Exam 1

EXAM STRUCTURE

• 100 points total

  • 40 points: multiple choice / multiple answer / matching

  • 40 points: short answer

  • 20 points: dichotomous key application

• Important to note:

  • You must state the traits used to reach your identification in the dichotomous key section

  • Emphasis on understanding and reasoning rather than memorization

NATURAL HISTORY & OBSERVATIONAL SCIENCE (≈25%)

WHAT IS NATURAL HISTORY?

• Possible meanings:

  • A written account of scientific knowledge about the natural world

  • The practice of collecting and recording observations of nature

• Informed primarily by observational study (less by experimental methods)

• Typically organism-focused:

  • Plants

  • Animals

  • Fungi

• Can include studies on:

  • Habitats (e.g., James River rockpools)

  • Ecosystems

  • Geological/climatological phenomena

WHAT DEFINES MODERN NATURAL HISTORY?

• Record of Knowledge

  • Written accounts, often illustrated

  • Cataloged locations and specimens

• Empirical Observation

  • Ideally firsthand experience

  • Secondhand anecdotes noted with intent to confirm or disprove

• Systematic Approach

  • Organizes observations into hypotheses and theories

  • Example question: How do species change over time?

  • Example hypothesis: Similar fossils/plants in South America & Africa suggest continental connection

• Universal Accessibility

  • Intended to be accessible to all people

HISTORICAL CONTEXT

• Term 'natural history' popularized during the Age of Contact (1500–1700s)

• Historical roots trace back to the Roman Empire

• Notable work: Pliny the Elder’s Naturalis Historiæ (77 CE)

• Natural history transitioned from cultural knowledge to a central scientific pillar by the 19th–20th centuries

• Major driving forces:

  • Taxonomy (classification of organisms)

  • Biogeography (distribution of species)

NATURAL HISTORY & CONSERVATION

• Use of citizen science platform iNaturalist:

  • Aids in cataloguing biodiversity

  • Records date, time, and location of observations

  • Suggests species identifications

  • Data shared with scientists and land managers

  • Important to upload own photos only; use field notes + keys to confirm identification

• Grinnell Method:

  • Focus on detailed field notes

  • Emphasis on documentation of location, time, habitat, and behavior

  • Creates baseline records for future comparative studies

ETHOLOGY & BEHAVIOR

ETHOLOGY DEFINED

• Ethology: the study of animal behavior

• Notable aspect: behaviors should be described descriptively rather than functionally unless certain

• Example distinction:

  • Descriptive: "Head bobbing with wing extension"

  • Functional: "Mating display" (only functional when proven)

PROXIMATE vs ULTIMATE CAUSES

• Proximate Cause:

  • Mechanism behind a behavior, such as

  • Hormones

  • Temperature

  • Neural triggers

• Ultimate Cause:

  • Evolutionary reason for a behavior, such as fitness benefits

• Example:

  • Bird singing in spring:

  • Proximate: Increased daylight triggers hormone production

  • Ultimate: Purpose of attracting mates / defending territory

DICHOTOMOUS KEYS

• Defined as a stepwise series of paired statements

• Each step narrows the identification process

• Must state the traits used at each step

• Example structure:

  • 1a. Leaves opposite → go to step 2

  • 1b. Leaves alternate → go to step 3

• Essential tasks:

  • Identify trait

  • Follow logical steps

  • Justify final answer

PHENOLOGY (≈25%)

WHAT IS PHENOLOGY?

• Study of the timing of biological events

• Examples of biological events:

  • Flowering

  • Leaf-out

  • Migration

  • Fruiting

• Field assignment examples:

  • Budding

  • Flowering

  • Leafing

  • Fruiting

SPRING VANGUARD

• Definition: First species to emerge in spring

• Examples from slides:

  • Skunk cabbage (melts snow)

  • Salamanders breeding in vernal pools

  • Yellow Trout Lily flowering before canopy closure

  • Cherry blossoms

WHY STUDY PHENOLOGY?

• Helps detect effects of climate change

• Example from analyses conducted in class:

  • Test regarding changes in cherry blossom timing over 70 years

  • Test if latitude predicts flowering date for species such as Yellow Trout Lily and skunk cabbage

PHENOLOGY & REGRESSION

LINEAR REGRESSION

• Formula: y = m imes x + b

  • Where:

  • m = slope

  • b = intercept

  • R^2 = proportion of variance explained

• Example from slides:

  • Linear equation: y = -0.54x + 44.61

  • R^2 value of 0.1145

INTERPRETATION OF RESULTS

• Negative Slope: :- As latitude increases, temperature tends to decrease.

• R² Value Interpretation:

  • R^2 = 0.1145 suggests latitude explains approximately 11% of temperature variance

• Analysis of points relative to the regression line:

  • Points close to the line indicate a strong relationship

  • Flat slope suggests a weak or nonexistent relationship

• Prediction Example:

  • Latitude of 40.2: Predicted summer temperature is approximately 22.9°C

LIFE HISTORY & POPULATION ECOLOGY (≈25%)

LIFE HISTORY DEFINED

• Focuses on patterns of survival and reproduction throughout the lifespan

• Different from natural history, as it emphasizes quantitative survival and reproductive strategies

EXPONENTIAL GROWTH

• Characteristic: Density independent

• Formula: Nt = N0 * e^{(r t)}

  • Where:

  • r = intrinsic rate of increase

• Produces a J-shaped growth curve assuming unlimited resources

LOGISTIC GROWTH

• Characteristic: Density dependent

• Includes carrying capacity (K)

• Produces an S-shaped curve

• Key point: Growth slows as population density approaches carrying capacity (K)

• Graph Interpretation:

  • Exponential growth appears as an accelerating curve directed upwards

  • Logistic growth shows rapid increase leveling off near K

• Important note: Carrying capacity may not be static over time

R- vs K-SELECTED SPECIES

• r-selected Species:

  • Traits:

  • Short-lived

  • Produces many offspring

  • Low parental investment

  • Frequently follows Type III survivorship curve

• K-selected Species:

  • Traits:

  • Long-lived

  • Produces few offspring

  • High parental investment

  • Frequently follows Type I survivorship curve

SURVIVORSHIP CURVES

• Type I Curve:

  • Characteristic of high juvenile survival

  • Mortality increases with age

• Type III Curve:

  • Characteristic of high juvenile mortality

  • Survivors tend to live long lives

• Case Study: Allen Cay Iguana

  • Used to illustrate survivorship and implications for life history strategies

LIFE HISTORY TABLES

• Components of the table include:

  • l_x = survivorship

  • mx or qx = mortality

  • b_x = birth rate

  • lx * bx = age-specific reproductive contribution

• R₀ (Lifetime reproductive success):

  • Sum of lx * bx

• T₀ (Generation time):

  • Defined as the weighted average age of reproduction

  • Calculate by dividing sum of (age * lx * bx) by R₀

EMPIRICAL SCIENCE & DATA TYPES (≈25%)

DATA TYPES

• Nominal Data:

  • Characteristics: No inherent order

  • Examples: Species, sex, flower color

• Ordinal Data:

  • Characteristics: Ordered sequence

  • Example: Stages of plant development (budding → flowering → fruiting)

• Continuous Data:

  • Characteristics: Can take any decimal value

  • Examples: Body length, temperature

• Discrete Data:

  • Characteristics: Only whole numbers

  • Example: Count of ducks

• Impact of Data Types:

  • Determines graph choice

  • Alters hypothesis wording

  • Influences choice of statistical tests

NULL vs ALTERNATIVE HYPOTHESES

• Null Hypotheses (H₀):

  • Categorical predictor & numeric response: H₀ signifies no difference exists

  • Numeric predictor & numeric response: H₀ signifies no relationship exists

• Alternative Hypotheses (HA):

  • Indicates existence of a difference or relationship when applicable

REGRESSION INTERPRETATION RECAP

• Key elements of regression analysis:

  • Slope reflects direction and magnitude of the relationship

  • R^2 indicates explanatory power

• Interpretation of R² values:

  • Strong R^2 indicates that the data accounts for a large percentage of variance

  • Weak R^2 indicates the involvement of many other factors beyond the studied variables

COMMUNITY ECOLOGY (BRIEF INTRO)

• Definition: A community is defined as a group of interacting species

• Characteristics:

  • Boundaries of communities are often poorly defined

  • Species within communities must overlap in both space and time

ADDITIONAL CONTENT

• Contains all equations shown

• Examples of regression values

• Case study of iguana life history

• Specific species examples (skunk cabbage, trout lily, salamanders, cherries)

• Data-type examples used in slides

• Definitions as presented in the class material

• Guidance for graph interpretation