 Good afternoon, and thank you for coming out to, I believe it's the first Burak lecture of the season, academic year, in a brand new facility. So thanks to the business school for allowing us to use the space. I also want to thank the president's office and Susan Davis, and in particular Susan who's still here. I highly recommend using the Burak lectures to bring folks like Mark LaBelle, caliber of Mark LaBelle, into town. Very, very helpful and we're thrilled. Also, so thank yous to my co-conspirators in bringing Mark here, Asensia over in community development and applied economics, and Meredith Niles in nutrition and food science program. They've both been really, really helpful in helping to craft Mark's visit. And Meredith and Mark go way back at UC Davis and it's been great to rekindle those connections. Also thanks to the Gund Institute for cosponsoring this to my own department of community development and applied economics. The office vice president for research, he's very much supportive of water research, and all the colleagues who have met with Mark over the last two days, and those who are going to mix and mingle with him later tonight. So following Mark's talk, we will be having a reception just outside the doors here. We invite you to stay around. There will be some question and answer periods, so please also stick around for that, feel free to come with your questions. So today's speaker is a real leader in the field of water governance, water governance research. We all know with the specter of climate change, political conflicts, increasing resource scarcity, conflict over water, water use, water quality, water quantity are ever present, aren't ever present challenge and will only likely continue to do so. So how are we going to govern our way through these challenges as we face the changing dynamics of the changing climate and ever evolving political systems? He's currently a professor and vice chair of the Department of Environmental Science and Policy of the University of California, Davis. He's also the director of the Center for Environmental Policy and Behavior. He possesses his PhD in political science from SUNY Stony Brook, so he's East Coast trend. It's a credit form. Mark, even though he looks like a young guy, he's prolific. He's authored or co-authored over 90 articles in peer-reviewed journals. His work has appeared in such high caliber journals as the College in Society, Journal of Environmental Management, Public Administration Review, Governments, Behavior, Water, Proceedings of the National Academy of Sciences, Global Environmental Change, Plus One, Society, Natural Resources, and the list does go on. His research has been funded by the National Science Foundation through many grants, as well as the USDA, as well as the State of California. So a lot of Mark's work, as he's going to talk about today, is done in partnership with collaborators with stakeholders. So it's a real action agenda. As you assume, many national leadership roles advancing policy, network, and environmental management topics within the field of political science is real, I would say, I would argue, is probably the foremost environmental, next to Bob Barton, environmental policy, particularly in water in the political science field. He sits on the editorial boards of such journals as Society, Natural Resources, Public Administration Review, Behavioral Science and Policy, and the International Journal of Blogger Governance. You're going to see all of those threads in today's talk. He teaches courses regularly on some topics, obviously politics and policy, land use management, public lands management, and also is developing courses in social ecological systems. And that's another area where Mark is at the vanguard of. He's helping us think about how to analyze and model social ecological systems. In his own words, Mark's work, as you'll hear, is about cooperation. It's the study of cooperation problems and decision making and environmental, agriculture, and public policy. Many of us are probably likely familiar with the tragedy of commons issues that I think drives a lot of Mark's work. He views these cooperation problems as the causes of many, many environmental conflicts. The largest areas that Mark's contributions have been the area of theory advancement in the concept of ecology of games as well as the idea of integrated water resource management. These are two keystone theoretical frames that really guide water governance as well as environmental governance in general. And his breadth in where he applies his empirical research extends to flood hazard mitigation, plant disease, transportation behavior, invasive species, among others. Methodologically, Mark is one of the leading users and employers of social network analysis, a lot of which you're going to hear about today as it applies to water governance. In addition to all that, Mark is a renaissance man. He plays a mean guitar, I'm told. He's been in bluegrass, but he's phased out of that because it's not electric. So he's in a funk band called Funk Defied. Well actually, it's changed now. It's changed. It's in the following band. But if you're around the Bay Area, look them up that way. I can also vouch for he's an avid fisherman, outdoorsman, soccer player, probably a swell dad too, I'm sure. We just thank Mark for taking the time out and engaging us in this talk. So without further ado, Mark, let's go. That's a very kind introduction. Thank you very much. I feel like I should put up the YouTube videos of our band and just let it be done with. We don't have to talk about water governance. But thanks very much for the invitation. It's been a very fun visit so far. I've been very impressed with lots of different things that are happening here at University of Vermont. A very interdisciplinary environment makes me feel like I'm at home at Davis from that perspective. So as Chris mentioned, I basically focus in my research on the evolution of cooperation and how you solve cooperation problems in the context of environmental governance and water governance is where a lot of my research has been done. And in particular, what I've been working on in the past about a decade now, the 2013 was where the paper that I published that laid out the theory of the Ecology of Gains framework is how cooperation evolves in the context of really complex governance systems where you have lots of different collective action problems, lots of different actors, lots of different policy venues in which decisions are being made. And I've done a lot of my work in California, but you're going to see some comparative work here in a second. So let me just kind of motivate this with California. This is the San Francisco Bay Area of California and the Delta. Here's the Delta. Here's San Francisco Bay itself. Golden Gate Bridge is here. There's nine counties in this Bay Area that I've done a lot of work on and this is just the map of it. This program here is called Integrated Regional Water Management which has been one of California's flagship programs for trying to get actors to cooperate together in the context of water management in the Bay Area. This is the San Francisco Bay Joint Venture. Another partnership, this one spearheaded by the U.S. Fish and Wildlife Service about how to get waterfowl habitat back in place and restored on the Pacific Flyway because California has lost 90% of its wetlands, the Bay Area, and it was a big part of that. So these little dots here are different project areas for that. This is another one called the Baylands Ecosystem Habitat Goals Project that tries to figure out what are the different kind of wetlands and coastal areas and how to restore them and what values they represent. This is at a smaller scale, the Sonoma Creek TMDL. TMDL, you guys know that well because there's a big fight about those at Lake Champlain, total maximum daily load program. This one's for sediment in Sonoma Creek which feeds into the Bay and then you get another program that's trying to get stakeholders to work together to solve an environmental problem. Alameda County Art Project. This is a more recent one that focuses on adapting to rising tides. That's what art stands for and how to deal with impending sea level rise and coastal flooding is already happening. The infrastructure to put in place, what are the vulnerabilities, how do you deal with disadvantaged communities and that sort of thing. This is the South Bay Pond Restoration Project which is mostly U.S. Fish and Wildlife Service Project because there's some national wildlife refugees down here and these were salt ponds that during the Gold Rush were used to mine salt and as you can imagine they're pretty much destroyed the wetlands there and you're trying to restore those. So what is that? That's six different collaborative partnerships all in one geography at different scales. So one of the studies that I did which I'll show you some of the results of I went out and found as many stakeholders in the San Francisco Bay as I could and asked who were involved with water management. I asked them to identify the core projects slash policy venues that they were involved with. They could name up to three. So I had about 300 stakeholders answer this. They named things like Sonoma Creek TMDL, IRWM and stuff like that. How many total water management policy venues do you think I discovered through that process? There's six here. How many total do you think I discovered? This is an audience participation part. It's kind of like Jeopardy or something like that. You don't have to answer it in the form of a question though. So how many total projects do you think I discovered? 70. Higher. 100. Lower. 120-ish. Yeah. Over 100 different projects at different scales in which people are collectively getting together to try to understand, to try to deal with water management. Most of policy analysis in my view up to this point basically would take one of these things and say how effective is this TMDL? How effective is this project or that project getting cooperation? The whole point of my research in the ecology games framework and really what I've been studying at this level has been to how to understand how that system operates. How the cooperation and learning and distribution and fairness works across that entire system. So if you leave right now from this talk and you leave with the point that we need to be studying the entire system and its structure and function and dynamics over time, I will feel I have succeeded in delivering the message here because that is to me like the major challenge of what we need to be studying and researching and communicating with stakeholders around water governance because when you go out in the real world and look at these systems, they all look like this. You will not find, in my opinion, if you do find a system which has only one policy venue in it at a place in a region, come tell me because I'd like to know about it. If you start thinking about this in this way, wherever you go, you are going to start seeing systems like this and hopefully be convinced you should be studying in this way because I'll tell you, I'm going to do a little bit more on telling you about the structure and function of these systems but we need a heck of a lot more research to understand what is going on. Okay, so that's really the reality, right? The reality of these systems is that they're messy, they're polycentric, they're fragmented, they're complex adaptive systems, they're multi-levels with cross-scale interactions, they have all these multiple actors and institutions. This, policymakers realize this, this is a quote from Phil Eisenberg, one of the leading former mayor of Sacramento, chair of the Delta Stewardship Council, one of the leading water policy practitioners in the history of California and one of the most interesting ones, in my opinion. This is his response to one of our papers in public administration review. Public policy is always a mess, it's acknowledging and enabling how to figure out how to manage a messy situation. They are always messy. Democracy creates messes of this sort and we need to figure out how to manage them and then this is Eleanor Ostrom in her Nobel Prize address from a theoretical perspective to explain the world of interactions and outcomes occurring at multiple levels. We have to be willing to deal with complexity instead of rejecting it. That's what I'm trying to do here. So I kind of view Ostrom throwing down the theoretical gauntlet here and this type of work trying to pick that up and carrying it forward to deal jointly with the practical and the theoretical issues there. Okay, I'm not going to spend a lot of time on this but this is from the 2013 framework that says the Ecology of Games framework. That's the theoretical framework that I evolved from an old sociologist paper, a guy named Norton Long who talked about it in the context of urban. So I did not coin this term but I kind of updated the framework by integrating it with some other things and it talks about how multiple actors might be involved with different policy institutions. So this would be like a TMDL or IRWM or whatever it is that you're looking at and you're like the Lake Champlain TMDL and then multiple collective action problems. This could be water supply, water quality, invasive species, how they're all linked together. And so you can read the paper to get into depth about how this is all put together. This is kind of a conceptual framework. Within these systems I think there's three core processes that we need to be paying attention to and I would submit to you that what I like about this is only three. I don't want to deal with a whole bunch of things. I want to deal with three. I think this is in any complex governance system, possibly complex societies. These are the three key ones. How people learn about what are the nature of the problems? What are the nature of the solutions? And importantly from a political perspective, what are the preferences of the other actors involved? What are they doing? Then how do you cooperate with each other both at the policy level coming to agreement about different policies and how implement them at the resource use level about how to use resources without and avoid the tragedy of the commons? And then another one that's really important is distributional fairness and procedural fairness thinking about the equity of those outcomes because in any society where you have to think about the use of resources, if you don't have some fair use of resources or some notion of equity driving that, eventually that society is likely to run into some serious problems. And this is where a lot of the political power and bargaining aspect is happening which has long been a criticism of Ostrone's framework of not being able to effectively deal with that. I think that's where it comes in here. All right, so now I'm going to report the results of some studies and a few of the core hypotheses that we've focused on and we've done it comparatively in a number of different systems. So this is the San Francisco Bay and I've basically spearheaded those with some surveys of stakeholders in 2012-2014. The same survey was rolled out in Tampa Bay, Florida in two years and the Paraná River Estuary in Argentina, Uruguay with this is Romero Barado at Ohio State. This is my old advisor, John Schultz, who made me study taxes at first and I said the environment's cooler and he studied the environment ever after. And this is Jack Muherter, who's a University of Ohio Cincinnati or University of Cincinnati. I've always forgotten the name of that one, sorry, Jack. And then this is Matt Hamilton, a former PhD student. He took the framework and the survey and adapted it to the context of climate adaptation in Lake Victoria in Africa. So I'm going to show you results from all of those different comparative sites. And in case you didn't think that this is an exportable framework, it's not just about water governance. It's about any sort of complex policy system where there's complex institutional arrangements. So my favorite and most exotic in a sense, extension of the system has been the application to the Norwegian handball talent development. So you see the ecology of games, a case study of Norwegian handball, which might be more fun than water governance, I don't know. It looks kind of difficult. And so this is from their app, there's a need for well-developed coordination mechanisms. So the same things are happening in such diverse locations. Water governance, education, health, climate change, Norwegian handball, food systems. You'll find this issue in all of them. We need to be studying. So here's all the hypotheses that I'll be trying to get through. Complex policy systems have structures for cooperation and learning from a network perspective. I'll get to that. How they change in response to new problems, the dynamics depends on their capacity and the sorts of constraints that they have on central versus decentralized authority. There's this idea of institutional externalities, which is like if you make a decision in one institution, it may have a positive or negative effect on your capacity to get things done in another one. Institutions co-evolved cooperation. So we show that if two actors participate in the same policy form, they are also likely to cooperate. But it depends on the nature of the form, the scale at which it operates. And then on the performance of the system, there's different variables that are linked to that that have kind of a transaction cost perspective, which is the idea of transaction cost is that when you're cooperating, you have to overcome the cost of discovering the solutions that you might cooperate on, the bargaining over the distribution of the benefits and costs, and then monitoring and enforcing the resulting agreements. Okay, so let's start with the first one about the structure. I have to get to this. I have to get a little bit of a detour into policy network analysis. So in policy network analysis, network analysis is basically about nodes and links. So you have some actors or different types of entities which are linked via some social relationship. So if I was dealing with what's called a one-mode network, I'd like ask everybody in this room who collaborates with who or who sends money to who and we'd have an actor-to-actor network. But you can also study what are called bipartite networks or two-mode networks, which is what we're studying here, where you have actors, these could be policy actors, all the state agencies, local governments, NGOs, whatever participating in one of all those 120-so policy institutions that I found. And then in what one of the classic approaches to network analysis is to say within these networks, as we measure them, you're going to look for structural configurations that are the fingerprint of some type of social process. And one of the really common ones is that you have so-called closed network structures, which are here, two actors participating in the same institution. So this would be like me and Chris going to lots of the same conferences together. And if we go to lots of the same conferences together, we're likely to form a bond with each other. And if Chris behaves really badly at a conference, I can see it and tell other people. So there's like, or if he behaves well, you know, then I can, there's a reputation management thing that can go on and monitoring that can go on to help people cooperate. And then these are more open network structures where you have actors participating in, lots of actors participating in a single institution or lots of institutions singled around one actor. And that's like a coordination point. So they're open. There's not a lot of non-redundant information happening there. And that's where efficient transmission of information is the theory. So there's hypotheses that would say, this is like bonding social capital, bonding for cooperation, bridging for information sharing. And these network structures, these different types of network structures, when you see them in the network are consistent with their like the fingerprints of those sorts of social processes. We can talk about in the Q and A whether you believe that, but that's the logic of a lot of the network analysis that's happening in policy analysis right now. Okay, so this is the actual, from the first study that I did and the first paper we wrote about this, this is from the Bay Area around integrated regional water management. All of these red circles are actors of various sorts and the blue squares are the policy venues in which they participate. For example, I started with the list of integrated regional water management which at the time was the big story there and that's where the biggest game is. So all the lines are actors participating in these games. So this is a two-mode network which is where that came up. This number is like 100 and something in here and you can see this is what governance looks like. It's not pretty, it's messy, but within this are those little motifs to think about what are the structural configurations. This is zooming in on the most central actors and you can see this is that big square Bay Area IRWM and there's several other ones, East Bay Water Forum, Central Valley Flood Plan, Cal FED, which at the time was still alive and then all these big actors here, a lot of these actors here are government agencies, state and federal government agencies and some regional government agencies that span a broad geography just to give you a sense of who's in there. So ignore everything for the most part here except where these circles are but I wanted to show the canonical regression table here. These are the results of what's called an exponential random graph model. Exponential random graph models are the cross-sectional models that are in a sense the regression analysis for networks and what they do is they take the network structure and think about which, given a link, does the link produce particular structural patterns that make it more or less likely to observe the network. So you basically say to yourself, how likely is it to observe different structural motifs? You put those motifs in here as independent variables in a sense and the coefficients tell you if it's a positive coefficient you're likely to see a link that creates these motifs is more likely to exist and if it's a negative coefficient, a link that creates that motif is less likely to exist. So this is basically showing you here that there's a lot in the Bay Area, there's a lot of centralization among institutions where you have those big blue squares that are centralizing a lot of actors providing bridging capital and this one there's a lot of actors within the same geography. They operate in the same county in the Bay Area working together and then these are showing that larger, that more actors that are state government, federal government or water or environmental special districts are more densely connected in the network so they're more powerful within the network in a sense. And then down here there's some convergence issues in these sort of models so you can analyze what's left over and what's left over is there's also a lot of closed network structures. So the overall network actually has motifs that are related both to learning and cooperation, both bridging and bonding social capital exist in these networks and that's crucial. These networks are not built from one purpose, they're multi-purpose networks that have to deal with all of those problems. Okay, so then we can think comparatively what's happening. So this is a paper in public administration review where we looked at the networks in the Paraná River, Tampa Bay and San Joaquin River and again we see a lot of open network structures around forums, individual policy venues like down here in San Francisco Bay and the Delta but in Tampa Bay you have more around the actors and in particular there's a really strong type of actor in Florida called the Southwest Florida Water Management District which integrates a lot of the different types of water policy decisions. So depending on the overall institutional structure in a particular state you get the networks to have different types of structures. And this is, you know, the comparative but also you notice the Paraná is much smaller so it already gives you a hint that in the developing country context the institutional capacity for developing these sorts of arrangements could be smaller. Okay, so how do they change in response? This is Romero's work from Paraná. So he did the network in 2010-2012 and right before he did it here there was a big wildfire event in Paraná. This is a picture of the smoke from the satellite. And as a consequence of that the network responded by creating a bunch of new forums and getting a lot more participation but what Romero showed over time is when he did it again a lot of that stuff had disappeared. So that gives us a hint that, well number one, dynamics are crucial but that's also not a guarantee that something that the institutions are built and then they stay. And the hypothesis that Romero is working on here is that because of the lack of capacity in a lot of developing countries this is like a key characteristic. They get together, they respond to an event, they talk, they come up with some informal ideas and maybe some plans and then nothing really happens because they don't have the capacity to keep that institutional development going. Okay, then you can look at as a comparison what's happening with sea level rise in San Francisco Bay and I just want to point out that adaptation to sea level rise also has a lot of cooperation problems involved. It's not just mitigation where collective action has to happen with climate change. But for example, this is with my engineering colleague Mark Stacey out of Berkeley. If you knock out Berkeley with flooding look at all the regional transportation impacts that happen. People have to move all around so you get these big regional interdependencies and then if you protect Alameda County like do a shoreline scenario where you just armor Alameda County and say no flooding is going to occur there, it moves water elsewhere. So it actually is like a bathtub type of effect where protecting, doing infrastructure protection in one county actually creates regional effects and given those interdependencies you have to find cooperation. So this is what's happened in our more recent analysis in the Bay Area. These statistics were derived from looking or these networks were measured looking at different planning documents and you can see and when those planning documents were created and you can see time one, there's a very few things that are looking at sea level rise but over time this network just grew and grew and grew and you have more and more projects, more and more actors involved with looking at sea level rise and climate adaptation in the Bay Area. This is kind of the vintage, it's from California so we got to think about the vintage of things. So the first one was born around 1992 but then around 2010 the rate at which these new institutions were created to deal with sea level rise really accelerated and it's still happening. You're just seeing this like a Cambrian explosion of institutional development that's happening right now in the Bay Area around sea level rise. I mean I'm deeply involved with talking to people about what is this going to look like. They're trying to figure it out right now. So you're at a moment of institutional change which makes sea level rise a cool thing to study. But also what's happening there is these connections right here are the presence of different connections, local actors to local venues. So for example a city connecting to another city operating at the local level or a local actor connecting to a regional venue or a regional actor connecting to a local venue or a regional actor to a regional venue and what you see is that it's a process of decentralization not centralization. So to actually address a regional problem what's happening is you're getting a lot more regional actors going to local venues like saying hey sea level rise is a problem we're going to create a local vulnerability planning process and help you with it and local actors cooperating with each other and there's not very much region to region stuff so the relative importance of region to region and local going up to the regional decreases. So it looks like in California which has a very strong home rule tradition of local governments trying to maintain their autonomy the only way to make region happen is to go local is to decentralize it. Now we don't know if that's the same thing that would happen in Vermont or whatever which talks about the comparative studies but that's what it's looking like in California as far as the dynamics go. Okay next hypothesis institutional externalities and political power of actors so we try to figure out how do these institutions affect each other. So we would ask in one of our surveys this is 2014 version of our surveys we said to people name the primary most important thing that you're involved with and a lot of people might do this in California may say CalFed which was one of the big partnerships at the time and then we would say out of a list of other ones how much does influence do these other ones have on yours? So they say well I'm in CalFed and I'm either doing well or doing not well in CalFed but now does IRWM another form does that influence positively or negatively what I'm doing in CalFed and the central value flood protection plan yeah I participate in that or not does it have a positive or negative influence or the Bay Area IRWRM does that have a positive or negative influence and you add all that up and when you get that across all the respondents these are all the arrows here show interdependencies between institutions in other words the overall strength of a decision being made in one institution affecting the other institutions so the question this analysis was given those interdependencies how well are people able to achieve their goals because you go to these policy actors go to try to like achieve their goals how well are they doing that and then what we were able to show is that when the externalities are really strong and people are but they will also say that I'm doing well in another institution we like say Chris is saying I participated in the University of Vermont but I'm also participating in some other thing and I'm doing really well that other thing will not will not have much of an effect on how well Chris does at the University of Vermont but if he says that he's doing poorly in those other places it has a really negative effect on your capacity to get things done so kind of one of the interesting policy lessons from that is like if you want to succeed in winning in one policy game like the big policy game go to other policy smaller games that are linked and win and if you do that you can kind of mitigate the effect of a portfolio of participation which I would say is also if you want to change something in the administration of a university you better participate in multiple games to figure out how to do it and win a few of the small ones and then you can win the big ones okay so that's institution X9 the next one is how the institutions co-evolve with cooperation and the question here is that for a long time we didn't really know the joint participation in one of these policy forms would actually lead them to collaborate here so we tried to figure out okay does this actually happen that you will develop bilateral collaboration as a function of institution this is like a huge core hypothesis in the entire institutional literature is that institutions can at least co-evolve with participation with cooperation of not produced cooperation so does this link exist if these two actors jointly participate here but we argue in the paper that it depends on geographic scale so this is from the Lake Victoria if it's working at the Lake Victoria regional level it's less likely to evolve cooperation than if they're working at the national level or if they're trying to make a very large policy change like at the level of major rules governing decision making it's harder than if they're trying to deal with implementation of projects and what this shows here is from the network modeling we did in there is the probability that this link exists based on whether or not the two actors participate jointly in a forum so the first question is yeah if they jointly participate in a forum they're more likely to cooperate but the likelihood of that goes down as you go from the national sub-national level scale to the country in Lake Victoria to the regional, to the Africa continent to the global scale so it gets much harder at higher levels of geographic scale and if you're dealing with what we classify as more kind of operational choice that would be an Ostrom term versus collective choice that as you go up the levels and this is a core hypothesis in the whole Ostrom framework as you go up from operational rules to collective choice to constitutional it gets harder and we show that exactly that exact thing in this paper this is Matt Hamilton made up this graph by the way Kudos to Matt Hamilton for like my favorite graph I hope you like it too okay now finally how do these institutions perform we looked at to measure performance I mean obviously you're gonna ask the question and everybody does how does this affect environmental outcomes I'm not gonna be able to answer that question right now because we need a heck of a lot more research but as a proxy to start out with we can say how do well do people perceive the performance of the institutions in terms of having an impact on your interest if they're fair if they think they've improved the problem if you had some efficacy in it so for each in many of our studies we say which ones do you participate in like this would be you know policy actor X central valley protection flood protection plan and their views on how effective that thing was so you can imagine in a survey design that's kind of it's a tricky business because you might have people nominate 10 different things that they participate in and then for each one of them we had them say how effective were they and then we're able to analyze that so our kind of hypotheses are based from transaction cost theory saying the performance of these institutions depends on the payoffs that people see cooperative or conflict how much scientific knowledge is at play how much they understand the preferences of other people their level of participation how experienced they are in water and whether or not they are a government actor and so this basically shows the marginal effect of all those independent variables depending on that so you do a regression analysis and say how much does each of these I'm focusing on two how much do each of these independent variables, political knowledge and scientific knowledge affect performance across these different systems Tampa, California, Paraná for all these different things so for example if you see here this is people that say I really understand political knowledge I understand the preferences of other actors really well that has a fairly negative effect on how the contribution to the problem but it has a really strong effect on how well they perceive the fairness and efficacy of the thing so it's kind of like you're going in, you're talking to people and as soon as you understand their preferences your perceptions of the procedural fairness get better and it's really strong for Paraná and not as strong for California and Tampa so it's like Paraná is an earlier stage of institutional development so that a hypothesis there is that at an earlier stage of institutional change this political knowledge and procedural bit is the most important because that's the thing that is affecting people's performance the most but as you go into more mature systems scientific knowledge plays a much larger role and has a broader role across different performance so it has an impact on fairness and efficacy and also on the more kind of output outcome oriented perceptions to solve the problem does it help me achieve my interest and especially in California and Tampa Bay the more mature systems so the relationship between these transaction cost variables and the outcome and performance of the system depends not only on the type of the dependent variable or performance metric you're looking at but depends on something about the stage of institutional development possibly something about the level of political development in a country with the idea that we think as far as developing when you're creating new institutions paying attention to the policy preferences and that type of political knowledge is the first step and later the science part comes in which is counterintuitive to a lot of people like oh it's a solid policy problem so we have to get the best available science in place which is true but probably before that you got to understand what the preferences are of the actors that are involved with these processes if you don't get that right then you're never going to be able to figure out how to find a solution set and this is just fresh fresh from the airplane editing that I was doing on the way over here this is in Lake Victoria where we asked them similar questions and so how good is the information available to you how would you describe the cooperation between organizations is it fair for all the venues in the different measures of social capital either closure and or bridging and what it shows here like for example this bridging type people who participate in a lot of forums that are very popular in other words have lots of participants they get more information but it has a negative effect on cooperation and fairness while the collaborative closure as expected has a positive effect on cooperation and no effect on information and procedural fairness which means that two types of social capital bridging and bonding social capital have differential trade off effects on the different types of performance so if you're building one of these systems or thinking about managing the systems you need to have both information sharing and cooperation and fairness as performance criteria that you want to meet but there's going to be trade offs there and how you manage those trade offs is going to be a key to the effectiveness of the system especially if you have to think about the system over time that at one stage learning needs to be emphasized and in other stages you might have to deal with cooperation more significantly so this is a cool paper in my opinion too alright so here's the recap of all the hypotheses we think that they have structures, cooperation and learning that the institutional change over time is crucial but it depends on the capacity and the type of political culture institutional externalities not only do they exist but they constrain how actors perform and makes it so that the actors have to have a deal with a portfolio of policy participation I think we have got now strong evidence from our work also some other works have done it that institutions and cooperation do indeed co-evolve which comes first is still an open question but I think they co-evolve for sure and that the performance of these institutions is affected by variables that are related to transaction costs such as political knowledge and scientific knowledge but the dynamics of that again varies across space and time so where does that lead us to the future you guys said you wanted to about the future of water governance well I'm not exactly you know who's Johnny Carson prognosticator guy what's what's that? Carmack yeah it's probably we should have asked all of the 20 somethings in here if they could have said that but anyways it's a what I view I mean for sure it's messy and it's gonna it's messy now it's gonna be messy later and we need to learn how to steer it so what I view from the research perspective what this perspective has done is kind of open to Pandora's box to think about to try to get as many people as I can to study policy systems from this perspective and build on what we've done here if you want our surveys you can have them please use our surveys adapt them to your systems because if we don't get some cumulative knowledge here we're never gonna answer these other big questions like we did some comparative research in other in other systems but guess what a lot of countries a lot of estuaries a lot of social ecological systems there's food systems there's health policies education system how do these how do these complex policy systems work in there what what are the things that we're always gonna see across the systems and over time and what are the things that are gonna vary according to the institutional context or the ecological context we do not know the answer to any of those questions yet in my in my opinion and then over time right are you getting cycles shocks how are things evolving are these systems that change incrementally I think they're they they're probably subject to punctuated equilibria of various sorts because that's how most complex system behavior works how are we gonna see that a lot of my research and other research is focused on cooperation specifically which obviously is important but I would argue these systems have to have learning and fairness and cooperation are the three core functions and they do not always work in positively each other there can be trade-offs with those things and how do those trade-offs play out and how do we effectively manage those trade-offs and how do we steer the system so that those trade-offs are made in the best way over time to have for a society to deal with new problems and environmental outcomes all right so I had the performance thing but I didn't show you anything about the water quality in the California Delta the health of the Delta Smelt or if there's harmful algae in there or not because all those problems of course are linked to each other but I've got one snapshot and it's not only do those problems unfold over very long periods of time which makes it necessary to track the performance of these systems we have to be doing long-term research and one of my goals is to establish an observatory network of socio-ecological systems that are capable of studying this on a scale 20, 30, 40, 50 years time so how do we solve the researcher collective action problem of doing that I would invite everybody to cooperate together to do that because if we don't do something like that we're not going to be able to answer questions like this so not only do the environmental outcomes unfold over very long periods of time the counterfactual analysis is very difficult to do to think if I took out one node from that system what's going to happen to the environment take the Delta, how do I do a counterfactual analysis over a 50-year period of the governance system of the Delta, what am I going to do go back in time for 50 years remove what node or remove what half of the governance system and then see how things are going to unfold very difficult to do but that's the reality there's a lot of cool work going on randomized control trials and counterfactual analysis and that stuff but it's a very small scale compared to what actually the scale of governance arrangements are in the reality in my opinion and then policy recommendations what do we tell policy makers I said a few things I think that are policy relevant that might be recommendations for either individual actors to help them succeed or that we ought to manage this or that but right now I'm still struggling I'd love to hear any ideas what are the top five things I'm going to go tell the governor or the chair of the Delta Stewardship Council about how to effectively manage the system because what I usually do if you go sit around offices in California right now you will find pictures from my research sitting on coffee table various things in agency places and when I have a chat with agency people in whatever form they go over beers or formally in a workshop or whatever we're looking at these networks and they're like oh yeah that's our world we've definitely recognized that they all recognize it there yeah it's messy it sucks to have to go to all these meetings and try to figure out how to do it there's fragmentation and conflict and then they say to me well what do you do about that and I'm like oh man well we're trying to figure that out still you know I don't have a magic bullet answer for that I wish I did but I believe that the only way that we will be able to find really good answers about policy recommendations is to embark as researchers on this type of approach where you're looking at these systems over a long period of time and if we have enough people doing that of enough places over a long enough time then I think we're going to get to some more solid answers about how to effectively manage it alright so that's it so thanks very much for listening I hope I didn't go too fast over some of these things and I'll take any questions I guess did you want to are you going to manage this or yeah so we have one mic so if you could ask your question oh you have a mic if you could ask your question that I will recede it for this is getting video I have a question about the survey technique and the interviewing it's enjoyed your talk and the analysis of the data results from those interviews and the research could say a little bit about how the interview how the surveys are actually conducted and then it's kind of getting into the weeds but is it an app? is it in person? is it online? and when you talk about the complexity of the networks and the connection between individuals who are bikinos they have a lot of connectivity that is replicating a single methodology and I'll be fascinating to hear excellent question so what we've done is we've embedded microchips in every single policy actor we can find and track them in real time that's not what we've done but it would be really nice to do that and have it like satellite enabled so we can kind of see it I tried that but it didn't get past the IRB so but yeah so we do we do a lot of survey research and most of it is online via online survey platforms I think Qualtrics, I've done it in live series Qualtrics I think is a pretty good platform for that where and we've done some customization of Qualtrics using their JavaScript interface to be able to get it to be pretty user friendly as far as reduce the respondent burden as much as we can with nominating people that you collaborate with or nominate institutions but there's no doubt in issue with surveys we do not have 100% response rate we're ranging somewhere between 35 to 50% depending on things so network analysis is definitely sensitive to non-response but nevertheless I think we've learned a lot about these networks I kind of think of it as like a Monet painting of the networks like you look at a nice realistic Monet painting you learn something about the landscape but you don't have a realist version of it yet so we try to get there so you got to reduce the respondent burden and then if you can honestly if you can like some of these we did by document analysis we pulled every single plan that we could find around sea level rise and then went through on the document or the website the list of actors and populated it that way and not only did we populate it that way to make the network we collected all their contact information at the same time and there's a survey in the field right now to over 3,000 potential sea level rise actors I think our list we took was too big in the end but you got to do stuff like that and if you're going to do surveys just face it you're going to have to accept the limitations of response rates here and deal with that as best you can there's some network methodologies that allow you to estimate the models with missing data on links but you know that's like not that many links that have missing data that I feel those methods are robust too so those are all yeah it's tough in the archival data using the web or meeting minutes or whatever whatever it is I think allows you to get more complete network pictures but the what you observe is limited because all the things on the list it on a document may not capture the fact that there's more informal or not unofficial collaboration going on that's not observed so they all have different tradeoffs there yep yeah go ahead I was really interested in your discussion about cooperation and learning being embedded in all complex systems and I think if you practice I wrong you're connecting cooperation to bonding social capital and the learning to bridge social capital but what it sounded like was when you have people interacting let's say you and Chris at a conference and you go to the same conferences you're sort of redundant right you're seeing the same person which helps to bond you but perhaps limits your learning and I'm curious though because I do I should say I do in depth qualitative research what kind of interaction would you be learning in a more deep sense rather than a superficial sense like so it's diversity of knowledge rather than depth of knowledge yeah possibly I mean I definitely think that these open network structures are more about diversity of knowledge and learning new things that you may not have known before rather than like deepening a relationship over time with the idea and you know it's kind of like strong ties weak ties that all this goes back I mean there's a I shouldn't go back there's just a long tradition in social network analysis about the difference between open and closed network structures and there's like bridging and bonding social capital structural holes strong and weak ties all those different things are related but in my opinion the open network structures are about for novel information rather than deep information I guess if I wanted to like toe the line of the theory as much as I could I would say the deep learning you're referring to is really something that enables cooperation more than learning something totally new about a novel policy or something like that I mean you could definitely challenge the theory from that perspective but that's like just to keep with you know in line with what the theory would try to push you to do that's that's how I would respond to that but I do think the systems have to have the novel information bit too because otherwise you get locked into a pattern of cooperation around one particular say solution and you can't get out of it and but so you have to have a capacity over time if you can't learn about what are the new problems how to solve them what are the new actors want your system will for sure fail so you have to have both and then how to manage and if you believe that which I think there's plenty of evidence for that now the question becomes how to effectively manage that and whether or not the closed network structures provide some additional benefits it could be it's a paper a hypothesis worth exploring for sure other questions I have so many I'm not sure where to stop but I will say this that from my experience Vermont is a beautiful mess but not nearly as messy as California well that's an interesting statement because comparatively what makes one more or less messy is a great question of the questions I have I'm going to ask you this one so organizations sometimes come together organically or self-organized a group of people will around a common interest will create sort of an association right if you have if you're a sort of a central policy actor maker which space that I think I occupy can you use a map like yours to identify and provide guidance as to how to direct the enthusiasm of that group towards an under occupied space or an under occupied leverage point what position are you in I I will tell you I am the senior policy advisor for the state's department of environmental okay man it's a good question it's not politically charged you know I think that there's probably two ways to look at that at least two ways to start or maybe even three you look at the map and you say what's going on in the periphery right who are all those actors in the periphery that are not connected to those planning process which means they're not very active and you do an assessment about how important those actors are actually to the environmental problems and the fairness that are there if they are like they don't matter because they don't care much or they don't have a huge effect maybe it's okay to leave them out there but they do matter because there's a fairness like an environmental justice consideration they're having a huge impact and they're not connected it's probably a good thing to reach out try to get them included because if they're not then whatever your system is doing is likely to have a limited impact because you're not changing or being informed by those actors another thing I think to look at is like thinking about the if there's a segment of the network like a set of planning processes that are very disconnected what's going on out there in assessing whether or not that could be like a set of planning processes that are mandated by some law or something like that that's acting quite independently of the rest of the system what's going on out there does that need to be linked more and another important thing I think is how to in a sense make the system a little bit more efficient possibly because I think what happens in one of the problems the pathologies of these systems that you'd like to guard against is having too many redundant forums that are kind of doing a lot of the same things where people like you have to spend every day going to these forums talking about the same exact thing over and over and you get a lot of meeting fatigue about that and how do you reduce that but not too much because you do want some redundancy but you gotta think about assessing does each of those blue squares does it really need to be there is it really doing something functional for the system or is it just kind of a waste of time and over time some of these things do become a waste of time and stakeholders abandon them and then they die that's kind of the birth and death process according to an evolutionary process that's basically the selection process is whether stakeholders think they're useful so I think it's good to be explicit about that when you're thinking about the system so those are kind of three general things that I'd love to hear what your thoughts are how you do it principles here that would be generalizable to the other environmental issues or do you think they're all unique say air or water or soil or food do you think there's common principles there I think that all of those issues involve collective action and cooperation problems you gotta solve so I think that the governance systems in all of those are gonna have a lot of common properties it's kind of an educated guess because we haven't really done enough research to get a handle on that but I think let's say 80% of the findings from water are gonna generalize to what you're seeing in these other systems but then there's gonna be some interesting 20% that's gonna be like more specific to types of resources that is gonna be interesting we're gonna need to have some theory about too because that customization to the nature of the problem is part of the story that's going on here not to mention the interconnections between the problems water, food, energy, da da da that's what a lot of it so if I tried to do water, energy, food, nexus with this sort of thing and dealt and tried to bring all those things together it's not gonna be simple any other questions one over here yeah I was wondering I think that you were previously saying about meeting fatigue kind of gets to this but do you ask in your surveys any questions that you get at how people, how actors from the network feel about the complexity of the network because it seems to be like there's probably a sweet spot and from a collective action framework would say try to all get pointed in the same direction use the same metrics set similar goals so that you're reducing some of the complexity but at the same time you're speculating that a certain level of complexity promotes some of the learning and evolution I have in the 2014 version of the survey that went out to Tampa in California a series of questions that are what are the major challenges to cooperation in your system and like fragmentation, time fatigue are in there and I think we replicated that in the C level rise one that we just let out I'm just remembering if we got that battery in there, I think we have a version of that in there but that data is currently being analyzed right now Jack is leading an analysis on that so I can hopefully report to you at least what the rank order is, the key challenges but definitely we put on things about you don't have enough time or resources to participate across the system which I expect will be a pretty high highly ranked challenge because you kind of at least anecdotally hear it all the time