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Julia Jones Oral History Interview, December 3, 2020

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SARA KHATIB: Okay. My name is Sara Khatib and this research is for my master's thesis, the research involves the history of different traditions of science at the Andrews Forest and the philosophical perception of nature that underlies these traditions. I would like to ask you a few open-ended questions regarding these topics. I expect the duration of the interview to take up to one hour to complete, but maybe up to two hours, depending on your interest in knowledge, would you like to participate in this interview?

JULIA JONES: Yes, please.

SK: We can end the interview at any point you wish to do so. So, just please inform me right away if you no longer want to participate and the interview will immediately end. Do I have permission to record this interview?

JJ: Yes, you do.

SK: The interview will be deposited with the Oregon State University Library Special Collections and Archives Research Center for preservation and access. 00:01:00Their commitment to open access includes the release of contextualized interview content online. Are you willing for this interview and its derivatives, including a transcript and an interview abstract to be made available online?

JJ: Yes, I am.

SK: Great, then we shall resume the interview. So I'm here with Dr. Julia Jones professor and program head for geography. She received her PhD. in Geography and Environmental Engineering from Johns Hopkins University in 1983 and made her way to the OSU community in 1989. Julia studies the dynamic nature of the Pacific Northwest forest and how different drivers of change can affect water yield, water quality, landscape disturbances, and climate. Are you ready to begin?

JJ: Yes.

SK: So the first few sets of questions are in regards to your personal philosophy and practice of science. And the first question I would like to ask 00:02:00is, how would you define an ecosystem?

JJ: I define an ecosystem as a set of biotic and abiotic interactions.

SK: And how would you describe the nature of an ecosystem? Are all ecosystems static, dynamic, orderly, or chaotic?

JJ: That's a really interesting question. I see ecosystems as dynamic and I see them as neither orderly nor chaotic but perhaps somewhere something in between. There is some order and some stochasticity, some randomness. And then to me, brittle and fragile are more synonyms than antonym. So do you want to explain 00:03:00that to me better?

SK: I suppose resilient versus fragile is the spectrum that I'm looking to ask.

JJ: I see them as resilient.

SK: Yeah, okay. So they are a combination of order and chaos and more or less resilient.

JJ: Yes, and dynamic.

SK: And dynamic. Yes. And would you say that that's consistent with all forest ecosystems?

JJ: Oh, so that's a good question. I was thinking about all kinds of ecosystems - forest, stream, marine, coastal, alpine, arctic. Yeah, you name it.

SK: And what is your theoretical philosophical background and how does that 00:04:00apply to you toward your science?

JJ: I don't really have much of a philosophical background in college. It was popular in the 1970s to read Thomas Kuhn's theory of Scientific Revolutions. I do some teaching in my classes about deductive versus inductive reasoning which may get to the next question. So maybe that's enough to get us going.

SK: Yeah. So how would you describe your scientific style?

JJ: So, I do not conduct experiments myself with physical materials, but I do use data from long-term experiments. And I also would say that I use models as 00:05:00experiments. So, I looked up what you might have meant by Baconian versus Popperian. Do you want to describe that a little bit to me so that I can answer your question?

SK: So Baconian in the sense of, it's more inductive and open-ended, but there's still some experimental manipulation of matter. And Popper is hypothetical deductive so you have a hypothesis prior to doing your experiment and it's, it's more forward predicting rather than backward predicting, I think, is another way to put it.


JJ: Well, that's interesting. So, most, most of the work that I do is an analysis of long-term data. So it's looking in the past. So the models that I fit are our models about the past behavior of ecosystems. They are not projections or predictions of the future. But having said that, the way I approach structuring those models is probably a combination of induction and deduction, in the sense that there are theories or concepts like the hydrological cycle, for example, or the water balance or the energy budget that lead you to expect certain kinds of relationships that can be tested by fitting statistical models to data, and then they can be falsified. So there definitely 00:07:00is some falsification involved, but it's a retrospective analysis of past data and there is also some induction because the process really works by fitting models and then trying alternative models and so that could perhaps be regarded as an inductive process of attempting different kinds of analyses to explore alternative ideas, maybe.

SK: And I want to go back for a moment. Do you mind elaborating when you say models as experiments? Is that what you're referring to, right now?

JJ: So, the notion of using a model as an experiment is that you don't...So 00:08:00there are many different kinds of models: optimization, simulation, empirical, theoretical, etc. statistical, mathematical. The kinds of models that I typically fit are empirical statistical models, but they do attempt to get at mechanisms. So they attempt to be mechanistic models as well. And I like to use models as an experiment because I don't expect the model necessarily to fit well or to explain the data well, in a statistical sense, and I'm as interested in the ways in which the model does not explain the data as I am in the way it does. And I'm interested in starting with very simple models. And then 00:09:00incrementally adding complexity to the models to try to see how the model behavior changes as you add, for example, different variables. So I regard that as an experiment in the sense that each time you change the model, you add a variable or you change some parameters in the model, or you change the structure of the equation or equations that you're using in the model. Each of those actions can be thought of as an experiment. And then the outcome is how the performance of the model changes. And that process is an iterative one, but the learning happens from the successive iterations and modifications of the model.

SK: Great, and that's interesting because this reminds me of the concept of 00:10:00reification where people are wary of models where we superimpose them and assume them to be reality themselves when they're supposed to be analytic tools. Is that your way of sort of preventing from that happening?

JJ: Right, yeah. The model isn't an answer in itself, and it's never finished and it's never correct, it just helps you to see something both because of what it explains, and what it doesn't explain.

SK: That's an interesting take on models that I have yet to come across. Would you say that there are people that use it in a different way, where they do see it as answers? Is that something you've seen within your field?

JJ: So my field. It's hard to know really what my field would be, but I could say that certainly in the field of hydrology, many of the practitioners of 00:11:00hydrology, though not all of them, are civil engineers and many of those people utilize hydrologic simulation models and there is a very large literature on many aspects of model performance and modeling philosophy. And, so, within that community, you find, of course, people whose careers are built around the use of a particular model which they continue to develop and refine over time, whether it's about snow or streamflow or whatever. But you also find people within the field of hydrology can often, these are people who do not have an engineering background, but it's not necessarily the case, who are agnostic in their use of models. They don't favor any particular model and they regard models as tools 00:12:00for exploration, which are more in the way that I had just described.

SK: And then one more thing I want to return to and elaborate on, is you said that you use models, not so much as predictive tools, but more so to analyze past mechanisms. Can you give an example or describe that a little bit more?

JJ: Yeah. A simple example would be there is a long-term paired watershed experiment at the Andrews Forest in which, for the case of simplicity, there are two watersheds, both of them had 150- to 500-year-old forest on them at the beginning of the experiment. In the early 1950s stream gauges were installed in 00:13:00those watersheds and streamflow was monitored. And then in 1962, after about 10 years, one of the watersheds was clear cut over a four year period and then burned.

So hydrologic theory, or more simply, the water balance would lead you to expect that, because we believe that runoff or streamflow is the difference between incoming precipitation and water that is lost from the watershed by evapotranspiration, you would expect that the removal of the forest would reduce evapotranspiration, and therefore increase streamflow. But, you would also expect that as the forest regrew or, actually, as a planted forest grew in that spot, evapotranspiration would resume and increase, and then streamflow would go 00:14:00back down again. So, I have conducted analyses using past data from those watersheds to test by how much did streamflow increase after the clear-cutting of the old-growth forest and burning and by how much and what rate has it been declining as the planted forest has been growing. Is that what you were looking for?

SK: Yes, that's great. Thank you. And how have your disciplinary roots influenced the development of your approach to science?

JJ: Well, my disciplinary background is rather peripatetic. I have a bachelor's degree in economic development. And a master's degree in international relations and a Ph.D. in geography and environmental engineering. So the trajectory of my 00:15:00disciplinary development was that I moved from the social sciences more into the natural sciences via engineering. So before my Ph.D., I did a lot of work with mathematical optimization modeling, which is a different kind of modeling than anything we've talked about here. So, I guess I would say that my education my educational trajectory were motivated by an interest in social issues. And I think we'll get to that later in the interview, but that that was a reason for studying economic development and international relations, and then that led me to look for specific questions in the natural world that are relevant to 00:16:00international policy or domestic policy related to things such as wood fuels energy, which was the topic of my Ph.D. and the effects of deforestation on soil characteristics which were also part of my Ph.D., and the causes of deforestation. And so the engineering methods, which I learned and developed for my Ph.D., have not been part of what I have continued to do, but rather, I shifted into this other kind of statistical empirical modeling that I just described to you because I became interested in explaining what had happened in 00:17:00the past as opposed to using models that give you answers to other kinds of questions. So a mathematical optimization modeling is most generally used to try to provide an answer to a problem and that is what should people do. How should such-and-such a resource be managed? But I became more interested in well, what has actually been happening in these ecosystems, which I thought are important questions to understand before we make decisions about how we ought to manage?

SK: Would you say that that approach contributes or is aligned with natural history in any way?

JJ: Certainly, yeah

SK: And at what point did you start turning towards hydrology and studying 00:18:00forest-stream interactions?

JJ: So, I got a master's degree in international relations. I got a bachelor's degree in economic development in 1977 and then a master's degree in international relations in 1979 or 80. And I was very interested in issues related to wood fuel energy and how people were faring in poor developing countries in Africa. So the Ph.D. was an exploration both of mathematical modeling for that question. But also, I had an opportunity to do field research in Tanzania and I think that was something of a transformative experience for me. To work in the field and try to communicate in Swahili with Tanzanian 00:19:00colleagues and workers and to sample soils and forests and I became more ... I think I was humbled by the complexity and diversity of the ecosystems and became much more interested in trying to explore and understand those. And so, why don't you lead me back to the question that you would like me to answer?

SK: Just at what point you shifted towards studying hydrology?

JJ: So that led to empirical work on describing and characterizing soils, but which I conducted while I was on the faculty of the University of California, Santa Barbara working in Africa with my then-husband, both in Tanzania and Kenya, and in Eritrea. But then when I moved to Oregon State University in 1989 00:20:00I had the opportunity to begin to work with long-term records of streamflow associated with the Andrews Forest, and that has been an endeavor of 30 years, I guess.

SK: And then would you say that the combination of these different academic trajectories, from the social science to environmental engineering to streamflow, has that all culminated into influencing your philosophy of science today, or do you think that it's very different than it once was if that makes sense?

JJ: For me, as a practitioner of science, I would guess that my philosophy is 00:21:00sort of continually evolving as I learn more about the ecosystems because each question that you attempt to answer leads you to what you don't know, which means that you start a new question and you may expand from one place to another, like looking at different sites and comparing them. I've done some of that or you might look to change the scale at which you're looking at something the temporal scale or the spatial scale. So, I'm not aware of having a philosophy of science, but rather, I feel like I'm on an adventure of a treasure hunt of continuing to find new things that puzzle me or questions that I think 00:22:00need to be answered open questions and trying to answer them with existing data. So that's the fundamental recurring theme is that in the fields in which I work there is a dearth of use of analysis of existing data sets. People have a tendency, for reasons that I don't really understand, to utilize models which don't rely on real data very much or to engage in experiments that produce data from a manipulated system that's been manipulated by a researcher and by contrast to those two approaches, which I think is anticipating a later question in your interview, but I am principally interested in what we can learn by 00:23:00observing natural systems, including those that have been manipulated by humans, possibly as part of a big experiment, but not trying to simulate them or optimize them.

SK: And what is your strategy in developing a research question?

JJ: Well, each research question seems to emerge from the work that's been done before. But also the research questions tend to emerge somewhat opportunistically from events and sometimes they emerge from collaborations, the interests of a colleague in a conversation that sparks an interaction, or a student who has an interest in a particular topic. But the thread, but for the 00:24:00thread of work, which is probably most closely related to me, you know, papers that I have led the ideas to seem to emerge as a sequence. One paper, leading to a question that hasn't been answered, which then leads to the next analysis. So that doesn't really sound like a strategy, very much. But that's the practice.

SK: That's how it unfolds. What are your thoughts in regards to objectivity in scientific research?

JJ: I guess I would say that it's very difficult or perhaps impossible to 00:25:00identify a research question objectively because the research question is always something that is based on your prior experience and knowledge and your inclinations and which include your feelings, such as places that you love. Or you want to learn more about or something that you fear, maybe perhaps not so much for me, but possibly. So I guess I would say that research question identification, I see as being highly subjective. But then the conduct of the research itself needs to seek objectivity, at least in the sense of rigor or respecting certain rules about the use of data, the fitting of models, the presentation of a balanced evaluation of what you found. Not trying to influence 00:26:00the results.

SK: And as a researcher, how do you use the scientific method to find truth?

JJ: Well, I guess I would say that I'm probably a post-modernist in the sense that I am not a believer that there is a truth with a capital T. But I do think that the scientific method is viable and best that we have an approach to learning about our world and learning about the things about the world that we need to know in order to make decisions to try to take care of the world and ourselves at the same time.


SK: Are there laws of nature? And if so can you explain what a law of nature means?

JJ: Certainly there are physical laws. You know the laws of thermodynamics are certainly laws of nature. And so is the theory of relativity, which operates a different time scale than we mostly live in and the Newtonian laws of mechanics seem to me to be quite applicable and relevant to the world that we live in, as people are time and space scales. I have not encountered anything in ecology that I would consider being a law, however. I think that that's a really interesting feature of the state of knowledge in whatever you want to call it, 00:28:00environmental science or ecology in general, that it has not been possible to identify things that could be considered laws. And, it appears to be the case that the complexity of ecosystems so far defies our capacity to perceive laws.

SK: And you just touched on this a bit, but I want to talk about it a little bit further. So what exactly is it about ecology, the complexity? Can you elaborate what you mean that it defies our ability to establish or find laws? If you can, describe what about the complexity?

JJ: Well, perhaps a way to do it would be to talk about models. I had the great privilege for about a decade to work closely with some very talented senior 00:29:00mathematicians in Oregon State University and some very talented computer scientists and we were working in a field that we called ecosystem informatics, but the idea was to bring together the methods and approaches and understanding of mathematics and the computational tools of computer science to examine and try to understand ecosystem dynamics. There were many really deep thoughtful conversations that occurred among the group of us as we were pondering this area of intersection among these different disciplines. But one of the ones that stuck with me is that mathematical models of systems tend to fall into two 00:30:00different classes. One of them is a sort of equilibrium model that solves for a particular condition that is presumed to be like a steady-state condition that doesn't change over time. And other forms of mathematical models are ones in which their time is varying and processes vary over time. But typically the equilibrium-based models are applied on two processes that operate at longer timescales, while the time-varying models are applied to things that operate in relatively short time scales. So this gets back to one of your first questions, and that is that ecosystems are dynamic. In fact, the earth as a system is 00:31:00dynamic on very long time scales. And so the mathematician commented that mathematics appears to lack models which can capture that sort of large scale or long time dynamics and this may be well, it seems to be related to a number of your questions. So maybe you can just ask me more if you're interested.

SK: Yeah, that was a great example. So I'm curious as to why it is the long-term scales are more difficult to model, I would have assumed, that the short scales are more difficult because there is more flux to them. So I'm curious as to why longer terms are more difficult or challenging?

JJ: Well, this relates to the fact that we don't have a theory for ecosystems 00:32:00yet, right, because what we understand about ecosystems is that they are continually responding to factors that are operating across a wide range of temporal and spatial scales. Everything from plate tectonics, you know, and changing the shape of continents and changing how and the climate system and the coupling of the ocean and atmospheres and the currents of air that bring moisture to certain places and not to others and then back to tectonics that build the mountains that obstruct the currents of air and heat and moisture, which then influences which things might grow where but that's all a deterministic perspective. And then, on the other hand, we have a life system 00:33:00that is continually evolving and adapting and changing to conditions on multiple timescales. Sometimes the adaptation of the response may take just a few hours and in other cases, it may take decades or centuries, so that is what those processes provided dynamism to the Earth system, which means that equilibrium models don't work very well. But on the other hand, the short-term dynamic models also don't work very well because they don't capture those longer-term processes and their influences.

SK: So, is it true that in the history of ecology as a discipline that at one point it was very fixated on equilibrium models, and then that got replaced by 00:34:00the recognition of dynamic nature ecosystems with ecosystem ecology now?

JJ: Well, it's a good question. I don't consider myself to be an authoritative historian of ecology, but, certainly, I think that people have ... . Maybe the way to describe it is that ecologists have interacted with mathematicians throughout the history of ecology, which was sort of born around 1970 and so ecologists did adopt mathematical models to try to represent ecosystems or ecological processes and they may have early on, adopted equilibrium type models, but pretty clear pretty soon it became evident that those were not adequate for describing what's actually observed and that kind of gets us to the 00:35:00motivation for and the timing of the creation of the Long-Term Ecological Research Program at the National Science Foundation. So perhaps this is somewhat relevant to your question about the history of ecology. If you think of ecology as a discipline that came into being really around the late 1960s and early 1970s coincident with many of our strongest environmental protection laws in the United States. By the time even by the mid-1970s, it was evident to researchers that ecosystems change over time at multiple times scales and a long-term perspective was needed. So there was a pretty quick realization. I think that ecosystems are anything but static.


SK: And my last question for this section is what are your overall motivations? Is it for curiosity or finding real-world solutions?

JJ: Well, I guess both. As a person, I find that life is so much more rewarding when you look at the world and try to understand why it is the way it is. So that maybe curiosity and the end the process of sort of dialectical process of making observations and then wondering how to explain them and then going back and looking more carefully. And wondering, some more. I find it to be just enormously satisfying, not because it leads to anything particularly, but just because it's a very enjoyable way to live in the world and it makes me feel more alive and more appreciative. I should have mentioned earlier that I started 00:37:00college as an art major and so art is about observation and looking. Art to me, painting, for example, is about trying to represent what you see, rather than what you believe is there. And so I think there's a parallel with science as I practice it, which is it's an exercise in trying to understand what you see, rather than imposing what you believe is there. So curiosity, I guess, if that's what you mean by curiosity, is a big motivator and a big reward, but I also believe very strongly that people who are privileged to have the kinds of job that I have a duty or responsibility to try to contribute to the welfare of our 00:38:00earth system, including the people who live in it and so applied research that focuses on ecological processes [and] hydrological processes, seems to me to be potentially a contribution to helping us to better understand how the world works so that people in general, not me necessarily, could make wiser decisions about the world and how we live in it.

SK: And if we could just go back for a minute because I'm, really intrigued by this. So with your background as an art major, was that in undergraduate school?

JJ: Well, I started taking art lessons as a child and I always did really well 00:39:00in art and I loved it. It was my favorite probably my favorite subject through high school. And when I entered college. I thought I would be an art major but I soon realized that I would have difficulty supporting myself. So I decided that I had to be practical in the most practical major that I could think of was economics.

SK: And so because I know with the Reflections program at the Andrews forest, there's this new space, since the early 2000s, where artists, as well as musicians and philosophers, have come and engaged with the space. Can you elaborate a little bit more about the relationship between art and science in our understanding of the world or in how we observe the world?


JJ: Yeah, I think that there are many different forms of positive interactions. I think the practice of science can be done as an art, some aspects of it. For example, clear writing is an art. And the creation of intelligible tables and comprehensible graphics and maps can have elements of artistic principles in them. They're not fine art, but still. So I think that science is more effective when it is done with attention to some of the principles that also govern artistic endeavors. But I also think that an artistic perspective, as I 00:41:00mentioned before, which is one of careful observation and depiction of the world around us that that's very similar to the process that I feel that I pursue in my own science. So I think that the partnership can be a really strong one.

SK: Alright, so that concludes the first section. We will go into this next section a little bit more swiftly through these questions and they generally go a little bit faster. But the next questions are more so on a community level. How these different approaches play a role on a community level at the Andrews forest. So my first question is what role does natural history play in both the 00:42:00historical and current state of the community?

JJ: Well, in my view, natural history is absolutely fundamental to the work at the Andrews Experimental Forest, and it is also fundamental to the underpinnings of long-term ecological research as an endeavor. So, do you want me to say more about that?

SK: Maybe if you can describe how it's contributed if you have any specific examples to some of the research that's come out of the Andrews Forest?

JJ: Well, one of the fundamental principles that has emerged not just from the Andrews Forest, but all kinds of long-term ecological research, including those sites that have National Science Foundation funding and sites that just do long-term ecological research, is the importance of history, including the 00:43:00concepts of biological legacies, for example, or physical legacies, such as past disturbances and how they shape the way to ecosystem response and changes over time. So I think an awareness of those past events is typically inferred or intuited or not usually intuited but inferred from careful observation and natural history reconstruction methods. But also that knowledge or that perspective, I think is integral to any science conducted at a long term 00:44:00ecological research site being able to be aware that the process that you're observing today and in this location is in some census tied to a distant past, in that place and to a much larger area and to that much larger area in the distant past. And so that is a key element of what I would consider being the most helpful research perspective at the Andrews Forest and also it's a big part of the teaching of students who come to the Andrews Forest in classes or REU program [Research Experience for Undergraduates program that is NSF or university funded] or whatever.

SK: Do you think that the importance of natural history is still recognized, or is it waning at all?


JJ: Oh, that's a good question. We do live in an era in which we are somewhat preoccupied probably excessively preoccupied and possibly even distracted by our electronic world. And so I work a lot with students who spend a lot of time looking at the world through a computer where they're observing, you know, layers - geographic information system layers of information. Or remotely sense data. And the students haven't been out to look at the ecosystem. So the classes that I teach and one, in particular, is designed to get students to go out into the ecosystem and to try to look at it themselves directly and remove that 00:46:00interface. And I think that electronic media, on the one hand, our computational power is of great use to us certainly, it's tremendously helpful to me in my own work, but then, the real information comes from the ecosystem. It doesn't come from the computer. So that's a long-winded way of saying that, you know, students or people possibly of your age are those in their 20s and 30s today, who have grown up in an era in which Pokemon creatures are better known than the species of real animals living in your yard has meant that we have sort of lost touch with our connection to how ecosystems really operate. That persists into 00:47:00graduate school where people have a belief which may be the fault of our educational institutions that proficiency in computer technology is the same as learning and that's it's only a part of it, and especially for ecosystems studies. It's quite inadequate. So, people, therefore, you know, for a few decades now, I think the students who have taken my classes wouldn't have been able to tell me what natural history was - they didn't know what the term was. But then when they practice it, they discover or they recognize probably what they knew all along that it's tremendously powerful and then they tell me, "Oh, 00:48:00I'm looking at the world in a completely different way than I used to before." I don't know whether they know that that might be called natural history or not, but they're doing it. So, yes, in answer to your question, I think that our educational systems, primarily because of the role of electronic media and the emphasis on data that is collected and stored on computers have tended to diminish the individual sense of their own power to comprehend the world around them through using their own observational skills and that that is something I try to emphasize in my teaching.

SK: And what are some of the things that make them realize that they're doing natural history. What is it that they're doing? Is it about being outside and observing?


JJ: One of the tools is the notion of multiple working hypotheses. So, you know, you take a whodoneit approach to looking at the world. You don't just look at it and say, oh, that's pretty, you say, why is it the way it is here. And how many different explanations can I think of why this might look the way it does? So I think that's a principal approach.

SK: And what about hypothesis-driven and experimental research. How has it contributed to the Andrews Forest, both in the past and current work?

JJ: Well, I mentioned earlier that a lot of my work has been based on long-term data sets from paired watershed experiments. So I certainly think that the paired watershed experimental approach has been a tremendous contribution to the 00:50:00Andrews Experimental Forest not merely because of the experimental treatments that were imposed, but because of the way in which the continued efforts to measure the ongoing changes and responses in most places have led to some unexpected findings or new questions as time has passed, and also those locations have become a point of connection among scientists from different disciplines. Also, you can cite a fine-scale study within the context of a larger, longer-term experiment, there's a lot of richness in terms of the interpretation you can make from your humble data set. So, from a social 00:51:00perspective, the long term watershed experiments have been extremely valuable and they have also generated many new science questions that were entirely unanticipated by the founders.

Another iconic long-term experiment at the Andrews Forest is the 200-year log decomposition experiment, which also has led to many spin-off projects that were not anticipated by its founder [OSU professor Mark Harmon] and also, because of where it is located, it has become somewhat of an iconic site for the writers in residence program at the Anders Forest. And so it has led to the creation of some wonderful poems and essays that couldn't possibly have been anticipated by 00:52:00the founders. So, I guess I would say an answer to your question is that the experimental treatments themselves and the hypotheses that led them have led to some interesting work over the long term. But mostly it's the fact that the treatments were undertaken and have been continued, which has led to the possibility of unexpected unplanned and unhypothesized outcomes scientifically and socially in our group.

SK: And what about ecosystem modeling and modeling in general, let's say, what, what are some of the fundamental contributions to the Andrews as a whole?


JJ: I don't have a whole lot of exposure to ecosystem modeling. There has been quite a bit of hydrological modeling done with long term records from the Andrews Forest, but I commented earlier that the world in hydrologic models consists of people either who are advocating for trying to develop a particular model and a few others who have maybe a more of a falsification perspective toward models that they're all wrong that maybe some are useful and you can learn some things from them. In terms of ecosystem models. The ones I know about are biogeochemical models that to try to predict things like the export of nitrogen from a watershed. And I think that there is a historical evolution of 00:54:00those types of models, which is a little bit similar to my description about the long term experiments in the sense that I believe that the most successful efforts initially those efforts may have been led by a single individual trying to build a huge, complicated model of everything, but that in recent years, those efforts have become much more collaborative efforts of people trying to exchange and combine their varied perspectives of the different components of an ecosystem that they understand and trying to combine it into a larger picture. And that's really interesting because we typically get told in the reviews of 00:55:00our LTER proposals that we should try to do synthetic modeling and I wonder whether the people who asked that really have an idea of what would be produced, right, because models of everything tend to be models that have so many parameters and so many equations in them that they become somewhat meaningless and so we have not had a lot of effort invested in that direction in our community in the recent past. And I think it's because there's more of a sense of respect or even humility that efforts to create a model of everything or 00:56:00synthetic models might be a doomed exercise for the Andrews Forest.

SK: I wonder where the desire or fixation on going in that direction comes from.

JJ: I think it would be in the peer-review process. You know, we get these questions from people who are anonymous reviewers. But if we had the opportunity, I think I'm increasingly thinking that it would be important to turn that question back and say, well, why do you think this would be valuable. What would you imagine could be gained by such an exercise, rather than saying, "Oh, yes, yes. Well, of course, we will do that because it should be done."

SK: Is that space provided at all. Are you able to have that dialectic 00:57:00conversation with the reviewers?

JJ: We have every six years. Around the middle of each six-year grant [cycle] - in year three -we are visited by a team of reviewers. And under those circumstances, we can have a conversation. So that might happen sometime in the coming years.

SK: I'd be curious to see [their responses].

JJ: Well, you're giving me the courage to take it on.

SK: Because it doesn't. Sometimes what seems to be best may come from a societal expectation and not so much what actually would be best, you, know. Alright, so that leads us to our concluding questions here. We're making good time. What significant ideas have emerged from the Andrews science community and how did the science these ideas of all in terms of questions and methods? So we spoke of a few, but if you have any more. That's come up in your thoughts.


JJ: We spent we've spent some time fruitlessly, well maybe not fruitlessly, but for some years, we thought we ought to write a book about the Andrews Forest. And we had a lot of discussions and we have many drafts Fred has many drafts of versions of the book. But in the conversations that we had about them, I associate this conceptualization with Fred, but it seems to me to be really useful on Fred Swanson, and that is that the science at the Andrews Forest has been evolving and continues to evolve as a result of three different kinds of 00:59:00sets of changes. And those are changes in technology, which provide new forms new sources of data. Changes in the environment itself, which may be due to disturbances, like the fire or past floods, or gradual changes in like climate change. And then changes in society and how we perceive and value ecosystems. So, the significant ideas that have emerged from the Andrew science community have been a reflection of that evolving process in the 1970s at a timeline. Logging of old-growth forest was going full bore. The Andrews Forest researchers 01:00:00began to understand and write about the value of retaining deadwood in [forest] ecosystems and in streams. And at a time when logging was not sparing the riparian zone and trees were being cut all the way down to the stream network, on the role of the riparian zone and definition of that concept. That was a very important finding at a time when landscape-wide logging of all growth cumulative growth was potentially affecting species pioneering work on the spotted owl began to reveal its dependence on these larger-scale processes.

In more my own area, in the early years of the watershed experiments, a 01:01:00principal focus was on water yield and water quality for downstream users, how much water and how much sediment. And then there was a period of time in the 1970s and into the mid-90s when there were episodes of very big flood strain on snow floods and so societal concerns turn to the effects of logging on flooding. But in the last 20 years we have been in a period of climate change when summer temperature has been increasing and summer rainfall has been declining and the plantations, or the planted forest that was created as the result of old-growth logging from the 50s into the 70s in the Andrews Forest or until 1990 in the forest in general, those forests have been growing and using more water and so attention has shifted to drought or hydrological drought, which is lack of water 01:02:00during the hot, dry season and also the long term studies of how ecosystems retain carbon have been a very important component of the Andrews Forest because they store so much carbon and the way in which that carbon is retained rather than exported from the system remains, in some senses, an open question. So there are so many questions. Climate change is emerging and spatial variability is an important area. I'm sure my list is quite incomplete.


SK: And with all those in mind. What would you say are the unique principles and motivating forces that drive the Andrews as a community?

JJ: I think people are drawn to the Andrews Experimental Forest and LTER community because it is fundamentally so much more satisfying to do your personal science in the context of a community that can react to and be interested in your work and gives you ideas about how to push it forward. So the benefits to the participants in the community are the community itself. And, also, I think the community shares perhaps reverence is to maybe not too strong 01:04:00a word, a reverence for the ecosystems themselves and a sense of an abiding curiosity about how they function and a sense of humility about what we don't understand about them and a dedication to the notion that more can be learned, by continued observation of those systems. So I think that the principles of open sharing and collaboration, which can be quite challenging at times. Are a very important element of the community and that it is healthy, as long as that principle is respected, but if it were to be not respected and people were 01:05:00excluded or then the community would pretty quickly unravel. So I think I also think that genuine interest in one another's work and the desire to learn what each other is learning is a key piece that knits together the community because people feel that their ideas are of value and that their ideas can contribute to benefiting the work of other individuals, but also much more broadly, the way in which the US government stewards the National Forest System and the streams and the water resources and the wildlife resources that are present in those ecosystems.


SK: Well, thank you so much. Are there any final words, you'd like to add?

JJ: No, thank you very much for doing this. I'm very curious to imagine what diversity of perspectives, you may be getting from different people who work with the Andrews Forest. I'm sure that there are as many different perspectives or possibly more different perspectives than individuals whom you have interviewed. Yeah. So I think it'll be very rewarding to see the final outcome of your work. I'm very grateful to you for taking the time and energy to do such a thoughtful job. Thank you.

SK: I appreciate it. It's been very fun so far.

JJ: Well, that's great. Yeah.