Ecology Lecture Notes (Population, Community, Biodiversity)

Bee-inspired optimization and real-world uses

• Bees’ foraging algorithm tells them which flowers to visit, when, and how much energy to allocate to each flower.
• This bee-inspired algorithm has practical applications beyond bees, notably in computing and web hosting: it can allocate server resources based on web traffic to different websites.
• Empirical claim: servers using this algorithm (modeled on bee foraging) generate between 5\%\text{ to }25\% more profit than server setups that do not use it.
• Economic impact example given: researchers invested \$100{,}000 into bee-inspired research, which allegedly contributed about \$5\times 10^{10} (50 billion) to the world economy through new insights and technologies.
• A YouTube story link is mentioned as a resource for more bee-science stories; the lecture uses this as an example of cross-disciplinary fruitfulness.
• Takeaway: investing in foundational, biologically inspired algorithms can yield large practical and economic payoffs.

Exam logistics and prep notes

• Exam format: in-class, Respondus LockDown Browser required; you must test it beforehand; available mock exam online.
• If there are device issues with LockDown Browser, contact instructor soon and seek alternatives if needed.
• Exam coverage: lectures 1–3; this is lecture 3.
• Question format: 50 multiple-choice questions; one question is shown at a time; after answering, you cannot go back to previous questions.
• Time allotment: 75 minutes; exam starts at 02:00 and closes at 03:15; you must use the full time window.
• Attendance and ID: in-room exam; you must show an ID to receive credit unless you have approved accommodations.
• If taking accommodations or testing off-campus, inform instructor and arrange in advance.
• Practical tips shared: arrive on time; test the browser well before the exam; try the mock exam early; if problems persist, reach out during office hours.
• iPad compatibility note: LockDown Browser can be used on iPad with a dedicated app, but experiences vary; use it as you would a normal browser to access Canvas.

Ecology: core concepts and framework

• Ecology is the study of organisms and their environments; levels include ecosystems, communities, populations, and organismal ecology.
• Abiotic factors are non-living components of the environment; biotic factors are living organisms.
• Key questions in ecology include how energy and chemicals flow (e.g., carbon cycle) through ecosystems; how organisms adapt to their environment and interactions with other species.
• A community is all living things (multiple species) in a given area; an ecosystem includes both biotic and abiotic components; a population is all individuals of the same species in a given area.
• Examples of level-appropriate questions: how populations evolve through time, what is population density, and how age structure varies within a population.

Population dynamics: growth models and carrying capacity

• Population growth dynamics overview:
  • Exponential growth: continuous growth with unlimited resources, producing a J-shaped curve.
  • Logistic growth: slows as resources become limiting, producing an S-shaped curve and leveling off near carrying capacity.
• Exponential growth model (conceptual): N(t) = N0 e^{rt} where N(t) is population size at time t, N0 is initial size, and r is intrinsic growth rate.
• Logistic growth model (conceptual): \frac{dN}{dt} = r N \left(1 - \frac{N}{K}\right) where K is carrying capacity, the maximum population size the environment can sustain indefinitely.
• Carrying capacity (K): the maximum number of individuals of a population that the environment can sustain indefinitely given finite resources and space.
• Examples and indicators:
  • Human population trend resembles exponential growth over centuries, with a recent shift influenced by medicine, sanitation, and nutrition; current population around 8\times 10^{9} (8 billion).
  • The global carrying capacity is often debated; a rough billionaire estimate attributed to E. O. Wilson places K ~ 10^{10} (10 billion) under certain assumptions (e.g., vegan baseline).
  • If humans remain at or near K, resource constraints become more pronounced; climate change can shift K by altering resources (food, water, habitat).
• Real-world constraint example: Peary/Peary Caribou population has crashed in some Arctic regions due to climate-related habitat changes (warming temperatures and snow/ice dynamics affecting access to moss and lichen).
• Population trajectory in humans historically shows rapid increases following medical and sanitary improvements; concern about crossing carrying capacity due to finite resources (water, food, space).
• Quick numerical snapshots:
  • Current global population: 8\times 10^{9}.
  • Estimated carrying capacity (rough): 10^{10}.
  • Remaining capacity (rough): 2\times 10^{9} people (context-dependent and sensitive to diet, climate, and technology changes).

Climate change, species declines, and life-history strategies

• Climate change example: Peary caribou in Arctic regions experienced a population crash linked to warming winters.
  • Mechanism: Warmer temperatures melt daytime snow and refreeze at night, creating an ice layer under the snow. When caribou dig for moss and lichen, they encounter a hard ice layer that blocks access, leading to starvation.
  • The pattern illustrates how climate-driven habitat change can directly reduce a species’ carrying capacity.
• Life-history strategies: how organisms allocate energy to growth, reproduction, and survival across lifetimes.
  • r-selected species: rapid development, many offspring, little parental care (e.g., frogs with hundreds of eggs; low parental investment).
  • K-selected species: slower development, fewer offspring, high parental care (e.g., humans with 2–3 offspring on average; ~2.45 children per US family as a cited value).
  • Trade-off: both strategies can yield similar numbers of offspring surviving to adulthood, but the energy allocation and survival strategies differ.
• Life-history diversity reflects adaptation to environmental stability: unstable environments favor rapid reproduction; stable environments favor investment in offspring survival.

Community ecology and species interactions

• Community ecology focuses on interactions among multiple species in a shared habitat and how these interactions shape community structure and dynamics.
• Types of species interactions (symbiosis) with typical effects:
  • Competition: negative effect on both populations (-resource limitation).
  • Mutualism: positive effect on both populations (e.g., pollinators and flowering plants).
  • Predation: positive effect on the predator, negative on the prey.
  • Parasitism: positive effect on the parasite, negative effect on the host.
  • Commensalism: positive effect on one population and neutral effect on the other.
  • Neutralism: neutral effects on both populations (the lecturer presented an example that the pollinator-plant interaction is used as an example of mutualism; note that the transcript contained a misstatement about neutralism being positive for one population).
• Important caveat from the lecture: while the table in class illustrates these categories, the speaker included a flawed note about neutralism; in standard ecology, neutralism means neither species affects the other.
• Pollination as a classic mutualism example: pollinators (e.g., honeybees, hummingbirds) obtain nectar, while plants gain pollen transfer to fertilize Ovules; pollen contains male gametes delivered to the stigma; mutual benefit to both parties.
• Phenological mismatch due to climate change: changes in timing (e.g., migration cues in birds tied to photoperiod vs. temperature cues for flowering) can uncouple mutualisms (plants bloom when pollinators are absent).
• Pathogens and diseases: climate change can influence disease dynamics and pandemic risk; recent emphasis in the course includes several weeks on pathogens.

Trophic structure, energy flow, and food webs

• Trophic levels describe energy flow: producers (plants) -> primary consumers (herbivores) -> secondary consumers (carnivores/omnivores) -> tertiary, quaternary consumers, etc.
• Energy transfer concept: energy is lost at each transfer (not all energy consumed by one trophic level is converted to biomass in the next); this underpins why more producers are needed to support higher trophic levels.
• Food chain vs. food web:
  • Food chain is a simple linear sequence (producer → consumer → consumer).
  • Food web is a network of many interconnected chains, showing multiple prey and predator relationships in a community.
• Example food web components:
  • Producers: plants, algae, phytoplankton.
  • Primary consumers: herbivores (e.g., caterpillars, zooplankton like krill).
  • Secondary and higher-level consumers: birds (red-winged blackbird), robins; predators like barn owls, peregrine falcons; apex predators like orcas and polar bears in some ecosystems.
• A practical takeaway: you can occupy multiple trophic levels with a single meal (e.g., humans can be primary, secondary, or tertiary consumers depending on food choices).
• Basic food chain example: Acorns (producer) → Squirrels (primary consumer) → Owls (secondary/tertiary predator).

Consequences of changing one link in a chain: a hands-on activity example

• If oak trees (acorns) are removed:
  • Squirrels decrease due to loss of food source.
  • Owls decrease due to reduced prey (indirect effect).
• If owls are removed:
  • Squirrels increase due to release from predation.
  • Acorns decrease due to increased herbivory pressure from more squirrels (and cascading effects).
  • Potential ecosystem imbalance if the top predator is removed (ecosystem could become dominated by herbivores and altered vegetation).
• Classroom activity: students analyze two basic food chains involving kelp, sea urchins, otters, and, on another chain, phytoplankton, zooplankton, cod, sea lions, and orcas; they predict responses to changes (e.g., warmer waters reducing nutrients affecting phytoplankton, cascading effects on higher trophic levels).
• Instructors encourage collaborative discussion, data interpretation, and documenting reasoning as part of the learning process.

Biodiversity: measuring diversity and its value

• Biodiversity yields multiple tangible and intangible benefits: food diversity, medicine from plants and fungi, crops and pollination, building materials, and water purification.
• Biodiversity contributes to resilience in ecosystems and provides ecosystem services (e.g., disease control, groundwater purification).
• How biodiversity is measured:
  • Species richness: the number of different species in a community. Example: two-species community with Homo sapiens and Habernatus Americanus (a jumping spider) has richness = 2.
  • Relative abundance: how common each species is relative to others. Example: 504 humans vs. 4 Habernatis Americanus, indicating a much higher abundance of humans in that community.
• Comparative forest examples:
  • Forest A: eastern hemlock, Tamarack, larch, sugar maple, poplar (4 species) but different abundances.
  • Forest B: same 4 species as Forest A but with different relative abundances; in one case, a single species dominates, making overall diversity lower; the example emphasizes that same species richness can differ in diversity due to relative abundances.
• Conceptual implication: Higher evenness (more balanced abundances) tends to indicate greater diversity even when species richness is the same.

Putting it together: real-world relevance and reflections

• Biodiversity supports fundamental human needs and wellbeing (food, medicine, energy, climate regulation, pollination, water filtration).
• The interconnectedness of species via trophic interactions means changes in one species propagate through the ecosystem.
• Climate change can alter carrying capacities, disrupt mutualisms (phenology), and reconfigure food webs, with ripple effects on ecosystem services and human societies.
• The lecturer emphasizes staying curious about how everyday life (e.g., what we eat) connects to ecology, energy flows, and the health of ecosystems.

Quick glossary of key terms

• Carrying capacity (K): maximum population size that an environment can sustain indefinitely.
• Exponential growth: growth pattern with constant per-capita growth rate; J-shaped curve.
• Logistic growth: growth that slows as resources become limiting; S-shaped curve.
• Trophic levels: hierarchical levels in a food web based on energy flow (producers, primary consumers, etc.).
• Symbiosis: close and long-term interaction between different species; includes mutualism, commensalism, parasitism, predation, competition, etc.
• Mutualism: both species benefit.
• Predation: one species benefits (predator); the other is harmed (prey).
• Parasitism: one benefits (parasite); the other is harmed (host).
• Commensalism: one benefits; the other is unaffected.
• Neutralism: theoretically, neither species affects the other (not always observed in nature; the lecture notes included a misstatement here that should be treated as an instructional error).
• Phenology: the timing of biological events (e.g., migration, flowering) and how it can be disrupted by climate change.
• Foraging algorithm: a computational method inspired by animal foraging behavior used to optimize resource allocation in systems like servers and networks.

Notes and caveats

• Some statements in the transcript were informal or contained simplifications/misstatements (e.g., neutralism defined as mutual benefit, which is not scientifically accurate). For study purposes, use standard definitions: neutralism means neither species strongly affects the other; mutualism means positive for both.
• Always distinguish between illustrative classroom examples and established scientific consensus when studying population dynamics, interactions, and carrying capacity.
• The numbers and estimates cited in the lecture are illustrative and should be cross-checked with current data or textbook figures for exam preparation.