to say in which, in which direction specifically it's going to. But if we have sufficient understanding, it may kind of design some, some schedule, right, for people who like to eat, but then they worry about getting fat and so on. And, and I think that in it can help to do it for particular sets of particular sets of communities or. Okay, thank you. Any other questions. Yeah, so I'm wondering to what extent in such a simple system, one can validate theoretical models. So, so for example, when you can describe this with this as an evolutionary game. You can write down a question so the question is, can you really estimate the utility functions of the different bacteria in this evolutionary game, at least to test whether this paradigm in a simple system is really what is going on. Yeah, so my answer will be that with simple communities, we are reaching the state in which we can really quantify much of, of ecological and evolutionary drivers there. So here I haven't shown it, but, but these, these phases space of the two stable states and the, and the basing of attraction for the two stable space. That's something that you that I have studied experimentally so you can really tune the range of initial concentrations of the two microbes and you really have in one experimental play you will actually see, because you have the different population densities by each micro you really see that there is the, the separate tricks there in your in your actual experimental play. And in, in these cases when you have two or three or four microbes that you have previously studied really well in the lab. The ability that we have right now to ask a quantitative question and go and measure it. That's very high, and the challenge right now is to go into more complex communities so more than, yeah, more than five species or even going into comparing these two to a soil community for example in which the initial number of species is astonishing. Does that answer your question. No, yes, no. I mean, the issue is that if you can validate models in this simple system, maybe then you can think that you can study models with many species. Also from theoretical point of view, I mean, extended. So, for example, with one of the grad students at the core lab right now, we are taking this approach in which we start with complex communities. And the model is based on on statistical physics tools so now you, you start thinking about about the, the community as if you could average the properties of the different species and predict what's going to be the abundance of the average species in the system, right. So this is kind of going a step forward. I'm, we are not able to predict there what happens to one particular species. But when we look at the statistical properties of the community we are finding very promising and and compelling results about how can we apply these different modeling tools to to our communities in the lab. Thanks. Great. Is there any other question. Hi, can I ask a question. Yes, please. I will first introduce myself briefly I'm she and recent graduate from geosciences Princeton University but I will start a post-op position with Alvaro Sanchez, who was in your current lab. And sorry if I crash the seminar today, but it's a very interesting seminar and I wasn't thinking about these problems. So I have a kind of a basic question which is what is, when can you call a microbial community stable. Like, I thought stable community means that if there are some perturbations they can still remains the same, but it seems that you're talking about adding somewhat stronger perturbation so the microbial community community shift. So I was thinking is there a way to, like, is a barrier criteria to tell us what is a stable community. In my experiences. Yeah, thank you for your question in my experiences. There is always a matter of definition. So what do you mean by stability one and resilience and it can change from study to study in my case here. Well, first I, my approach is that if you go into very, very strong perturbations no community are going to be stable. Right. So there's always a limit. So because of that, I understand stability as a relative consistency or persistence of population abundances and ecological functions. And, and the resilience is how much how strong the perturbations. Yeah. The resilience is related to the strength of the perturbation that this the community can endure without without experiencing a change in the in the stable state in which they are. Is that answering your question. Yeah, thank you. So it's more of a relative. Yes, I think it's always going to be a little bit relative, but we can learn once you define and what you mean. And yeah, was you define what you mean by it, then we can learn about about these concepts. I think it's time to thank again, for getting the seminar.