chapter 1 and 2 ecology Flashcards
the study of the interactions that determine the abundance and distributions of organims
ecology
a group of interacting organisms and their physical envioronment
ecosystem
the current geological epoch that is characterized by the large and influential effects humans have on the planet
Anthropocence
anthropo- human
cene- recent
since the 1950s (beginning of the anthropocene) what did we see increases in?
- population
- real GDP (total monetary value of goods and services)
- primary energy use
- carbon dioxide
- methane
- nitrogen to coastal zone
- surface temperature
- tropical forest loss
- ocean acidification
the sudden, intense increase across a range of planetary metrics due to human influence (starting in the 1950s)
the great acceleration
an impact on earth’s ecology that is caused by human actions
anthropogenic effects
what are the 4 approaches for doing ecological science?
- observation and natural history
- experimental ecology and null hypothesis testing
- multiple hypothesis testing with best fit comparisons
- ecological modelling
the first ecologists were called
naturalists (a person who studies natural organisms in a deep context)
“just so stories” a narrative that explains an observed pattern without proof and is believed correct because it sounds right
ad hoc fallacies
key aspects are also called
focal factors
manipualted aspects are called
treatments
nonfocal elements
extraneous factors
a statement proposing that the focal explanatory factors DO NOT have an effect
null hypothesis
a statement proposing that the focal explanatory facotrs DO have an effect
alternative hypothesis
a conceptual model that is translated into the language of mathematics
mathematical model
a theoretical construct that specifies how various components of a system fit in relation to each other
conceptual model
a model that can be solved mathematically or for which the relationships among the variables can be interpreted through math
analytical models
a model that is solves or run on a computer multiple times to explore outcomes with different parameters
simulation model
can be conceptual or mathematical
carefully watching nature and natural phenomena and constructing narrative explanations
observation and natural history
hypothesis testing through the use of manipulative experiments
experimental ecology and null hypothesis testing
- used to study smaller organisms under shorter timescales
results and conclusions are based on the strength of evidence supporting one or more of the competing hypotehses
multiple hypothesis testing with best fit comparisons
- used in the context of large scale studies in which multiple causative factors are at play
the application of math or mathematical thinking to measured or counted information in order to gain a deeper understanding of a topic
quantitative reasoning
- usually involves numbers, measuring etc (quantity not quality)
ability to collect, analyze, make sense of, and communicate the meaning of quantitative and qualitative data
data literacy
a changeable value within an equation
variable (generally uppercase letters)
an element in a mathematical model that will not change across iterations of a model
parameters (generally lowercase letters)
a mathematical model that will always produce the same result if the starting conditions are the same
deterministic model
a type of model that lets the parameter values to change between iterations, therby allowing the results to vary
stochastic models
a data type associated with no inherent numerical value and that is defined by names (ex. blue, yellow,etc)
nominal categorical variables
a data type that is not characterized by a numerical value but it has a natural order (ex. small, medium, large)
ordinal categorical variables
A data type whose possible values are numbers that can take on any value, including fractions and decimals (e.g., acorn length).
continuous numerical variable
a data type whose possible values are numbers but which can only occur on whole numbers, not fractions or decimals
discrete numerical variables
A statistical term describing the probability of collecting observed data if the null hypothesis is true; in practice this often means the probability of getting the statistical results of an experiment by random chance.
p-value
