Lecture G4 (2023-03-30): Identifying Information in Living Systems, Part 1

This lecture focuses on the diverse ways that ants (and slime mold) process information from their environment. We start with some basic background on ants (including their evolution from solitary wasps) and then discuss mass recruitment (one of the three main ways that ants recruit to food or candidate nest sites). We contrast the dynamic performance of Lasius niger with Pheidole megacephala and explore the suggestion that "errors" make P. megacephala better at tracking changes (using fire ants as an example that confirms this idea). We then discuss how trails are used in slime mold for enhancing exploration (instead of the exploitation case in ants) and show how slime mold can spread itself out to make decisions that compare different options in the environment. That brings us to ants that similarly spread themselves out (using linear recruitment strategies instead of the nonlinear pheromone-trail-based mass recruitment strategies) so that they can make similar deliberative decisions. We will pick up with this case in the next lecture.

Lecture G3 (2023-03-28): Information Processing in Living Systems

In this lecture, we discuss topics related to the chapter, "Information Processing in Living Systems," by Mitchell (2009, Chapter 12). The beginning of the lecture discusses the first use of information theory for a non-human application -- an analysis of the honeybee waggle dance. That requires a description of the waggle dance/waggle run. We then move on to examples brought up by Mitchell -- the adaptive immune system (lymphocytes, B cells, T cells, antibodies) and ants (primarily the use of pheromone trails for recruiting to discovered foods during foraging). Our discussion of the vertebrate adaptive/acquired immune system also gives us an opportunity to briefly discuss the innate immune system (which has a much deeper phylogenetic history). We discuss natural selection within the adaptive immune system, both in terms of negative selection (central tolerance and autoimmune disorders) and positive selection. We close with a brief description of basic trail laying behavior, which we will pick up in our next lecture that will discuss more sophisticated communication cases in ants and other non-human organisms.

Whiteboard notes for this lecture can be found at: https://www.dropbox.com/s/lhwde9zdg25s5mu/SOS220-LectureG3-2023-03-28-Information_Processing_in_Living_Systems.pdf?dl=0

Lecture G2 (2023-03-23): Basic Population Genetics and Evolutionary Biology

In this lecture, we wrap up our introduction to The Modern Synthesis by describing how population genetics connected particulate inheritance (genes with discrete alleles) to quantitative traits and natural selection. After reviewing the initial conflict between Mendelism and Darwinism, we use a simple additive effect example to show how discrete alleles can produce approximately continuous features (that are even more continuous when considering the effect of the environment on gene expression). We then discuss the contributions of Haldane and Wright to population genetics, summarize the key components of population genetics, and hold up population genetics as a foundational core to The Modern Synthesis which also include the primacy of natural selection in evolution. This gives us an opportunity to discuss Stephen Jay Gould's objections, punctuated equilibria, biological constraints (including the "spandrels of evolution"), and historical contingency. We conclude with a brief introduction to the central dogma of molecular biology, which helps to explain how genes lead to the expression of phenotypic traits that confer fitness on alleles. We end this discussion a little early (due to starting a little late).

Whiteboard notes for this lecture can be found at: https://www.dropbox.com/s/vc5rsqpmpymih60/SOS220-LectureG2-2023-03-23-Basic_Population_Genetics_and_Evolutionary_Biology.pdf?dl=0

Lecture G1 (2023-03-21): Evolution of Evolution

In this lecture, we review the history of thought about biological evolution, as surveyed by Mitchell (2009, Chapter 5). We start with Lamarck's ideas and discuss their appeal to Darwin. We then move to Darwin and note the influence of Lyell, Lamarck, Mathus, and (Adam) Smith on Darwin's theory of evolution by natural selection. We describe Darwin's finches on the Galapagos Island chain as evidence for natural selection. We then pivot to Mendel to discuss particulate inheritance and point out the difficulties with integrating this with natural selection. We close with an introduction to population genetics (Fisher, Haldane, and Wright) that resolves the conflict between Darwinism and Mendelism, providing the foundations for The Modern Synthesis.

Whiteboard notes for this lecture can be found at: https://www.dropbox.com/s/5fsaefbep03ddq0/SOS220-LectureG1-2023-03-21-Evolution_of_Evolution.pdf?dl=0

Lecture F3 (2023-03-16): Applying Resilience Thinking in Social–Ecological Systems

In this lecture, we review the conceptual dimensions of resilience (latitude, resistance, precariousness, and panarchy) and the adaptive cycles that pass information and influence from systems at one scale to systems at other scales. Ultimately, this lecture is about how to manage resilience in systems. We define terms like adaptability and transformability, and we discuss tradeoffs between resilience and short-term profits as well as different forms of resilience (as in specified/targeted/local resilience and generic/global resilience). We finish with a discussion of three properties that help increase generic resilience – diversity, modularity (connectedness), and tightness of feedbacks.

This lecture is based upon content from Walker and Salt (2006, Chapter 5) and Walker et al. (2004).

Whiteboard notes for this lecture can be found at: https://www.dropbox.com/s/g87jqbx3eqg5ljy/SOS220-LectureF3-2023-03-16-Applying_Resilience_Thinking_in_Social-Ecological_Systems.pdf?dl=0

Lecture F2 (2023-03-14): The Adaptive Cycle and Panarchy

In this lecture, we review the processes in natural systems that cause diversity to grow initially and then collapse as systems get more mature (and this collapse in diversity can lead to the release and reorganization, as in the Adaptive Cycle). We use a Pareto-based multi-objective framework to conceptualize what is going on in ecological communities. In this framework, Pareto improvements correspond to expansion of diversity (virtuous cycle) that ends up slowing down as the community approaches the Pareto frontier (limits to growth). Once on the frontier, competitive exclusion and genetic drift lead to sparsification of the community (success to the successful). In other words, the initial process generates a diverse set of niches, but the later processes collapse each niche to a very small set of individuals that dominate that niche. We explain how genetic drift causes diversity to collapse even when diverse individuals have equal fitness. We also talk about how we can measure diversity using the Shannon index, which measures both richness as well as evenness. This whole explanation sets up for an introduction of the Adaptive Cycle (r/growth phase, K/conservation phase, omega/release phase, and alpha/reorganization phase). Overall, the adaptive cycle links topics from earlier in the semester (systems archetypes) with more recent topics (chaotic dynamics) and helps provide a framework for understanding how exogenous/slow variables change over time (and thus how stability regimes change over time). Change is inevitable, and sustainability is about surviving change; sustainability is not about preventing change.

Whiteboard notes for this lecture can be found at: https://www.dropbox.com/s/te0c37iet0roxa3/SOS220-LectureF2-2023-03-14-The_Adaptive_Cycle_and_Panarchy.pdf?dl=0

Lecture F1 (2023-03-02): Assessing Development, Growth, and Diversity in Systems

In this lecture, we focus on how to estimate the health or general status of large complex systems. This is motivated by the concern that systems that appear, at a macroscale, to be stable might actually be undergoing changes from within that affect their resilience. We provide one example from social welfare economics, which starts with an introduction to the Lorenz curve for wealth distributions and the related Gini coefficient/index used to measure the distance in a distribution from the equal-wealth distribution. We show how the Gini index has changed over time for different countries based on their political decisions, which allows us to talk about Pareto optimality as a framework for thinking about social-welfare policy decisions. We introduce things like the Pareto improvement and the Pareto frontier. We then pivot to community ecology and use the Pareto framework as a lens for thinking about how evolution (and natural selection, in particular) is a sequence of Pareto improvements that moves communities toward a Pareto frontier. Although they diversify in getting to the frontier, that diversification can be limited in later movements along the frontier (which will affect resilience). We begin to talk about how to use Shannon entropy as an index for biodiversity, helping to estimate the "health" of a given ecological community.

Whiteboard notes for this lecture can be found at: https://www.dropbox.com/s/9xflupesoz0rqx0/SOS220-LectureF1-2023-03-02-Assessing_Development_Growth_and_Diversitiy_in_Systems.pdf?dl=0