Introduction to Ecology and Evolution Flashcards
Fundamentals of Ecology and Environmental Science
Definition of Ecology:
Ecology is the scientific study of interactions between living organisms and their environment.
The term interaction is the central component of ecology. It focuses on how organisms affect and are affected by both biotic (living) and abiotic (non-living) components of their surrounding environment.
Distinction Between Ecology and Environmental Science:
A major misconception exists—often stemming from high school or Advanced Placement (AP) Environmental Science curricula—where ecology and environmental science are treated as synonymous.
Environmental Science: Focuses exclusively on the physical, chemical, and biological conditions of the environment itself without requiring a focus on organismal interactions.
Example 1: Measuring a drop in lake water level during a drought and testing if the salt concentration or pH has changed.
Example 2: Testing a body of water for high mercury concentrations or elevated temperatures.
Example 3: Measuring atmospheric concentrations of pollutants, such as nitrous oxide () or carbon dioxide ().
Ecology: Formally incorporates living organisms and analyzes how those organisms respond to, interact with, or alter those environmental changes.
Example 1: Studying how an increase in lake water pH leads to a rapid bloom of specific microorganisms.
Example 2: Investigating whether elevated air pollution increases the incidence of lung cancer in humans (treating human populations as ecological organisms).
Example 3: Assessing how changes in environmental pollutants alter the reproductive capacity of a specific species.
Core Questions in Ecology:
Where does an organism live?
Why does it live there? (Determined by whether the organism can tolerate the specific environmental conditions of that habitat).
How many individuals are present?
Why is that specific population size maintained?
What Ecology Is Not:
Environmental Activism / Environmentalism: Social or political movements aimed at protecting nature (e.g., organization tactics used by Greenpeace).
Resource Management: Applied practice fields such as wildlife management, fishery management, soil resource management, or forestry.
Conservation Biology: Applied discipline focused on preserving biodiversity and designing conservation solutions.
Role of the Ecologist: Ecologists do not prescribe policy solutions or perform management fixes. Ecologists define, quantify, and explain what is occurring and how organisms respond to environmental change. Resource managers and conservation biologists then utilize ecological data to formulate and execute solutions.
Biological Scale and Smallest Unit of Ecology:
General biology studies hierarchical levels down to cells, biological molecules, proteins, DNA, and subatomic particles.
In ecology, the smallest fundamental unit of study is the individual organism. Ecological inquiries do not go below the level of the individual organism because ecology fundamentally focuses on how an individual interacts with its environment.
Hierarchical Levels of Ecological Organization
Organismal Ecology:
Focuses on the behavioral, physiological, and morphological mechanisms used by an individual organism to interact with its environment.
Behavioral Ecology: A sub-discipline of organismal ecology examining individual decisions and responses.
Example 1: Observing a dog that immediately runs to the kitchen upon hearing the rustle of a string cheese package opening in another room.
Example 2: Studying a bat species that emerges from its roost exclusively during dawn.
Example 3: Investigating the specific floral preference of a butterfly species.
Population Ecology:
Population Definition: A group of individuals belonging to the same species that inhabit a defined geographic area at a given time (e.g., the human population of Edinburg, Texas, or the United States).
Biological Definition of Species: Two individuals are considered the same species if they can interbreed in nature and produce viable, fertile offspring.
Evolutionary Connection: Evolution acts directly on populations, not on single individuals. A genetic mutation in a single individual does not constitute evolution; evolutionary change requires shifts in gene frequencies across a population over time.
Scope of Study: Examines population dynamics, including birth rates, mortality rates, immigration/emmigration rates, and overall population growth rates.
Example 1: Analyzing how the COVID-19 pandemic impacted human birth rates from to .
Example 2: Evaluating how regional conservation programs impacted the population size of ocelots in the Lower Rio Grande Valley.
Example 3: Determining infant mortality rates resulting from Zika virus infections.
Analytical Distinction (Population vs. Community):
If gray wolves are reintroduced into Yellowstone National Park and a study measures the resulting numeric decline in the elk population, the study focuses on Population Ecology because the primary metric measured is population dynamics of a single target species.
If the study instead investigates the behavioral hunting strategies used by wolf packs to capture young elk, it shifts to Organismal/Behavioral Ecology.
Community Ecology:
Community Definition: Populations of multiple distinct species living and interacting within a defined geographic area.
Scope of Study: Focuses on interspecific interactions, such as predation, competition, parasitism, mutualism, and food web dynamics.
Example 1: Studying an environment where dense vegetation harbors mosquito populations carrying the Zika pathogen, which subsequently bite and infect human hosts (involving interactions among plant species, vector insect species, viral pathogen species, and human host species).
Example 2: Investigating the predator-prey interaction of a lion pride hunting a herd of buffalo.
Example 3: Studying how the presence of wolf packs alters elk foraging locations and vegetation recovery patterns across a landscape.
Ecosystem Ecology:
Ecosystem Definition: The community of living organisms (biotic factors) interacting directly with the non-living physical and chemical components (abiotic factors) of their environment.
Abiotic Variables: Include precipitation/rainfall patterns, temperature fluctuations, water levels, pH, dissolved oxygen, solar radiation, and soil nutrient levels.
Scope of Study: Focuses on energy flow and biogeochemical/nutrient cycling (e.g., microbial decomposition of organic matter releasing inorganic nutrients for plant uptake).
Example 1: Analyzing how a heavy rainfall event increases standing water, triggering a surge in mosquito breeding and subsequent viral disease transmission.
Example 2: Studying how agricultural water drainage lowers lake levels, altering dissolved oxygen, aquatic vegetation, and fish survival.
Landscape Ecology:
Landscape Definition: A mosaic of multiple interconnected ecosystems spanning a large geographic area.
Components: Encompasses both natural systems (forests, rivers, scrublands) and human-built/modified systems (agricultural fields, canals, residential developments, commercial zones, road networks, turf grass lawns).
Scope of Study: Examines ecological processes, disturbance spread, and material movement across extensive spatial scales.
Example 1: Evaluating how prolonged, multi-year drought across Texas affects agricultural output, forest mortality, canal water retention, and urban water supplies simultaneously.
Example 2: Analyzing landscape urbanization in the Lower Rio Grande Valley, where native scrubland and citrus/corn agriculture are progressively converted into residential housing, dense asphalt road networks, and ornamental landscapes.
Example 3: Investigating a glacial lake outburst flood in the Himalayas of Nepal, where melting high-altitude ice causes massive downstream flooding, severe landslides, and destruction across alpine, riverine, and forest ecosystems.
Biosphere / Global Ecology:
Biosphere Definition: The sum of all Earth's ecosystems—the global ecological system incorporating all life and its planetary relationships.
Scope of Study: Focuses on global-scale processes, planetary climate systems, and broad atmospheric interactions.
Example 1: Examining how global greenhouse gas emissions drive climate change, causing elevated Himalayan temperatures, rapid glacial melting, and downstream flood disasters.
Example 2: Modeling global sea-level rise driven by thermal expansion and ice sheet decay.
Example 3: Evaluating global population declines in an endangered species caused by widespread acid precipitation.
Interdisciplinary Nature of Ecology and Evolution
Cross-Disciplinary Integration:
Ecology requires integration with diverse scientific disciplines:
Genetics & Molecular Biology: Understanding how genotype dictates phenotype and environmental adaptability.
Physiology & Biochemistry: Analyzing metabolic and functional responses of organisms to physical stressors.
Geology, Hydrology & Atmospheric Sciences: Understanding how substrate, water flow, humidity, and climatic patterns shape habitats.
Mathematics, Statistics & Physics: Utilizing quantitative models, statistical hypothesis testing, spatial modeling, and Geographic Information Systems (GIS).
Ecology and Evolution as Evolving Sciences:
Both fields continually adjust as environments change, pathogens emerge, and species adapt.
Case Study (COVID-19 Pandemic):
Initial human behavioral responses included universal masking, social isolation, and extreme surface disinfection of inanimate objects.
As clinical data revealed primary respiratory aerosol transmission, surface wiping was abandoned.
Vaccine deployment strengthened immune responses while viral strains shifted, altering human behavioral protocols and epidemiological risk profiles over time.
Variability in Organismal Response: Individual organisms within a species respond variably to environmental shifts based on physiological state and background.
Example: A sudden drop to freezing temperatures in a room causes shivering; individuals with jackets put them on, sick individuals may leave immediately, and others wait out the stress. Unpredictable behavioral variation necessitates continuous scientific inquiry.
The Scientific Method in Ecological Science
Sequential Steps of the Scientific Method:
Observation: Noticing an unusual event, pattern, or anomaly in nature that deviates from baseline conditions.
Medical Context: Realizing one has a high body temperature ().
Ecological Context: Walking across campus and observing a cluster of dead birds lying on the ground.
Question Formulation: Asking explicit questions about the underlying cause of the observation.
Medical Context: "Why am I experiencing a fever?"
Ecological Context: "What caused this localized mortality event in the bird population?"
Hypothesis Generation: Formulating testable, falsifiable explanations grounded in background knowledge and scientific literature.
Hypotheses for Bird Mortality: Excessive heat stress, opening of a local hunting season, outbreak of an infectious disease, or ingestion of toxic agricultural pesticides applied on campus grounds.
Experimentation and Data Collection: Designing structured protocols to gather empirical data and test hypotheses.
Medical Context: Drawing blood, conducting urine cultures, taking chest X-rays, and prescribing targeted antibiotics.
Ecological Context: Recording daily local temperatures, testing soil and bird tissue samples for chemical residues, and necropsying avian specimens.
Data Analysis and Evaluation: Comparing empirical results against hypothesis predictions.
If data support the hypothesis across multiple independent trials, species, and locations, the explanation gains strong support and can eventually contribute to a scientific Theory.
If data refute the hypothesis (e.g., fever persists after antibiotic treatment, or zero pesticide residue is found in birds), the hypothesis is rejected, and a new hypothesis must be formulated and tested.
Ecological Data Variables, Graphing Protocols, and Visualizations
Types of Variables:
Dependent Variable: The response or outcome variable being measured (e.g., mortality rate of birds). Placed strictly on the y-axis.
Independent Variable: The factor being manipulated or categorized (e.g., concentration of chemical toxins in ). Placed strictly on the x-axis.
Control Variable: Environmental factors held constant across treatments during an experiment (e.g., ambient temperature, light availability, cage dimensions).
Types of Data:
Quantitative / Numeric / Continuous Data: Measured numerical values along a continuous scale.
Examples: Plant height in centimeters (, , , ), leaf count, leaf width, toxin concentration.
Qualitative / Categorical Data: Non-numerical observations sorted into discrete categories or descriptors.
Examples: Plant species name, flower color, qualitative height categories (e.g., short, medium, tall).
Data Visualization Standards and Graph Selection:
Bar Graph: Used when plotting one categorical independent variable against one continuous numerical dependent variable (e.g., comparing mean plant height across species A, B, and C, or comparing mean mortality across distinct drug treatments).
Includes error bars displaying standard deviation () or standard error of the mean ().
Scatter Plot: Used to display associations and relationships between two continuous quantitative variables (e.g., plotting chemical toxin concentration in on the x-axis against bird mortality rate on the y-axis).
A mathematical line of best fit (trendline) is fitted through the scatter points to determine positive, negative, or neutral correlation.
Line Graph: Used to plot continuous quantitative data tracked over uniform, sequential time intervals (e.g., bird mortality rate tracked monthly from January through October).
Points are connected chronologically to visualize temporal trends.
Pie Chart: Visualizes proportional breakdowns of a whole (rarely utilized in advanced ecological analysis).
Box Plot: Displays continuous data distributions, displaying the median, upper and lower quartiles, and variance ranges above and below average values.
Stacked Bar Graph: Used to illustrate sub-category proportions within discrete sample categories (e.g., visual genomic or microbiological analyses displaying relative microbial composition percentages across individual patient samples).
Experimental Methodologies in Ecological Research
Observational Studies:
Involves measuring and recording natural conditions without directly manipulating environmental variables.
Example: Collecting wild dead birds found on campus, dissecting tissue samples, and measuring baseline chemical toxin concentrations present in their systems.
Manipulative Experiments:
Involves direct experimental control and systematic manipulation of independent variables across treatments while maintaining controlled baselines.
Example: Housing test birds in laboratory enclosures, administering precise toxin dosages (, , ) across controlled age groups (hatchlings vs. mature adults) and controlled thermal settings ( vs. ), and tracking mortality rates.
Critical Requirements of Experimental Design:
Controls: Baseline groups where the manipulated independent variable is omitted or held at ambient levels to isolate causation.
Replication: Performing experimental treatments on multiple independent experimental units to account for random individual variation and satisfy statistical power requirements.
Randomization: Randomly assigning treatments and positioning experimental units (e.g., shuffling cage positions across a lab space) to eliminate spatial bias caused by localized light, drafts, or temperature variations.
Microcosms and Mesocosms:
Microcosm Definition: Simplified, enclosed physical systems designed to replicate key features of natural ecosystems within controlled laboratory or greenhouse environments (e.g., test tubes, aquariums, beakers, small artificial ponds).
Purpose: Allows ecologists to perform manipulative experiments involving hazardous substances (such as aquatic chemical pollutants) without releasing toxic pollutants into natural lakes or rivers.
Field Experiments and Real-World Case Studies:
Manipulative experiments executed directly in natural field settings provide high realism, but risk unexpected ecosystem impacts.
Agricultural Field Case Study:
A -year government-funded field research project was executed in the Lower Rio Grande Valley to evaluate agricultural yield strategies.
Researchers applied soil and crop management techniques that were highly successful in cool, high-rainfall northern states like Nebraska and Iowa.
When applied to the hot, semi-arid conditions of the Rio Grande Valley, the management intervention failed drastically, causing a reduction in crop yield.
The study demonstrated long-term negative legacy effects on field soil structure, prompting local farmers to terminate the project.