Research Questions: How do altered soil moisture and nutrients influence the microbial community composition of a degraded dryland soil? Does the altered microbial community composition affect native plant germination and growth? Project Description: Claire Karban designed this field experiment and we set it up Fall 2020. Claire is testing various approaches to dryland restoration including soil pitting (shown in the photo above), biochar, and seed coating. I am curious whether these treatments have an indirect effect on native plant establishment through altering microbial communities. In particular, we expect that the pits will improve soil moisture status and will collect nutrients via dust collection. This may alter the microbial community structure. We would also like to know whether that altered microbial community structure contributes to seeded plant establishment. In the spring, I will be collecting soils from the pits, from control plots, and from healthy nearby soils. I will be extracting an intact microbial community (using methods from Corinne Walsh in Noah Fierer's Lab) from each soil type, applying them to the native seeds we used in the field experiment, and measuring plant growth in growth chambers and in the greenhouse. I will follow-up with marker gene sequencing for both bacteria and fungi. I'll link my findings to the field site, where Claire and Sallie will be measuring plant success (plant densities and biomass) for each treatment as well as fungal infection rates. Our overall goal is to improve dryland restoration strategies in ways that can be used at a large-scale.
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Research Question: What are the microbial community outcomes of using an assisted migration strategy for biological soil crust restoration with inocula from three different North American deserts and cultivation at a single site on the Colorado Plateau? Project Description: Working with the USGS in Moab, I will be assessing the microbial community composition of inocula that was created as a mix of various intact biocrust communities from the Colorado Plateau, Mojave, and Sonoran Deserts. This inoculum was cultivated in the Colorado Plateau, so we might expect the inoculum to become more similar, genetically, to other local communities. Alternatively, we might predict that the more tolerant hot-desert microbes from the Sonoran Desert could out-perform those of the Colorado Plateau. If that is the case, then there may be promise for using this assisted migration technique in biocrust restoration projects.
Research Question: What is the relationship between chlorophyll a production, exopolysaccharide content, and soil stability in early stage biological soil crust? Project Description: As researchers move beyond cover estimates for cyanobacterial presence in biological soil crust communities, it is not clear how to efficiently measure cyanobacterial abundance. Often, researchers use chlorophyll a content or exopolysaccharide content. The relationship between these variables as well as to soil stability during very early biological soil crust establishment is under-studied and will greatly enhance our understanding of microbial ecology in these environments.
Research Question: How does each stage of biocrust restoration influence microbial community composition? Project Description: Often biocrust restorations fall short of expectations, with the inoculum often not growing rapidly enough in the field to remain long-term at the restoration site. In order to make improvements, we are assessing microbial community composition throughout the entire process to learn how our manipulations affect the microorganisms and at which steps we should make adjustments. This project involves sequencing microbial communities, extracting their chemical products, and thinking about their ecosystem functions once deployed at the restoration site.
Research Question: Does the spatial scale of disturbance influence the rate of recovery of biological soil crusts? Project Description: If you walk through the desert, there may be signs warning you "Don't Bust the Crust". You might think to yourself, how much damage could a single footstep cause? Biocrust recovery rates depend on disturbance types, water availability, and propagule availability, so sometimes recovery can take a few years and sometimes in can take centuries. This project looks at the rates of biocrust recovery for small plots vs. large plots to determine if there are differences. This will help inform dryland restoration efforts and their strategies for large and small scale disturbances. Links to presentations
The next 9 blog posts will summarize my reading assignments for the EBIO 3rd semester exam. The exam is scheduled for 3 hours and involves my four committee members asking me questions about anything at all! I was required to put together a reading list covering 4 main topics: biological soil crusts & drylands, microbial ecology, ecosystem services, and community, restoration, and disturbance-succession ecology. Obviously, I actually have 7 topics, which I managed to squeeze into "4". The reading list is a guide for the exam. To help me through this exam preparation process, I will use these blogs to summarize what I am learning over the next 9 weeks.Environmental variability (pros and cons)
My last 6 readings of the restoration ecology section were assigned by Laura Dee, a faculty member who specializes in ecosystem services. They are all recent publications and most had a controversial message. Two of the papers presented frameworks for ecological stability. Stability is an important concept because it is generally what we hope ecosystems will have in the face of disturbances. Disturbances can be of many types and so they have different magnitudes, directions, frequencies, and variability over time. In response to a disturbance, ecosystems can have at least 5 different qualities that contribute to their overall stability: resistance, resilience, variability, robustness, and persistence. Donohue et al. (2016) suggest that studies need to address all of these components (multidimensional perspective) so that we have more continuity across fields for what "stability" actually means. This paper has grounding in policy, motivated by the idea that policy can be improved by more direct language and linkages to underlying science. This paper was also super useful because it showed theoretical graphs of disturbances (presses and pulses) compared to actual measured disturbances for wildfire, nitrogen deposition, and disease outbreaks. None of the real disturbances matched the simple theoretical versions. Alternatively to this, Ninmo et al. (2015) take a resistance-resilience framework (only two components of Donohue's framework). For Ninmo, resistance and resilience can be measured at any biological level (a single molecule, individual organisms, or communities). In this paper, resistance and resilience are actually calculated (based on an initial condition) and then graphed. In relation to the last blog post, one might expect a shift to an alternative stable state when the resistance and resilience of the system are both low. There are some limitations to their approach, but overall, the framework allows us to predict how certain traits of species, populations, or communities might respond to disturbance, which is super useful. Donohue's paper indicates that there is a lot of scientific evidence that biodiversity loss reduces productivity and other resource utilization rates. At the same time, though, we do not know the mechanisms for how biodiversity affects ecosystem services. In Bullock et al. (2011) this is even more clear. They discuss how restoration for biodiversity and for ecosystem services should be two separate endeavors since the links between the two are not certain and not always positive. It may be that restoration goals for these two will align but sometimes they will conflict. Cost-benefit analysis is recommended and they encourage researchers to consider how Payment for Ecosystem Services (PES) could fund restoration. This approach is limited because we really do not have good documentation of how much restoration costs. Of 200,000 restoration case studies, only 96 had associated cost information. This approach is also complicated because you have to be able to value every part of the process, you need willing buyers and sellers, there may be a skew to certain types of services and not others, and there may be inequities in the implementation. Who gives up land? Who benefits from the service? One of the controversial papers I read was lead by the Chief Scientist of the Nature Conservancy, Hugh Possingham (2015). In this paper, Possingham addresses the common perception that land protection is preferable to restoration for conservation goals. The mainstream view is that protection leads to superior outcomes, is associated with lower costs, and has no time delay. Using some simple models, the authors show that in some cases restoration is better than protection. In their example, after 30 years a restoration approach did not have as much protected land, but it did have less degraded land compared to the protection approach. Importantly, throughout their models, it was never optimal to fund both protection and restoration at the same time. Sometimes it was best to protect for some time (say 20 years) and then switch to restoration. The field of restoration ecology would really like to move toward prediction (being able to use a model to make decisions in a scientific way) and this was a step in that direction. The other controversial paper I read touched on the common perspective that we should increase monitoring for conservation. This is a dominant idea in the science-policy reports I read. We need more monitoring! McDonald-Madden et al. (2010) show how someone can use a decision tree to guide decisions about monitoring. Sometimes monitoring can yield unforeseen outcomes with broader impacts that initially intended. On the other hand, monitoring can be very expensive and not worth the effort. Sometimes I think about this for the herpetology monitoring I did in Southwestern WY for two summers. We were able to regularly find amphibians (since they are concentrated in particular habitats at certain times of the year), but snakes were rare. I shudder to think about who may be using that data now as a baseline for future herpetological surveys...no snakes in the area in 2014, and no snakes now. The last paper on this list introduced the term "recovery debt". In their meta-anlaysis of 350 studies, Moreno-Mateos (2017) showed that during recovery there are 50% fewer organisms, 30% less diversity, 35% less carbon and nitrogen cycling. These differences are known as the recovery debt and the authors argue that restoration/offsetting are inadequate to ecosystem protection (an opposite view from Possingham et al. above). In the studies they looked at, the authors found that restoration takes 22 years on average and that recovery from anthropogenic disturbances are worse than recovery from natural disturbances (on multiple measures). Overall, restoration literature is very interesting to me. I like that some people approach it with math, others with theory, and others with applied experience. In EBIO at CU, there is a restoration club that guides volunteers and students on restoration efforts throughout the year. I look forward to the end of the pandemic when I can get involved and see restoration efforts for myself. It is one thing to read these papers and theorize about how ecosystems work. It is another to be in it, pulling each weed, one by one. References McDonald-Madden E, Baxter PWJ, Fuller RA, Martin TG, Game ET, Montambault J, Possingham HP (2010) Monitoring does not always count. Trends in Ecology and Evolution, 25(10):547–550. https://doi.org/10.1016/j.tree.2010.07.002 Nimmo DG, Nally R Mac, Cunningham SC, Haslem A, Bennett AF (2015) Vive la résistance: Reviving resistance for 21st century conservation. Trends in Ecology and Evolution, 30(9):516–523. https://doi.org/10.1016/j.tree.2015.07.008 Possingham HP, Bode M, Klein CJ (2015) Optimal Conservation Outcomes Require Both Restoration and Protection. PLoS Biology, 13(1):1–15. https://doi.org/10.1371/journal.pbio.1002052 Donohue I, Hillebrand H, Montoya JM, Petchey OL, Pimm SL, Fowler MS, Healy K, Jackson AL, Lurgi M, McClean D, O’Connor NE, O’Gorman EJ, Yang Q (2016) Navigating the complexity of ecological stability. Ecology letters, 19(9):1172–1185. https://doi.org/10.1111/ele.12648 Bullock JM, Aronson J, Newton AC, Pywell RF, Rey-Benayas JM (2011) Restoration of ecosystem services and biodiversity: Conflicts and opportunities. Trends in Ecology and Evolution, 26(10):541–549. https://doi.org/10.1016/j.tree.2011.06.011 Moreno-Mateos D, Barbier EB, Jones PC, Jones HP, Aronson J, López-López JA, McCrackin ML, Meli P, Montoya D, Rey Benayas JM (2017) Anthropogenic ecosystem disturbance and the recovery debt. Nature Communications, 8:8–13. https://doi.org/10.1038/ncomms14163 The next 9 blog posts will summarize my reading assignments for the EBIO 3rd semester exam. The exam is scheduled for 3 hours and involves my four committee members asking me questions about anything at all! I was required to put together a reading list covering 4 main topics: biological soil crusts & drylands, microbial ecology, ecosystem services, and community, restoration, and disturbance-succession ecology. Obviously, I actually have 7 topics, which I managed to squeeze into "4". The reading list is a guide for the exam. To help me through this exam preparation process, I will use these blogs to summarize what I am learning over the next 9 weeks.
Ecosystem resilience: "the magnitude of a perturbation that a system can withstand before undergoing a shift", or sometimes, "the time it takes for a system to recover from a perturbation". My reading this week addressed all sorts of factors related to this resilience concept. Specifically for soil microbial communities, Shade et al. explained individual-, population-, and community-level characteristics (dormancy, dispersal rate, turnover rate) that contribute to microbial community resilience and thus stability over time. Viewed from a different perspective, ecosystems can also be resilient to restoration (Suding et al. 2004). Sometimes there are feedbacks that increase the resilience of degraded systems: species effects, trophic interactions, landscape connectivity and seed source, and long-term change. As an example, Suding et al. talk about how grasses invaded Hawaiian shrublands, making the landscape more fire-prone, which allows more fires and thus more grasses. This positive feedback makes the ecosystem more resilient to your restoration efforts because it is internally-reinforcing. Getting the shrubland back in a self-sustaining form may be very tricky. Two papers by Suding et al. set up an important framework for understanding restoration through alternative states, positive feedbacks, and threshold models. These theories are quite complex with mathematical underpinnings and applications through models, but I constantly remind myself of the simplicity of the ideas when boiled down...for example, do we add gravel, grass-clippings, or living plants to stabilize a soil surface and increase soil moisture availability? The theory becomes important when you have asked this same question over and over again in different contexts and you'd probably prefer to know for sure which option is the best one for your particular context. The theory is also important when our restoration efforts start to falter due to complexities that we did not account for. Restoration is going to continue to be extremely important into the future and hopefully it will play a big role in my work, so it is critical for me to understand the fundamental theory in the field. Succession is the dominant model used in restoration. Succession is the orderly progression of community shifts toward a climax community (often discussed in terms of vegetation) with early successional species facilitating the colonization of later successional species. If ecosystems all follow successional patterns, it makes sense that you could encourage ecosystem recovery through restoration actions by following the known sequence of succession for that environment. In Read et al., this idea was tested specifically in biocrusts. They used a space-for-time substitution (they found crusts that were 0-50+ years old) and looked at the community composition, species traits, and functions to show that there were specific species traits that made them good at being early or late successional species. They also found that biocrust cover increased (after grazing disturbance) up to 20 years later, but that the community composition never stabilized (reached a climax community). Therefore, the successional model does not quite fit. Many other researchers have found fault with a successional model for restoration. For instance, an alternative perspective would be the stepwise degradation cycle (King & Hobbs 2006) which divides degradation into abiotic, biotic, structure, and function categories. The degradation spiral they show indicates important points of action for restoration which push back against the positive feedbacks that cause the spiral, hopefully by pushing on multiple steps at once and in a way that minimizes the spatial scale of interactions. Building on this perspective, Suding et al. prefer to think of a degraded state as an alternative state (two or more different communities can exist on the same patch of land equivalent environmental conditions). This is important to distinguish from a gradual or threshold type of degradation. In a threshold model, there is a steep point at which the community shifts due to environmental factors, but the way back to the prior state is along a continuous known trajectory. In alternative state models, hysteresis occurs such that there may not be an easy route back to the prior state. This is important to know if you are a land manager spending a lot of money on a restoration project because the best path forward may be quite complex. A land manager might know if thresholds or alternative states are occurring using monitoring, identifying examples of rapid change through measurements, and looking at the shape of the stress/time curve. Another way suggested in the literature is to look for sharp spatial boundaries in community composition or function without a measurable boundary in the environmental parameters. There are other factors that may deter a well-planned restoration effort. Stuble et al. 2017 show that the outcomes of restoration efforts are highly dependent on the spatial and temporal context in which they were implemented. In their experiment, 3 different sites were "restored" in the exact same way for 4 years. After two years of growth, each plot's community stabilized and that final community composition was highly dependent on the site and year. This is something dryland restorationists know all too well because the success of their efforts highly depends on how good a water-year it is at their site. In another study, Winkler et al. (2018) further explain how restoration on the Colorado Plateau can be unique. Not only are their diverse and intense land uses across many different land ownership agencies, but there are also strong abiotic gradients and heterogeneous geomorphology which all impact restoration efforts. In this paper, two successful restoration efforts on the Colorado Plateau are described (one for graminoid grass establishment and one for native grass seeding to prevent invasive species growth). They predict that we can have more successful restoration there if we use sustained, strategic programs, targeted and evolving restoration practices, long-term monitoring with adaptive management, land-scape scale collaboration, and a willingness to change old practices. These final ideas are contested in the next blog post. References Community Ecology. Second Edition. Gary G. Mittelbach and Brian J. McGill 2019 Oxford University Press. King, E.G. & Hobbs, R.J. 2006. Identifying linkages among conceptual models of ecosystem degradation and restoration: Towards an Integrative Framework. Restoration Ecology 14(3), 369-378. https://doi.org/10.1111/j.1526-100X.2006.00145.x Read, C. F. et al. 2016. Testing a model of biological soil crust succession. Journal of Vegetation Science, 27, 176-186. https://doi.org/10.1111/jvs.12332 Shade, A. et al. 2012. Fundamentals of microbial community resistance and resilience. Frontiers in Microbiology, 3(417). https://doi.org/10.3389/fmicb.2012.00417 Stuble, K.L. et al. 2017. Every restoration is unique: Testing year effects and side effects as drivers of initial restoration trajectories. Journal of Applied Ecology 54, 1051-1057. https://doi.org/10.1111/1365-2664.12861 Suding, K.N. et al. 2003. Alternative states and positive feedbacks in restoration ecology. TRENDS in Ecology and Evolution 19(1). https://doi.org/10.1016/j.tree.2003.10.005 Suding, K.N. & R. J. Hobbs. 2009. Threshold models in restoration and conservation: a developing framework. Trends in Ecology & Evolution 24: 271– 279. https://doi.org/10.1016/j.tree.2008.11.012 Winkler, D.E. et al. 2018. Beyond traditional ecological restoration on the Colorado Plateau. Restoration Ecology 26(6), 1055-1060. https://doi.org/10.1111/rec.12876 The next 9 blog posts will summarize my reading assignments for the EBIO 3rd semester exam. The exam is scheduled for 3 hours and involves my four committee members asking me questions about anything at all! I was required to put together a reading list covering 4 main topics: biological soil crusts & drylands, microbial ecology, ecosystem services, and community, restoration, and disturbance-succession ecology. Obviously, I actually have 7 topics, which I managed to squeeze into "4". The reading list is a guide for the exam. To help me through this exam preparation process, I will use these blogs to summarize what I am learning over the next 9 weeks.
You know those pictures of hydrothermal vents deep in the ocean? The ones where hot water spews forth and only the most badass life forms survive there? I never knew that the hot water causes mineral reactions that produce light. Hydrothermal shrimp have light sensing organs to detect this light (either for gathering food or for avoiding the hot water) and green sulfur bacteria have the ability to use this light to photosynthesize (without sunlight) deep in the ocean. During my reading this week, I realized I should take a moment to review photosynthesis in bacteria. Plants are the most well-known photosynthesizers, producing their own biomass from carbon dioxide, water, and light. Chlorophyll is the light collecting compound in their cells, and it is green. Cyanobacteria are able to carry out this same type of photosynthesis, and there are evolutionary links between the free-living cyanobacteria and the chloroplast in plant cells. There are other ways to photosynthesize, that replace each of the three ingredients described above with alternatives. For instance, a bacteria might use hydrogen sulfide instead of water in the reaction (purple sulfur bacteria) or hydrogen (purple non-sulfur bacteria). Instead of using sunlight, the green sulfur bacteria can use the light from a hydrothermal vent (and sulfur). Some bacteria do not obtain carbon from CO2 (inorganic), but instead use carbon compounds that they must "consume". These are photoheterotrophs. And some bacteria can switch between these different photosynthetic forms. The Cyanobacteria found in biological soil crusts use the typical plant-like photosynthesis, as do the mosses, lichen, algae, and bryophytes. There may be many photosynthesizers in the biocrust community. Like plants, these organisms compete for resources (light, water, nutrients) and often, their ability to gather these resources depends on their ability to take up space. And that has a lot to do with how organisms operate in a community context... This week's reading was primarily focused on the book Community Ecology by Mittelbach. Community ecology is "the branch of science focused...on understanding Earth's biodiversity, including the generation, maintenance, and distribution of life in space and time". I need to be familiar with this field because biological soil crusts are communities of many species, and there is a long history of theories and conceptual frameworks in this field that help scientists think through their scientific questions about communities. So I have been learning the history of this field, the main questions that have been asked and investigated, the most important debates, and where the field is currently headed. Topics in this book include patterns of biological diversity, biodiversity and ecosystem functioning, population growth and density dependence, the fundamentals of competitive interactions, species coexistence and niche theory, beneficial interactions in communities: mutualism and facilitation, etc. Suddenly this week it became much easier to get through my readings. A 12-page scientific paper seems do-able. A chapter in the Mittelbach book does not feel ghastly. I suppose this is part of the exam outcomes. Being able to not only select useful papers, but also to read them efficiently and then communicate the information to others or apply it to your work. The papers I have been reading are mostly about restoration ecology. The first paper, Copeland et al. 2018, introduced me to the Land Treatment Digital Library which stores over 70 years of land treatment data. The paper assessed trends in restoration over time, showing that the CO Plateau has seen the most treatment and that the most common treatments are seeding or vegetation/soil manipulations. Other types include herbicide/weed removal, prescribed burns, closure/exclosure, and soil stabilization. In more recent years, treatments have shifted toward fire and invasive species control. Treatments have become larger and more expensive over time. In addition, for seeding treatments, we now seed with more species (average of 2 plant species per treatment to 8 species per treatment now). Still, only 10% of treatments saw monitoring afterward. This is something the Barger Lab talks about a lot and we are working on projects with the BLM where we rely on each other's expertise: they implement land treatments while we do monitoring and scientific assessment. One way to deal with the increasing costs of restoration was dealt with in a second paper (Hulvey et al. 2017) which encourages the use of restoration islands (even in drylands). The idea is that you concentrate restoration efforts in locations that are most likely to succeed (small islands). The goal may be that these islands spread over time, or it could simply be a goal that they persist, acting as refugia, corridors, nurseries, firebreaks, or genetic repositories. The James et al. paper was challenging for me. The main idea was that we need to shift ecosystem models away from qualitative (descriptive) formats and toward quantitative formats that can help us predict restoration outcomes. This makes sense to me theoretically, but I am not sure how to practically make this happen in every restoration context. The one they show in the paper includes some 40+ processes which would need to be quantified for a complete system model. Only then would you be able to plug in restoration outcomes (which would probably still be incorrect) to the economic options to select a path forward. I don't see this working in the field as described. Finally, I read a great paper about soil microbial succession after a heat shock disturbance (Jurburg et al. 2017). The authors tracked microbial communities over 50 days and used various statistical techniques to classify bacterial groups into recovery types as well as classifying the entire community into restoration phases. Their community was able to recover after the heat shock and they described this as conventional recovery for a resilient community. Throughout this paper I imagined how I would transfer the methods to my soil microbial system with different disturbance types and assisted recovery instead of natural regrowth. It is quite complicated. It may be easier to do this type of basic science with a model system in a laboratory setting... The one non-restoration paper I read this week was by Matt Bowker's group (2014) on how biological soil crusts could be a model system. Models in biology are usually organisms or systems that can be easily manipulated for experiments because they are simpler, smaller, faster, or more general than others. Examples include Darwin's finches for natural selection, water boatmen for niches, diatoms for resource competition. The paper argues that biological soil crusts can be a model system for many ecological questions related to community ecology and ecosystem ecology. All of the examples given in the paper excite me and it seems reasonable to me that we could use biocrusts as a model in particular contexts (despite them not being very simple with slow growth). The rest of this week, I continue with community ecology, restoration ecology, disturbance-succession topics. References Bowker, M.A. et al. 2014. Biological soil crusts (biocrusts) as a model system in community, landscape and ecosystem ecology. Biodiversity and Conservation, 23, 1619-1637. https://doi.org/10.1007/s10531-014-0658-x Community Ecology. Second Edition. Gary G. Mittelbach and Brian J. McGill 2019 Oxford University Press. Copeland, S.M. et al. 2017. Long‐term trends in restoration and associated land treatments in the southwestern United States. Restoration Ecology 26(2), 311-322. https://doi.org/10.1111/rec.12574 Costantini, E.A. et al. 2016. Soil indicators to assess the effectiveness of restoration strategies in dryland ecosystems. Solid Earth, 7, 397-414. https://doi.org/10.5194/se-7-397-2016 Hulvey, K.B. et al. 2017. Restoration islands: a tool for efficiently restoring dryland ecosystems? Restoration Ecology 25(S2), S124-S134. https://doi.org/10.1111/rec.12614 James, J.J. et al. 2013. A systems approach to restoring degraded drylands. Journal of Applied Ecology, 50, 730-739. https://doi.org/10.1111/1365-2664.12090 Jurburg, S.D. et al. 2017. Autogenic succession and deterministic recovery following disturbance in soil bacterial communities. Scientific Reports. https://doi.org/10.1038/srep45691 |
AuthorSierra is a graduate student in the Barger Lab at CU Boulder studying microbial ecology for dryland restoration. Archives
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