Evolution and Ecology: Understanding the Dynamics of Organisms and Populations
Evolution
Change over time in the proportions of individual organisms that differ genetically.
Microevolution
Change over time in gene frequency within a population.
Macroevolution
Change over time in the proportions of species that determines the diversity of a taxonomic group.
New Organism Types
Micro-Mutation & Macro-Speciation
Alteration of Proportions of Different Organism Types
Micro-genetic drift, Natural Selection & Macro Adaptive Radiation
Natural Selection = not random, leads to evolution based on genotype & phenotype.
Conditions for Natural Selection
- More offspring than support (not everyone survives)
- Phenotypic variation & inheritance
- Traits give some advantage over others
- Traits increase fitness. Fitness: Number of babies produced by phenotype, how many times they reproduce, number of babies every time.
Selection
How fitness varies over different phenotypes. 4 types: 1. Stabilizing: intermediate size has most fitness, trait size means don’t change, therefore decrease in variation-no extremes favored. 2. Directional: Extreme end (small or big) favored, means move in direction of fitness, variation decrease over time. 3. Disruptive: both extreme ends (big/small) favored, next gen has bimodal (2 humps) distribution. 4. Frequency dependent: fitness depends on relative frequency of other phenotype, (-) frequency= fitness decreases as it becomes more common.
Speciation
Interruption of gene flow interbred, ecological process interacts with selection & drift to create new species à cladogenesis (1 species à 2 daughter species.) 3 types: 1. Allopatric: different country, separated by distance prevent gene flow, population evolve independent. 2. Parapatric: population expands into new habitat within pre-existing range of parent species (plant grow on contaminated soil-parent on uncontaminated). 3. Sympatric: same country, reproductive isolation between 2 groups in continuous contact, barrier to gene flow.
Adaptation
Species have evolved to be better suited for environment.
Ecology
Individual Physiological Ecology
Study of how organisms cope with factors of the environment.
Abiotic Variability
Resources used by one organism made less available to another. Water: use energy to maintain internal water level. Environmental change climate change, nutrition variability, disease, toxin exposure. Temp: organism evolve to regulate body temp. 1. Poikilotherm: body temp changes with environment. 2. Homeotherm: keep constant body temp despite environment. 3. Heterotherms: do both (1 & 2). 4. Ectotherm: change behavior to regulate body temp, don’t use MR. 5. Endotherm: use MR to regulate body temp.
Critical Limits
Freeze to death or heat shock. Performance optima: best condition. Distribution limits: where organism is found due to range of temp/climate it performs optimally in. Adaptation (genetic change- over time)/Acclimation (reversible -quick): how thermal curve can be altered. Homeostasis Costs E, allocate E differently to respond. Climate change: change of biological events, failure to migrate, food availability.
Population Ecology
What makes populations grow in one area?
Population (N)
Group of potentially interbreeding individuals of a single species, inhabiting specific area (1 species @ 1 place). 4 processes change # in a population. Vital Rate: Births (+) & Death (-) Movement: Immigration (+) & Emigration (-). Total rates: rate for total population, UPPERCASE (B,D,I,E). Per-Capita: individual rate LOWERCASE (b,d,i,e). To get Total rate (per capita*pop size) B = b*N and D=dN and I=iN and E = eN. In Close Population: assume ∆N/time is: dN/dt=(b-d) *N (instantaneous rate). Per capita rate of increase close population (r): summarize net balance of per capita births/death, slope=r, If b > d, then r = +. If b < d, then r = –
Density-INDEPENDENT growth
Exponential growth!!! per capita birth/death rates are Independent of the density of the population (not a function of pop density). If b > d, r > 0 à exponential growth (+) of N(t). If b < d, r < 0 à exponential decrease (-) of N(t). If b = d, r = 0 à N(t)is also flat, population stay same/time. In ideal conditions birth/death are maximized, so intrinsic rate of inc is also (rmax): dN/dt = r(max) * N <- describe rate change of N. Add calculated # TO INITIAL POP #. To solve for N @ any time use: Nt=N0 er(max) * t (Continuous Growth) Discrete Growth: only reproduce once a year not continuously. For that Use equation: Nt = λt * N0. HOW TO FIND λ? -> à λ=Nt+1/Nt = 1 + (b – d). If λ>1 population inc. If λ<1 population dec. If λ=1 than pop stay same. Density-DEPENDENT growth: Carrying capacity!! per capita birth/ death rate is dependent on the density of the population. Due to intraspecific competition for resources. K=carrying capacity (stable equilibrium) Decrease Population (b < d), N is above K. Increase population (b > d) N is below K. Equations density-dependent: Birth: b= b0- aN (b0=intercept, a=slope) Death: d=d0-aN. Logistic growth EQUATION
Logistic growth
Exponential growth scaled up to unused proportion of carrying capacity. r as a function of density, r =0 is carrying capacity cuz per capita is zero (stable)
Allee Effect
Density dependence is not a simple linear relationship. Per capita (r) growth rate can increase as a function of density. As Inc. N, Inc. R. Due to: Mate Limit, plants not attracting enough pollinators. Not all individuals are equal: Age, Stage (egg -> adult), Sex, influence impact N. Age Structure: survivorship vs age & reproduction vs age for age structure. Each population has different, Rwanda has high % of young due to high adult mortality, pop grow fast cause reproduce young. Sweden has high% of middle age. Survivorship (lx): pattern of survival for individuals in a population as a function of age. Calculated from cohort tables (population from initial cohort that survive to age x). Always log survivorship on a log scale! Stage structure population: consider stage (not age) that might be important for pop growth rates. Or when vital rates are more tied to stages than (when only one stage reproduces ie; insects) Types of survivorship scales: Type 1: survivorship in juveniles is high – mortality in adults is high. (K-selected: reproduce @ old age/parental care) Type 2: Everyone die at equal rates (constantly vulnerable to predator/disease) Type 3: high survivorship in adults, high mortality in juveniles. (r-selected: don’t care for offspring)
Reproductive Strategies
Semelparity & Iteroparity. Fecundity schedule: avg # of offspring produced for each per female. Life table: show growth rate for an age structured population look @ survivorship (lx) fecundity (mx). Find net productive rate (R0) by summing (lx* mx) values. (R0) > 1: growing population (replaces itself + more) (R0) < 1: decreasing pop (cannot replace itself (R0) = 1: each individual only replaces itself and dies
Stable age distribution
If life table values are fixed, the population will reach a stable age of distribution. Proportion of individuals in each age class is constant.
Metapopulation
Suitable habitat in discrete patches that are occupied by pop., all patches have risk of extinction. Habitat patches NOT ISOLATED. To prevent recolonization, organisms can move around. Pop. dynamic not synchronized. Colonization: movement of individuals from occupied sites to unoccupied sites to form a new local population. Factors affecting colonization: ability to move (distance or mobility). Reasons to move (resource abundance, biotic interaction, disturbance). Factors affecting extinction: disease, resource availability, predation, disturbance, population size (Allee effect). Dispersal: high-quality patch (Source population) may permit (Sink population) to stay in inferior habitat. Pop size goes down if go from good habitat (source) to inferior (sink). r< 0; sink population (N dec) & r >0; source pop (N inc). Rescue effect: high immigration rate protects a population from extinction due to the recolonization. Main island is the dominant source to move to other habitat patches. P= Patches occupied (0-1) if 6 patches and 3 occupied P=0.5. How does # of occupied patch change over time: dP/dt = C – E Simple model: if P=fraction of occupied patches, then expect some patches to go extinct over time (E). E = e*P Colonization Model: C= mP (1-P) (mP= movement from occupied patch to empty patch) Overall EQN: dP/dt = mP (1-P)- eP Occupied patches: C > E go towards eqm (pop inc). C < E not enough patch so go back (pop dec)