Agenda/Schedule
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Irreversible Processes in Ecological Evolution
From Complex Time
Category: Application Area Application Area: Ecology
Date/Time: January 29, 2019 - January 31, 2019
Location: Santa Fe Institute (Noyce Conference Room)
Organizers
Jacopo Grilli (ICTP)
Dervis Can Vural (Univ. Notre Dame)
Attendees
Priyanga Amarasekare (UCLA)
Fernanda Valdovinos (Univ. Michigan)
Meeting Synopsis
An ink drop placed in water will dissolve and homogenize, never to return back to its original state. Many-body processes involving stochastic forces universally and irreversibly lead to entropy maximizing distributions. This working group aims to ask what the analog of ‘dissolving ink’ is in the context of ecological evolution. Specifically, this WG will explore irreversible changes in the ecological interaction structure and their consequences. Of particular interest are theoretical frameworks that incorporate dynamics as well as experimental approaches that can track irreversible transitions in strongly interacting populations. Key foci for this WG are the directionality of the coevolution of interspecific interactions and ecological transitions, and the synthetic control of such transitions.
Abstracts by Presenters
Samraat Pawar (Imperial College London) - Are changes in species interactions and their ecosystem consequences irreversible?[edit source]
All interactions between individuals of the same or different species (populations) are metabolically-constrained. That is, the rate of an individual's energy use (metabolic rate) sets the rate of interactions with other individuals. In this talk, I will first describe the relationship between metabolic and species interaction rates as a function of the physical environment as well as the organism's mass, using ecological metabolic theory. I will then describe the effects of (metabolically-constrained) species interactions on the dynamics of ecosystems. Finally, I will consider whether changes in metabolically-constrained species interactions are irreversible.
Dervis Can Vural (Univ. Notre Dame) - Cooperation and specialization in dynamic fluids[edit source]
Community ecology is built on the notion of interspecies interactions. The strengths of interactions are almost invariably taken as fixed parameters, which must either be measured or assumed. The few available models that do consider the formation and evolution of interactions, including some built by myself, are based on ad hoc definitions of fitness. In this talk I will present a first-principles approach to how interactions between and within species change. In this picture, the black box of "interspecies interactions" will be replaced with advection, diffusion, dispersal, chemical secretions and domain geometry. I will show that the fundamental laws of fluid dynamics and the physical parameters describing the fluid habitat determine whether species will be driven towards individualism, social cooperation, specialization, or extinction. I will end my talk by proposing ways to tailoring the interaction structure of a microbial community by manipulating flow patterns and domain geometry.
Otto Cordero (MIT) - Cooperative growth and cell-cell aggregation in marine bacteria[edit source]
Bacterial cooperation, whereby cells secrete compounds that can facilitate the growth of neighboring cells, has been extensively studied through the lens of evolutionary biology. However, the environmental implications of cooperation and the ecological scenarios under which it takes place remain much less understood. In this talk I will discuss the conditions under which cooperative growth emerges in microbial populations that degrade complex organic materials in the ocean. I will show that organisms that are poor secretors of hydrolytic enzymes use chemotactic behavior to form cell-cell aggregates that enable individuals to increase local concentrations and efficiently uptake the solubilized organic matter. By contrast, when organisms secrete highly active enzymes dynamics turn competitive, cells avoid aggregation and the efficiency of carbon uptake drops. I will also discuss the theoretical limits of aggregation and how bacterial isolates from the ocean overcome these limits in the laboratory by developing multicellular behaviors. I will back up these results with theory, data from individual based models and experiments with natural isolates. Finally, I will discuss the potential role of social cheaters in the natural environment, based on a study with hundreds of micro-scale particle colonization experiments in natural seawater.
Annette Ostling (Univ. Michigan) - Emergent structure and dynamics in stochastic, open, competitive communities[edit source]
Here I describe recent theoretical work by my lab looking at the emergent patterning in models where niche differentiation acts in concert with drift and immigration, as well as empirical work looking for that patterning. The results of our study of “stochastic niche communities” provides further generalization of the recent theoretical developments suggesting that niche differentiation may actually lead to clusters of species similar in traits, in contrast with traditional expectations of even spacing or overdispersion. These traditional expectations are derived from models ignoring stochasticity and immigration as well as other factors. I will review both classical and more recent theoretical developments along the way. We also find niche differentiation plays a more complex role in species persistence in stochastic niche communities than classically expected, enhancing persistence of a select few species, and lessening the persistence of others. We have also demonstrated the occurrence of this pattern of clusters across an array of niche mechanisms, and groundtruthed metrics for its detection in field data. Finally, we have applied our metrics to trait and abundance data for tree species in the 50 ha plot on Barro Colorado Island, and find significant clusters in four traits linked to niche axes. I will discuss all of these developments and also highlight connections to the question of irreversibility in the ecological and evolutionary dynamics of competing species.
Jacopo Grilli (ICTP) - Higher-order interactions, stability across timescales, and macroecological patterns[edit source]
The difficulty of reconciling the staggering biodiversity found in tropical rainforests with classical theories of resource partitioning has led ecologists to explore neutral theories of coexistence, in which all species are assumed to have the same physiological parameters, and variations in species abundance arise from stochastic fluctuations. Here we propose a theory of coexistence in which all species have different physiological rates, and interact with each other through a network of competitive interactions. We show that our models produce robust coexistence of many species even when parameters are drawn at random. Importantly, the dynamical stability of our models is due to higher-order interactions — interactions involving more than two species at a time. Moving from deterministic to stochastic models, we find that the presence of higher-order interactions, which make equilibrium points attractive, dramatically increases the time to extinction in isolated systems, allowing for the prolonged coexistence of species. When we let the system evolve, we recover many empirically observed macroecological patterns.
Fernanda Valdovinos (Univ. Michigan) - Irreversible processes in ecological networks[edit source]
Inspired by the exciting topic of this workshop, my talk will present research by my group that have found irreversible processes in the ecological and evolutionary dynamics of species-interaction networks. The first work I will present evaluates the interplay between the structure and dynamics of plant-pollinator networks when population and behavioral dynamics are incorporated in more mechanistic models of those networks. I will focus on the irreversible dynamics caused by adaptive foraging that may explain why we only observe moderately connected plant-pollinator networks in nature even when pollinator would benefit from fully connected networks. The second work I will present predicts the invasion success of pollinators in plant-pollinator networks and their subsequent impacts on natives. I will focus on the impacts that can and cannot be reversed by restoration practices seeking to remove the invasive species. The third work I will present evaluates the interplay between economic and ecological dynamics governing fishing effort in harvested food webs. I will focus on the irreversible transients that cause a fisheries industry to either thrive or collapse, the harvested species to either go extinct or persist, and food webs to suffer either dramatic cascade extinctions or sustainable harvest. Finally, I will present our work on the evolution of food webs integrating population, speciation and invasion dynamics over evolutionary timescale. I will focus on the irreversible extinctions patterns and whether the specialization tendency found can be reversed by increasing the frequency of perturbations. In my presentation of each of those four projects I will share with you what I still do not understand to hopefully ignite insightful discussion on the specific subjects.
Greg Dwyer (Univ. Chicago) - Natural selection, population cycles, and climate change in forest insects[edit source]
Cyclic outbreaks of forest insects devastate forests, leading to widespread defoliation and tree death. Outbreaks would be far worse if not for epidemics of fatal virus diseases, which decimate outbreaking insect populations. The selection pressure imposed by these diseases suggests that natural selection may affect outbreaks, but understanding such effects is impossible with data alone. My lab has therefore used a combination of field experiments and models to test for effects of selection on outbreaks. Our work shows that both heritable host resistance and variation in viral virulence strongly affect outbreaks of the the gypsy moth, Lymantria dispar, an introduced pest of eastern hardwood forests in North America. Over the last few decades, however, an introduced fungal pathogen has competitively displaced the virus. The fungus provides better control, but its survival is much higher when the weather is cool and wet, whereas climate change is likely to cause weather conditions in the range of the gypsy moth to become increasingly hot and dry. By again combining models and data, we have shown that climate change will have a strong negative effect on the gypsy moth fungus, which may lead to the devastation of hardwood forests in North America. A key question is therefore, can the virus make a comeback? Our answers to this question are as yet incomplete, but provide initial chapters in an interesting story about the ecological effects of climate change.
Pamela Martinez (Harvard) - Pathogen diversity and negative frequency-dependent selection: consequences for intervention[edit source]
Understanding how populations respond to selective pressures is an active area of research, of particular relevance for pathogens, which often adapt after the implementation of epidemic control strategies. Yet attempts to anticipate how and when these populations will evolve, are challenging. By looking at population diversity of rotavirus and Streptococcus pneumoniae, we have explored the impact of negative-frequency dependent selection, which tends to confer an advantage to the rare and a disadvantage to the common, in the response to intervention. Our results emphasize the resilience to control measures, and thus low vaccine effectiveness, in pathogens for which frequency-dependent selection is a key driving force.
Priyanga Amarasekare (UCLA) - Phenotypic evolution in the Anthropocene[edit source]
Phenotypic traits constitute the interface between the organism and the environment. Adaptive evolution occurs when trait responses to the environment maximize fitness subject to constraints. These constraints can be morphological, biochemical or genetic. On the one hand, evidence of rapid evolution in response to environmental perturbations (e.g., pollution, habitat degradation, climate warming) suggests that evolution in response to these novel selection pressures can proceed unconstrained. On the other hand, evidence of extinctions and disruptions of species interactions suggests that constraints can impede evolution in response to novel selective regimes. There is much we do not understand about the interplay between selection and constraints, particularly in light of anthropogenically-induced selection regimes. I am particularly interested in the role of biochemical constraints in reaction norm evolution. This interest is fueled by my work on temperature effects on ectotherm life history, population dynamics and species interactions. I want to gain a mechanistic understanding of biochemical constraints all the way from protein folding to enzyme kinetics so that I can incorporate these mechanisms into models of reaction norm evolution. There is a great deal I do not understand about these processes themselves and how they translate into the mathematics of population dynamics. I do, however, entertain some speculations about the role of how biochemical constraints in irreversible outcomes in phenotypic evolution.
Stephen Proulx (UCSB) - Population genetics of low-probability transitions[edit source]
I will discuss several examples from population genetics and adaptive dynamics where the probability for a transition between “equilibrium” states is very low. These situations can occur when stochastic environmental conditions create scenarios with alternate stable states that can only be invaded by mutations of large effect, for instance in scenarios with overlapping generations and lottery competition. In a similar vein, when mutations of small effect cause intermediate phenotypes with low fitness, transitions can be rare. Another type of transition involves feedback between the environment and the distribution of population phenotypes, for example in terms of the evolution of mating preferences in combination with the evolution of ecological specialization. Yet another scenario occurs when multiple independent mutations are required to cross an “adaptive valley”. This has parallels in ecological theory, for example with the invasion of novel habitats (e.g. zoonotic diseases). I will encourage discussion of how these different concepts and modes of analysis may be extended to situations with eco-evo feedbacks.
Robert Marsland (Boston Univ.) - Statistical mechanics of microbiomes[edit source]
In a seminal paper in 1972, Robert May studied complex ecosystems using Random Matrix Theory. Nearly fifty years later, the rise of quantitative microbial ecology makes it possible to test and refine this approach. Random matrix models successfully capture a wide range of large-scale patterns observed in real microbial communities, including functional and family-level reproducibility, compositional clustering by environment, enterotypes, dissimilarity-overlap correlations, decreased diversity in harsh environments, compositional nestedness, succession dynamics and modularity. After describing the computational model we have developed to reproduce all these patterns, I will present a set of analytic results that explain why this works in the real world. Adding even a small amount of noise to a sufficiently diverse community induces a phase transition to a “typical” phase, where community-level properties such as diversity and rank-abundance curves are indistinguishable from those of a completely random ecosystem. I will explain how the properties of this phase are governed by “susceptibilities” describing the linear response of the ecosystem to small changes in population sizes or resource concentrations. These susceptibilities can be obtained from Random Matrix Theory, in the spirit of May’s paper, and can also be measured by subjecting a community to controlled perturbations.
Post-meeting Reflection by Presenter
Dervis Can Vural (Univ. Notre Dame) - Cooperation and specialization in dynamic fluids Link to the source page[edit source]
To discuss: Could we make a grocery list of all irreversible processes mentioned in the workshop? Few that come to mind immediately: (1) Priyanga's idea on hot to cold invasion (2) Ecological succession. (3) Niche filling (4) something funky happens with the lottery model when there is a big mutation event (is there a name for this? Surely it is a generic thing that can happen in many other systems) (4) formation of interdependences / mutualism / specialization (I will mention in my talk tomorrow) (5) gene duplication (I couldn't follow all there steps here). Anything else I'm missing?
More specific thoughts on individual talks:
Otto Cordero:
Succession of species on hydrogel microspheres. Otto uses spheres with four kinds of nutrition. (1) why are species either specialist (able to digest only one type of sphere) or generalist (able to digest all types). (2) Why don't the cheaters (those who do not produce digestive enzymes) take over. (3) Prima facie, I would expect cheaters to have much lower detachment rate. They should just stick onto spheres and wait for the digestive bacteria to arrive. For the bacteria doing the work a better strategy is to detach quicker, at least before cheaters arrive. Is this observed in experiments? (4) is the interaction between bacteria indirect (i.e. they compete for the same resource) or do they secrete antibiotics or consume one other? (5) what is the role of diffusion lengths? The commensalist bacteria (those who do not secrete enzymes, do not compete for the main resource, but utilize the metabolic byproducts of others) gather whatever they can within diffusion length. So we can calculate the limit the number of layers of bacteria on a surface. For resources (e.g. dead crab shells) that are smaller than the diffusion length, the shape and size of the resource will also make a difference. Also calculable.
Pamela Martinez:
Markov process to describe the spread of pathogen with multiple serotypes (a kind of SIR model). How to differentiate between different models with sparse data. Data could be equally consistent with randomly connected states or even a single Poisson process with appropriate mean. A good suggestion during the talk: generate synthetic sparse data using the model, pretend the data is real, and estimate model parameters. Do they have a similar value? (1) why does the efficacy of vaccines not show up in the population data (they do make a significant difference in controlled studies). (2) why does the vaccine work on some countries but not the others (3) Rotavirus somehow interacts with the gut microbiome. There is some literature that shows that vaccines work for people with microbiomes of the "european kind".
Annette Ostling
Starts with Lotka-Volterra type fitness function. Species are assigned traits between 0-1 and and the interaction matrix is structured such that species with similar traits antagonize each other. This is done with a gaussian kernel in the sum. Questions: (1) what determines the number of clusters. Can I use Turing analysis to solve this analytically? (2) Can I view phylogenetic branches as "clusters"? e.g. animal kingdom, plant kingdom etc. are, in some sense, clusters. And then, there are sub-clusters within these clusters, and sub-sub clusters. What feature should be added to the model to obtain sub-clusters. (3) Given an empirical distribution of features (within a species or within multiple species supposedly filling a niche) how do I distinguish between environmental filtering vs exclusion?
Priyanga Amarasekare: Her argument is, species respond to temperature in an "asymmetric way" (specifically, you hit a wall at high temperatures, but the negative response to cold is more gradual). This leads to an irreversible flow of species (via mutant invasions) from hot regions to cold ones. Comments: (1) I like the idea a lot, very plausible. Here is my alternative (and quite possibly false) point of view: A high population is more evolvable, because there will be more mutants/innovation. Warmer climates have higher biomass (just because it receives more energy) and will therefore generate viable invaders at a higher rate. Maybe.
(2) She had some discussion about constraints vs selection. It's a possible to dichotomize, but I view these two things as one thing. A constrained region in phenotype space is just one with fitness=minusinfinity, so no one visits there. Possibly just a matter of semantics, but in any case, I don't see how a constraint implies irreversibility.
Jacopo Grilli: Three-body interactions surprisingly stabilize the community (unlike those with two-body interactions). I found this surprising because the model with three-body interactions is really an effective model of a two-body interactions. e.g. species A,B,C come together; first A interacts with B, then the winner interacts with C. (and you symmetrize this, because sometimes first A interacts with C first). As such, the outcomes of this model should reduce to a Lotka-Volterra model, (with specific structure, under specific conditions). However, I was not able to figure out what this structure is, and what the conditions are. Whatever the structure and conditions, the stability of the system with three-body interactions should not be a surprise if the equivalent Lotka-Volterra equations are also stable. Either way, I would like to understand this better.
Greg Dwyer: The viruses that infect the pests have multiple DNA's, so I thought that might give rise to an interesting cooperation/cheating dilemma, similar to the one we see in sperm trains. Also there is an interesting three-species coevolution going on between the pests, and the virus and fungus that infect the pests.
Greg likes things he can measure and doesn't like discussing the meaning of life. But then he was converted, and found the meaning of life. Turns out meaning of life is measurable after all.
Jacopo Grilli (ICTP) - Higher-order interactions, stability across timescales, and macroecological patterns Link to the source page[edit source]
Pamela Martinez
Connection between population dynamics and strain diversity. What is the response to pathogen intervention? (clear in a Chessonian framework, unclear when there is strong strain diversity). 1) Rotavirus. Robust antigenic diversity. Estimate of the parameters from cases: G-type strong specific immune response, P-type strong general immune response (concern: very few data, enough statistical power). Surprising: no effect of vaccine/intervention. 2) S. pneumonia. Frequency of strains. How does frequency change after intervention? Replicator model, predicted fitness from genes (how? Not clear): can predict frequencies after intervation (which again does not work). Questions: 1) what determines the equilibrium frequencies of genes? Why loci are under negative frequency negative dependent selection?
Annette Ostling
Stochastic open competitive communities. Niche/unique opportunities/deterministic forces vs chance/neutral/stochastic forces. Finding niche differences is a challenge. Stochastic Lotka-Volterra on 1dim niche axis . Cluster emerge. 1) Metric. What is a good measure of clustering and how is that affected by different mechanisms? 2) Data. BCI and regional pool.
Greg Dwyer
Gipsy moth & virus/fungi. Inference of parameters from time-series. Key ingredient: variability of susceptibility between individuals. Works in reproducing data (but it is hard to predict)
Otto Cordero
Hyper-diversity of microbial communities. How do we interpret that diversity? Patches of organic matters (~detritus) are hotspots of diversity: multiple species are recruited. Lab experiment: biopolymers, 100 species. -Omics + culturing + phenotyping in order to recostruct dynamics. Observed successions (are true successions? Can also be explained by variability in growth/dilution rate). How succession depends on niche-breadth? Idea: niche breadth is bimodal (small niche breadth: early colonizers, specialized. Large niche breadth: late colonizers, cannot be grown in culture). He then looks at the metabolic networks: close to the central metabolism everything is more homogeneous, close to the periphery everything is more heterogenous (high variability in copy number). He then plots #of chitinases vs the # of coevolved modules. Early colonizers are high in both. Late colonizers are low in both. Free loaders have high # of coevolved modules but low #chitinases (can eat what free riders eat). Ecological dyanmics is consistent with this classification (degraders grow initially and then decay, cheaters and cross-feeders grow later)
Robert Marsland
Two facts: A) Microbiome is very diverse. B) Taxa is unstable, function is stable (robust patterns). Assumptions: 1) classical ecological models are inadequate for understanding ecosystems 2) large / diverse ecosystems are typically random. (Random) Chemostat model predicts many patterns. Why random works well? Above stability threshold random works very well.
Priyanga Amarasekare
1) Phenotypic traits are the interface between organisms and the environment 2) Evolution: (mutation+)contraints+selection 3) Irreversible processes arise from contraints. Different types of contraints: genetic (evolution acts only on heritable traits), energetic (tradeoffs), morphological (upper limits to evolutionary trajectories). Rest of the talk on how different traits depend on environment (Temperature). Two mechanism for reaction (to T variaton) norm: enzyme activation (monotonic response, e.g. mortality) and regulatory/hormonal (unimodal shape, e.g. eggs maturation) -> conserved across taxa.
Fernanda Valdovinos
Samraat Pawar
Stephen Proulx
Dervis Can Vural
OPEN DISCUSSION. 3 themes/questions
1) Identify quantities that are always increading or decreasing.
(side questions: why? At what scale (temporal, spatial, ...) do they have that trend?
Possible examples (in a Markov chain): return time (as a measure of irreversibility), turnover time, how often the system returns to the original state, fraction of trajectories that go from A->B vs from B->A.
Possible examples (interpretable quantities): # of species, biomass, # of limiting resources, # of niches, properties of resource consumption (e.g. efficiency), degree of specialization, interdependence, major (evolutionary) transitions
2) List of properties that we expect to be reversible/irreversible
Irreversible: oxygenation event (major transition), increase of specialization, latitudinal gradients, adaptive radiation, cluster formation
Debated: drift, mass exctintion (in what sense they are irreversible)
Reversible: function(?), total biomass (?)
3) (relevance of) transients
It depends on the timescale of evolution vs population dynamics.
Relevance of timescales: timescale of evolution, environmental change, behavior vs timescale of population/community dynamics
Relevant examples: patterns of extintions (position in transient determines outcomes), cycles ("always" in a transient)
Fernanda Valdovinos (Univ. Michigan) - Irreversible processes in ecological networks Link to the source page[edit source]
Pamela Martinez:
Very interesting research on how strain diversity can affect disease spread. I learned a lot about best practices on how feetting models to data because of the discussion this work provoked.
Annette Ostling:
Impressive work of testing the prediction of a competitive model of plant species with empirical data. The authors found that clustering happens in tropical forests due to niche partitioning. I learned much on different competitive models.
Greg Dwyer:
This talk was very useful for me to understand ways in which empirical data and models can interplay to make concrete predictions that can inform management. The applied case of informing agencies when to spray the forest with virus to stop the tree disease was very illuminating.
Otto Cordero:
Interesting application of ecological theory to microbial communities. I really enjoyed the way the speaker identified biological mechanisms in his empirical system and was able to connect the modeled dynamics to those empirically tested mechanisms.
Priyanga Amarasekare:
This talk made me think in a deeper way about constraints on phenotipic/genotipic variation that can help us understand how ecological system may respond to human perturbations such as climate change.
Fernanda Valdovinos (my talk):
It was extremely helpful for my research the in depth discussion that the audience provoked on the details of my model. The dissecting questions I received on my equations and their consequences were very illuminating. I will definitely use some of the new understanding I acquired trough answering those questions in the paper I'm currently working on. I also really appreciate the philosophical question that Greg asked me over the break and Jacopo helped to answer. That question was about what are we actually learning by using a network approach instead of just many differential equations as we have been doing for years in ecology prior networks. I would really like to further discuss this question as a group tomorrow.
Stephen Proulx:
Amazing talk that helped me better understand adaptive dynamics, how we can read mutation/invasion maps and how to make better use/understanding of fitness landscapes. It was fascinating to me the trade-off example on plant fertility-survival that showed a clear case in which small vs large mutations can drive the genotype/phenotype of plants to different attractors. I also liked a lot one of the speakers questions on how to produce general theory from non-equilibrium cases and the discussion that question provoked.
Priyanga Amarasekare (UCLA) - Phenotypic evolution in the Anthropocene Link to the source page[edit source]
- Presentation highlights: (i) The role of constraints in phenotypic evolution as means of generating irreversible evolutionary endpoints and set upper limits to evolutionary trajectories. (ii) Role of constraints in species' ability to adapt to changing environments. (iii) Species come up against hard limits to phenotypic plasticity under climate warming. (iv) In order for thermal reaction norms to evolve in the face of climate warming, there has to be genetic variation. Unclear that reaction norms under strong biochemical control (e.g., development) have sufficient amounts of variation for the upper thermal limit to evolve in response to warming.
2. Open questions:
2.1 Connection between Darwinian adaptationist evolution and the idea of increase in disorder (as in the second law of thermodynamics)
2.2 What exactly are irreversible evolutionary endpoints? Can we come up with a specific definition of irreversibility?
2.3 Selection and constraints are not the same thing. This needs to be clarified.
3. How my perspective has changed: I want to think more carefully and deeply about the connection between Darwinian evolution and the second law of thermodynamics.
4. Reflections on other presentations
4.1 Stephen Proulx - I very much liked this presentation about the population genetics of low-probability transitions. I was particularly interested in stochastic selection due to lottery competition that leads to alternative stable states making it possible for mutations of large effect to cause transitions between states in a directional manner. I also liked the models of stochastic tunneling or valley crossing, that provide possible avenues for transitions between states. The case of multiple independent mutations enabling valley crossing is equally fascinating. I particularly liked how the examples shown related to the central theme of irreversibility and transitions.
4.2 Dervis Can Vural - An elegant presentation of the evolution of cooperation against the backdrop of fluid dynamics. I would like the theory to be generalized to perturbations other than shear so that it can also apply to pathogenic microbes within a host and other situations that do not involve fluid as a medium. I think you also should take the plunge and try to connect this theory to Hamilton's theory of kin selection. It is hard, and perhaps not analytically tractable, but it would be worth doing.
4.3. Samraat Pawar - I like the connection between metabolic constraints on species interactions and carbon fluxes.
4.4 Fernanda Valdovinos - The idea that adaptive foraging by mutualists (e.g., pollinators) allowing the persistence of nested mutualistic networks is a novel and exciting finding that pushes the field forward.
Post-meeting Reflection by Non-presenting Attendees
Reference Materials by Presenting Attendees[edit source]
Dervis Can Vural (Univ. Notre Dame) - Cooperation and specialization in dynamic fluids[edit source]
| Title | Author name | Source name | Year | Citation count From Scopus. Refreshed every 5 days. | Page views | Related file |
|---|---|---|---|---|---|---|
| The organization and control of an evolving interdependent population | Dervis C. Vural, Alexander Isakov, L. Mahadevan | Journal of the Royal Society Interface | 2015 | 5 | 1 | |
| Shearing in flow environment promotes evolution of social behavior in microbial populations | Gurdip Uppal, Dervis Can Vural | eLife | 2018 | 5 | 0 | |
| Increased Network Interdependency Leads to Aging | Physical Review E - Statistical, Nonlinear, and Soft Matter Physics | 2013 | 0 | 0 |
Fernanda Valdovinos (Univ. Michigan) - Irreversible processes in ecological networks[edit source]
I uploaded the three papers I presented in my talk:
Valdovinos et al (2013), Oikos: here I propose the model for the first time and use empirical networks.
Valdovinos et al (2016), Ecology Letters: Main results I presented in my talk. Niche partitioning via adaptive foraging reverses the effects of nesteness and connectance on species persistance in plant-pollinator networks.
Valdovinos et al (2018), Nature Communications: I used my model to generate a predictive framework on the invasion of alien pollinators and the subsequent effect on native species within plant-pollinator networks.
Brosi & Briggs (2013), PNAS: This is the data we used to test the prediction of my model on pollinators preferring specialist plants, when standardizing by plant and pollinator abundances.
| Title | Author name | Source name | Year | Citation count From Scopus. Refreshed every 5 days. | Page views | Related file |
|---|---|---|---|---|---|---|
| Adaptive foraging allows the maintenance of biodiversity of pollination networks | Fernanda S. Valdovinos, Pablo Moisset de Espanés, José D. Flores, Rodrigo Ramos-Jiliberto | Oikos | 2013 | 64 | 6 | [ Download] |
| Niche partitioning due to adaptive foraging reverses effects of nestedness and connectance on pollination network stability | Fernanda S. Valdovinos, Berry J. Brosi, Heather M. Briggs, Pablo Moisset de Espanés, Rodrigo Ramos-Jiliberto, Neo D. Martinez | Ecology letters | 2016 | 42 | 1 | |
| Species traits and network structure predict the success and impacts of pollinator invasions | Fernanda S. Valdovinos, Eric L. Berlow, Pablo Moisset De Espanés, Rodrigo Ramos-Jiliberto, Diego P. Vázquez, Neo D. Martinez | Nature Communications | 2018 | 22 | 3 | |
| Single pollinator species losses reduce floral fidelity and plant reproductive function | Proceedings of the National Academy of Sciences | 2013 | 0 | 1 |
Priyanga Amarasekare (UCLA) - Phenotypic evolution in the Anthropocene[edit source]
| Title | Author name | Source name | Year | Citation count From Scopus. Refreshed every 5 days. | Page views | Related file |
|---|---|---|---|---|---|---|
| Temperature dependence of the functional response | Göran Englund, Gunnar Öhlund, Catherine L. Hein, Sebastian Diehl | Ecology Letters | 2011 | 226 | 13 | |
| The common patterns of nature | S. A. Frank | Journal of Evolutionary Biology | 2009 | 117 | 2 | |
| Temperature dependence of the functional response2 | Ecology Letters | 2011 | 0 | 25 | Download |
Reference Materials by Non-presenting Attendees
