bio iq final prep - exam 1 (biodiversity to stats)

biodiversity

total number of species in an environment

where do you find high diversity?

tropical areas

where do you find low diversity?

polar environments

ecology

the study of how individuals interact with others of their own species

• how they interact with individuals of different species

• how these interactions can change depending on the physical and biotic environment

intraspecific interaction

interactions between individuals of the same species

• they compete, cooperate, reproduce

• intraspecific competition is more intense, they are fighting for the same resources

interspecific interactions

interactions between individuals of different species

• compete, mutualism, predation, parasitism

geographic range

the geographic boundaries occupied by a species

habitat

the array of physical and biological factors present in an area that permit a specific species to live there

niche

the ecological role of a species

generalist

can live in a variety of settings or eat a broad range of foods

• more likely to shift their geographical range to keep up with climate change

specialist

can live only in a limited set of conditions or has a restricted diet

• more sensitive to habitat loss

organismal

individuals that are capable of breeding with one another

population

individual of the same species living and interacting with each other

species

individuals that are capable of breeding with one another and are reproductively isolated from other groups

adaptation

how well-suited an individual is to its environment

fitness

how successful an individual is in passing genes on to the next generation

genotype

an individual’s genetic makeup

phenotype

an individual’s observable characteristics resulting from the interaction of its genotype with the environment

• a better adapted phenotype will have higher fitness

evolution by natural selection

a change in genotype frequencies in a population over generations because of differences in the survivorship and/or reproduction of their phenotypes

• not all populations experience selective pressure

• not all species have the same length of time per generation

• sexual reproduction creates new combinations of genes and mutation creates new alleles

agents of natural selection

typically, an external force or event that effects survival and/or reproduction

• drought and aridification

• change in precipitation regime

• change in water pH or temp

• presence of a parasite or disease

• change in soil chemistry

requirements for evolution by natural selection

• there must be variation in the population

• that variation must be heritable (genetically-based)

• that variation must affect fitness

constraints on adaptive evolution

• mutations are random with respect to fitness—just because a mutation would be very advantageous or maladaptive does not make it more or less likely to appear

• tradeoffs are too costly

• physical or chemical constraints

• selection is too rapid relative to generation time…or selection is too variable

what are species going to do in response to a rapidly (and erratically) changing climate?

• adjust: a flexible change in behavior or phenology that is not genetically based

• adapt: evolve to be better suited to the new conditions

• migrate: move with their preferred climate

• extinct: die

phenology

period of activity, timing of life’s major events (growing, reproducing, surviving)

phenological shift

a temporal shift in phenology

phenological match

the alignment of penologies of two interacting species

phenological mismatch

the misalignment of phenologies of two interacting species

sensitivity of populations to phenological mismatch depends on

1. the importance of the interaction: depends on how sensitive the species’ demography is to the vital rate affected by the interaction

2. the details of shift in the phenologies:

   • the temporal breadth of overlap in the interaction

   • the amount of shift by one (or both) species

tip of the proverbial iceberg in terms of how phenological shifts can alter ecological interactions and outcomes

• apex predators

• meso predators

• herbivores and pollinators

• plants

mutualism

reciprocal exploitation between species in which the net effect is beneficial for both despite costs

goals of all analyses

to see if there is a relationship between two measurable things

normal distribution

• a probability distribution that is symmetric about the mean

• data near the mean are more frequent in occurrence then data far from the mean

• most statistical test assume that the data are distributed in this way

positive skew

skewed to the right

negative skew

skewed to the left

variance

measures the average degree to which each point differs from the mean and is calculated as the average of the squared difference of each data point from the mean

standard deviation (SD)

the spread of a group of numbers from the mean and is calculated as the square root of the variance

standard error of the mean (SEM)

is the SD divided by the square root of the sample size (n)

the t-test

tests whether the means of 2 populations are significantly different from each other

what does the test statistic tell us?

the magnitude of the effect

what does the p-value tell us?

whether the effect/difference is real, aka “statistically significant”…the likelihood we committed a type 1 error

type 1 error

reject the null hypothesis when in fact there are no differences between groups…false positive

type 2 error

fail to detect a significant difference when one does in fact exist…false negative

2 factor ANOVA

what if two independent factors are suspected of affecting your response variable?

R²

the coefficient of determination

• statistical measure in a regression model that explains the variation in a dependent variable based on the independent variable

• a higher R² = better fit to the data

• perfect fit = 1.00

same letter

no difference

correlation (C)

two measurements vary in tandem; no causal relationship; both responding to the same underlying driver

regression (R²)

two measurements vary in tandem; necessarily implies causal relationship

• both may vary in a positive or negative fashion; linear or nonlinear response

what does R² mean?

it is the proportion of variation in Y that is explained by X

• bounded by 0 and 1 (0.0 - 1.0)