Food Webs & Production and Biogeography Lecture Notes

Administrative Announcements and Extra Credit

• Homework Help: Available in Storer Basement at Noon on Thursday, May 28, 2026.
• Late Discussion Assignments: These are due no later than June 4th by $11:59\,\text{PM}$.
• Extra Credit Opportunity (Memes):     * Students can earn $2$ points added to their Midterm 2 exam score (recorded in the midterms category).     * The submission deadline is Tuesday, 6/2 at $11:59\,\text{PM}$.

The Equilibrium Theory of Island Biogeography

• Theoretical Basis: Equilibrium species richness is determined by identifying the intersection of the immigration rate curve and the extinction rate curve.
• Experimental Test (Simberloff & Wilson 1969):     * Researcher: Dan Simberloff.     * Study Site: $8$ small mangrove islands, ranging from $11$ to $18\,m$ in diameter.     * Colonization Distance: The distance to the nearest source of colonists varied from $2$ to $1200\,m$.     * Methodology: Six of the islands were fumigated to eliminate all existing insects. Researchers then censused the islands to observe the process of recolonization.     * Results for "Near" Islands:         * Acquired species sooner than far islands.         * Maintained a higher total number of species.         * These findings align with the predictions of the Equilibrium Theory of Island Biogeography.     * Graphical Data (Species vs. Days Since Defaunation):         * Prior to defaunation, near islands had higher species richness than far islands.         * After defaunation, both types of islands showed a rapid initial increase in species, reaching an asymptote roughly reflecting their original pre-defaunation numbers within $320-400$ days.
• Area Manipulation Experiment:     * Researchers experimentally decreased the area of mangrove islands.     * Outcome: A decrease in island area led to local extinctions of arthropod species, corroborating the theory that smaller areas support fewer species.

Species-Area Relationships

• Mathematical Formula:     * The relationship is expressed as: $S = cA^z$     * The linearized log-log version is: $\ln(S) = \ln(c) + z \times \ln(A)$     * Variables:         * $S$: Number of species.         * $c$: A constant (representing the y-intercept in log-log space).         * $A$: Area of the habitat.         * $z$: The slope of the increase.
• Ubiquity of the Pattern: Species-area relationships are observed across diverse taxa and environments:     * Plants in Britain: Data from Southern England, Thames, and Surrey show a log-linear increase in species richness with log area.     * Reptiles on Islands: Show a clear positive slope between log area ($km^2$) and log number of species.     * Mammals on Mountaintops: Demonstrate increasing richness as the area of the "sky island" (mountaintop habitat) increases from $1$ to $100,000\,km^2$.     * Fishes in Desert Springs: Show a log-linear increase as spring area ($m^2$) increases.

Global Diversity Patterns

• General Latitudinal Gradient: Most taxonomic groups exhibit the highest species diversity in the tropics and the lowest diversity near the poles.
• Soil Organisms: Biodiversity indices for soil organisms show high levels of diversity concentrated in tropical regions, though data for Greenland, ice-covered zones, and certain water bodies are not available.     * iClicker Question: Based on global maps, soil biodiversity is highest near the equator.
• Plants: Map data indicates that plant species richness can exceed $6500$ species in high-diversity tropical hotspots.
• Mammals: Aboveground mammal diversity reaches peaks of approximately $217$ species per area unit in tropical latitudes.
• Birds: Mapping shows a global peak of around $666$ species in tropical zones.
• Freshwater Fish: Data from The Nature Conservancy and WWF (2008) indicates species richness ranges from $1-19$ in high-latitude regions to $491-880$ in tropical river basins.
• Marine Species: Marine biodiversity shows a similar peak at low latitudes, though some patterns vary based on specific ocean currents and depths.

Mechanisms Explaining Global Diversity Patterns

Mechanism 1: Energy and Abiotic Stress

• Theory: The tropics receive the most solar energy and experience less abiotic stress (e.g., extreme cold).
• Result: Higher Annual Net Primary Productivity (NPP), which can reach levels of $1500\,g\,C\,m^{-2}\,yr^{-1}$. This high energy base allows for more species and more trophic levels to coexist.

Mechanism 2: Geographic Area and Evolutionary Time

• Theory: The tropics represent the largest and oldest continuous land masses.
• Result: Greater land area (measured in $50,000\,km^2$ blocks) is found in tropical regions compared to tundra or boreal regions. More time and space provide significantly more opportunities for speciation events to occur.

Mechanism 3: Biotic Interactions and Speciation Rates

• Abiotic Resource Limitation: In high-latitude/stressed environments, there is often a fixed background environment with a fixed number of available niches.
• Biotic Resource Limitation: In the tropics, species are limited by interactions with other organisms. This creates constant feedback and coevolution (biological arms races), leading to a possibly infinite number of niches as species evolve.
• Evidence (Schemske et al. 2009): A review of $39$ kinds of species interactions found:     * Stronger interactions at low (tropical) latitudes in $29$ out of $39$ cases.     * Similar interaction strengths across latitudes in $10$ out of $39$ cases.     * Zero cases where interactions were stronger at high (polar) latitudes.

Biogeography Summary

• Pattern 1: Species diversity decreases from the equator to the poles.     * Causes: Abiotic environment (high productivity), biogeographic history (large area, long time), and ecological feedbacks (biotic interactions leading to speciation).
• Pattern 2: Species-area curves are one of the most consistent patterns in ecology.     * Pattern: Higher area leads to more species.     * Cause: The balance between extinction and immigration rates.
• Pattern 3: Species diversity is critical for ecological function.     * Impacts: It can increase both ecological stability and overall ecosystem function.

Fundamentals of Food Webs

• Definition: Food webs organize species based on their trophic (energetic) interactions.
• Ecological Roles: These are determined by "what they eat and what eats them."
• Trophic Levels:     * First Level: Primary producers (autotrophs) and detritus (dead organic matter).     * Second Level: Primary consumers (herbivores and detritivores).     * Third Level: Secondary consumers (primary carnivores).     * Fourth Level: Tertiary consumers (secondary carnivores).
• Community vs. Ecosystem Perspectives:     * Communities: Groups of interacting species at the same place/time; measured by species composition and population numbers.     * Ecosystems: Organisms plus the abiotic environment; measured by the flux of energy and nutrients.     * Food webs link these by showing how interactions determine the movement of energy through the ecosystem.

Energy Transfer and Trophic Efficiency

• Second Law of Thermodynamics: Energy conversion is imperfect; energy is lost as heat during every transfer. Consequently, available energy decreases at each higher trophic level.
• Fate of Primary Production:     * Net Primary Production (NPP) can be consumed or not consumed.     * Not Consumed: Becomes detritus.     * Consumed: Can be assimilated or lost as feces/urine (which becomes detritus).     * Assimilated: Used for respiration or converted into biomass (Secondary Production).

Efficiency Parameters and Formulas

• Consumption Efficiency ($E_c$): The proportion of available biomass ingested by consumers.     * $E_c = \frac{I_n}{P_{n-1}}$
• Assimilation Efficiency ($E_a$): The proportion of ingested biomass that is digested.     * $E_a = \frac{A_n}{I_n}$
• Production Efficiency ($E_p$): The proportion of assimilated energy converted into new consumer biomass.     * $E_p = \frac{P_n}{A_n}$
• Ecological Efficiency ($E_e$): The overall conversion efficiency of energy from one trophic level to the next.     * $E_e = E_c \times E_a \times E_p = \frac{P_n}{P_{n-1}}$     * Note: $P_1$ refers to energy converted to plant biomass ($P_{n-1}$); $P_2$ refers to energy converted to herbivore biomass ($P_n$).

Practice Problem: Calculating Energy Transfer

Given the following data:

• NPP ($P_{n-1}$): $500\,J$
• Ingestion ($I_n$): $250\,J$
• Respiration: $125\,J$
• Excretion: $50\,J$
• Secondary Production ($P_n$): $75\,J$

Calculations:

• Consumption Efficiency ($E_c$):     * $E_c = \frac{250\,J}{500\,J} = 0.5$
• Assimilated Biomass ($A_n$):     * $A_n = \text{Ingestion} - \text{Excretion} = 250\,J - 50\,J = 200\,J$
• Assimilation Efficiency ($E_a$):     * $E_a = \frac{200\,J}{250\,J} = 0.8$
• Production Efficiency ($E_p$):     * $E_p = \frac{75\,J}{200\,J} = 0.375$
• Ecological Efficiency ($E_e$):     * $E_e = \frac{75\,J}{500\,J} = 0.15$

Trophic Dynamics and Interactions

• Top-Down vs. Bottom-Up Control: Ecological systems are influenced by both the availability of resources (bottom-up) and the impact of predators (top-down).
• Indirect Interactions:     * Trophic Cascades: Predators limit herbivores, thereby releasing producers from grazing pressure.     * Trophic Facilitation: One species indirectly helps another through a third species.     * Competitive Networks: Complex sets of interactions where no single species dominates.     * Apparent Competition: Two species share a predator; if one species increases, the predator population grows and subsequently reduces the second species.
• Strong Interactors:     * Keystone Species: Have disproportionately large effects relative to their low abundance.     * Foundation Species: Have large effects due to their high abundance/biomass (e.g., trees in a forest).     * Ecosystem Engineers: Organisms that physically create, modify, or maintain habitats (e.g., beavers).