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RNR 316 Natural Resources Ecology - Chapter 4: Adaptations to Variable Environments

Chapter 4 Learning Notes: Adaptations to Variable Environments

  • Context and scope

    • Chapter 4 focuses on how ecological systems vary in time and space and how organisms respond through adaptations, plasticity, and behavioral strategies.
    • Key framing: variable environments select for variable phenotypes; organisms can evolve adaptations to abiotic variability; migration, storage, and dormancy are strategies to cope with extreme variation.
    • Weather vs. climate definitions: Weather = short-term variation in temperature and precipitation; Climate = long-term averages and patterns. Climate drivers include solar radiation changes, ocean circulation, albedo, and topography. These concepts underpin why variability matters for organisms.

  • Core concepts and definitions

    • Variation and natural selection (Chapter context)

    • Intra-species variation exists in traits; some variation is heritable.

    • More offspring are produced than can survive.

    • Individuals with better fitness (survival and reproduction) pass advantageous alleles to offspring, altering trait frequencies over generations.

    • Key ingredients: mutation, recombination, and inheritance.

    • Conceptual takeaway: Evolution by natural selection shapes populations in response to environmental variation.

    • Genotype × Environment = Phenotype

    • Phenotypes arise from genetic information interacting with environmental conditions.

    • A given genotype may produce different phenotypes in different environments; a phenotype well-suited to one environment may be poorly suited to another.

    • Expression can be on/off for certain genes depending on environmental cues.

    • Notation: ext{Phenotype} = f( ext{Genotype}, ext{Environment})

    • Alternate concise form used in lectures: ext{Genotype} imes ext{Environment}
      ightarrow ext{Phenotype}

    • Phenotypic plasticity and trade-offs

    • Phenotypic plasticity: the ability of a single genotype to produce multiple phenotypes in response to environmental variation.

    • Plasticity helps maintain homeostasis when conditions vary.

    • Phenotypic trade-offs: a given phenotype may be highly fit in one environment but less fit in another; different genotypes can be favored in different environments.

    • Example emphasis: a grey tree frog tadpole chooses a phenotype that enables fast escape when predators are present and fast growth when predators are absent; reliable environmental cues are necessary for plastic responses.

    • Acclimation vs. adaptation

    • Acclimation (physiological plasticity): rapid, reversible changes within an individual in response to environmental conditions (e.g., increased heart rate or red blood cell production at high elevation).

    • Adaptation: longer-term evolutionary change at the population level that makes a lineage better suited to its habitat; involves genetic changes and is less reversible.

    • Distinction matters for predicting responses to climate change and habitat alteration.

    • Elevation studies and reaction norms

    • Classic work: Clausen, Keck, and Heisey (California transect) across environmental gradients (coastal California, coast ranges, Sierra Nevada foothills, timberline).

    • Purpose: understand how traits (e.g., stem height) vary with elevation and whether plastic responses exist across populations.

    • Concept: Reaction norms describe how a phenotype changes across environments for a given genotype.

  • Variation across space and time

    • Spatial scales
    • Large-scale variation: climate, landforms, soil types.
    • Small-scale variation: microhabitat structure, plant form, or animal behavior.
    • A given spatial scale can be important to one organism but not to another (e.g., leaf shape affecting an insect herbivore vs. large mammal).
    • Temporal variation
    • Spatial variation experienced by organisms is the temporal sequence of exposures as they move through space.
    • Event duration influences the spatial extent of affected areas (e.g., atmospheric and marine phenomena).

  • Extreme events and variability examples

    • Weather and climate examples illustrate how extreme events can vary in space and time.
    • Notable events discussed: hurricanes and wildfires with annotated years (e.g., SE U.S. hurricanes, NW wildfires) to demonstrate episodic extremes and their ecological implications.
    • These examples underscore the need for flexible strategies (migration, storage, and dormancy) to cope with unpredictable patterns.

  • Ecological strategies for variable environments

    • Migration
    • A plastic behavior: seasonal movement in response to changing temperature or resource availability.
    • Example: Monarch butterfly migration; depicted with radar-based tracking imagery and a map of migratory routes.
    • Conditions: when resources are limited or local conditions are unfavorable, moving to more favorable regions can maximize fitness.
    • Storage (resource accumulation)
    • When migration is not feasible, organisms store energy or resources to endure harsh periods.
    • Examples: fat reserves in animals; storage in plant tissues (e.g., roots) that serve as reserves after disturbance (e.g., fire).
    • Dormancy (metabolic downregulation)
    • Dormancy reduces metabolism during unfavorable periods and includes several forms:
      • Diapause: partial or complete physiological shutdown; common in insects facing drought.
      • Hibernation: reduced metabolism and lower body activity in mammals.
      • Aestivation: shutdown in hot/dry conditions (e.g., snails, desert tortoises, crocodiles).
      • Torpor: brief dormancy with reduced activity and body temperature (e.g., some birds and mammals).
    • Dormancy can be triggered by environmental cues and allows survival when active growth is not possible.
    • Adaptations to prevent freezing and water balance
    • Some animals can survive freezing by producing antifreeze compounds and by forming extracellular ice rather than intracellular ice.
    • Notable examples include certain Notothenioids (antifreeze adaptations).
    • Plants cope with water scarcity through physiological and structural strategies:
      • Modified photosynthetic pathways: C4 and CAM.
      • Changes in leaf area to root area ratio to reduce water loss.
      • Dormancy or leaf loss during drought.
      • Boundary layer formation with spines/hairs to reduce evaporation.

  • Temperature and water balance: physiological and behavioral responses

    • Temperature adaptations
    • Isozymes confer enzyme performance at different temperatures; e.g., goldfish can swim fast when acclimated to cold vs warm temperatures.
    • Many animals move to microhabitats to regulate body temperature (behavioral thermoregulation).
    • Desert iguanas regulate body temperature by basking, seeking shade, or burrowing.
    • Notothenioid fishes display antifreeze adaptations to prevent freezing in polar waters.
    • Water balance and plant strategies
    • Water acquisition via soil uptake and loss via transpiration through stomata.
    • Plants reduce water loss by adjusting photosynthetic pathways, leaf-to-root area ratios, and through dormancy or leaf shedding.

  • Foraging theory and ecological decision-making

    • Optimal foraging theory (OFT) framework
    • Foragers optimize trade-offs between energy intake and costs such as search time, handling time, and predation risk.
    • Core components:
      • Time and energy budgets determine when and where to forage.
      • Diet composition reflects the most profitable resources given acquisition costs.
      • Diet mixing can meet nutrient requirements when single items are suboptimal.
    • Central place foraging (CPF)
    • Definition: a foraging strategy where resources are brought to a central place (e.g., nest with young).
    • Trade-off: as forager travels farther, encountered resources increase but travel costs and load to carry back increase, reducing marginal returns.
    • Decision rule: for sites farther away, allocate more time to searching and collect more food per trip to offset travel costs.
    • Energy-return calculus: total energy gained per trip declines with distance unless compensated by increased resource intake per trip.
    • Key metrics: travel time (T), searching time (S), and energy gained (E).
    • Core relation (conceptual): foraging decisions balance travel costs against energy gains to maximize long-term fitness.
    • Optimal diet and handling time
    • Foragers choose prey items by profitability: energy gained per unit time, given by
      ext{Profitability} = rac{E}{h}
      where E is the energy content of the prey and h is the handling time.
    • If the most profitable prey is rare, foragers supplement with less profitable items to maintain energy intake.
    • Diet mixing and nutrient balance
    • Some foragers consume a mix of foods to ensure a complete set of necessary nutrients; e.g., American grasshopper nymphs grow faster on mixed diets, even if individual plants are low quality.
    • Risk-sensitive foraging
    • Foraging decisions are influenced by predation risk and other dangers; even high-energy rewards may be avoided if risk is high.
    • Experimental examples show reduced foraging time in the presence of predators, illustrating a fitness cost through reduced food intake and potentially fewer offspring.
    • Case study visuals and measurements
    • Example of predation risk manipulation: control vs. predator-present treatments show significant reductions in foraging time.
    • Stats (study design reference): 8 replicates per treatment; 65 minutes; ~18% reduction in foraging time when predators are present; reported as P < 0.05 in a Student’s t-test.

  • Examples and empirical ties

    • Elevation and reaction norms (Clausen, Keck & Heisey, 1948)
    • The California transect study set up a gradient from coastal to alpine environments to examine environmental responses of climatic races in Achillea (yarrow).
    • Findings documented via ducting of stems and other growth traits across sites, illustrating plastic responses and genetic differences.
    • Foraging and predation ecosystems
    • Burmese python example: extreme plasticity in digestive morphology in response to prey availability – when a large meal is consumed, intestinal length and heart size increase to extract more nutrients; after digestion, these tissues revert to baseline to avoid costs of maintaining large organs.
    • Temperature adaptations and microhabitat selection
    • Desert iguana example: behavioral thermoregulation through basking, shade seeking, and burrowing to regulate body temperature.
    • Reproductive strategies and mating systems
    • Inbreeding depression: reduced fitness due to mating among relatives, leading some species to delay reproduction or outcross when mates are available.
    • Hermaphroditic organisms (e.g., pond snails) can self-fertilize if mates are unavailable, but self-fertilization often results in reduced egg production.

  • Practical and real-world implications

    • Climate variability and species responses
    • Variation in climate drivers (solar radiation, ocean currents, albedo, topography) can alter habitat suitability and selective pressures.
    • Plasticity and reaction norms allow species to persist across shifting conditions, but limits exist based on cue reliability and genetic variation.
    • Conservation and management relevance
    • Understanding migration, storage, and dormancy strategies helps predict species resilience to droughts, heatwaves, fires, and storms.
    • OFT and risk-sensitive foraging provide a framework to predict how animals might alter foraging in changing predator landscapes and resource distributions.

  • Notable formulas and quantitative references to include in study notes

    • Phenotype expression as a function of genotype and environment:
      ext{Phenotype} = f( ext{Genotype}, ext{Environment})
    • Genotype × Environment interaction leading to phenotype:
      ext{Genotype} imes ext{Environment}
      ightarrow ext{Phenotype}
    • Energy gain per unit time in central place foraging (conceptual):
      ext{Energy gain per unit time} \ = \frac{E}{T + S}
      where E = energy per prey item, T = travel time, S = search time.
    • Profitability (handling-time-based) in diet optimization:
      ext{Profitability} = rac{E}{h}
      where E = energy content, h = handling time.

  • Summary takeaways for exam prep

    • Understand why variable environments select for plasticity and variable phenotypes.
    • Distinguish acclimation from adaptation and physiological plasticity from long-term evolutionary change.
    • Be able to describe central place foraging and the logic of optimal diet and diet mixing, including the role of handling time and energy gains.
    • Recognize how predators and enemies shape phenotypic traits and foraging decisions (risk-sensitive foraging).
    • Recall examples that illustrate plastic responses across temperature and water availability, dormancy strategies, and migratory behavior.
    • Remember the key quantitative tools (conceptual equations) used to evaluate foraging decisions and trade-offs, and how to interpret statistical results like P-values in ecological experiments.