Animal Ecology Flashcards
(103 cards)
1
Q
Ecology
A
The scientific study of the interactions that determine the distribution and abundance of organisms
2
Q
Levels of interactions
A
- Between individuals
- Individuals and their environment
- Species
- Species and their environment
3
Q
interactions between species and their environment
A
- interspecific competition
- resource partitioning
- predation
- facilitation
- dispersal
- migration
4
Q
Interactions between individuals and their environment
A
- behavioural ecology
- intraspecific competition
- basic physiological responses
- life history responses
5
Q
Abundance
A
number of individuals (designated by N)
6
Q
What does abundance depend on?
A
- Interactions with their environment
- Interactions with your own species
- Interactions with competing species
- Interactions with predators
7
Q
Properties of communities
A
- diversity
- trophic structure (food webs)
- organisation (biological and physical processes)
8
Q
Why do ecologists care about experimental design?
A
- Allows correct interpretation of results of surveys and experiments
- Avoids confounding factors
- Ensures appropriate level of generality (or specificity) is assigned
- Makes the statistical analysis easier
9
Q
Population
A
Group of individuals of same species occupying a defined place at a particular time
10
Q
Fecundity (natality)
A
- Number of offspring added to population in a given time (B)
- Number of offspring per female per unit time (b)
- Potential reproductive output = fecundity
- Actual reproductive output = fertility
11
Q
Mortality
A
- Deaths in the population in a given time (D)
- Deaths per individual per unit time (d)
- Potential longevity = maximum attainable lifespan
- Realized longevity = actual lifespan
12
Q
Fundamental concepts of population ecology
A
- populations tend to grow exponentially
- populations show self-limitation
- consumer-resource interactions tend to be oscillatory
13
Q
why use instantaneous rate
A
- Better reflects how biological system operate
- Has more intuitive values
- mathematically easier to handle – when instantaneous rate is 0 there is no change, when positive it is increasing and when negative it is decreasing
14
Q
carrying capacity (K)
A
- Number of individuals that can be maintained indefinitely in the population
- Number of individuals that available resources can sustain
15
Q
how does competition affect r?
A
- increased competition results in fewer resources per capita
- birth rate and death rate decrease
- r decreases
16
Q
factors that affect b and d
A
- size
- sex
- life stage
- age
17
Q
cohort life table
A
involve tracking a group of individuals from early life and determining their rate of survival
18
Q
static life table
A
based on data collected from individuals in a population at one time either from dead individuals or individuals based on an age estimator of some sort
19
Q
difficulties in getting cohort data
A
- Tracking animals over time is laborious, often impossible
- Some animals live longer than the researchers who study them, and even more live longer than research funding cycles
20
Q
type 1 survivorship curve
A
high infant survival rates and increased mortality later in life
21
Q
type 2 survivorship curve
A
characterised by constant mortality throughout life
22
Q
type 3 survivorship curve
A
characterised by higher mortality rates in young, with only some individuals surviving to breeding or older ages
23
Q
life cycle graphs
A
- circles for age groups (nodes)
- lines are for survival and reproduction (verticies)
- all transitions must have the same time value
24
Q
life history
A
Schedule of birth, reproduction and death of an individual
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life history relationships
- r (rate of increase) is inversely related to generation time
- generation time is directly related to size, therefore r is inversely related to size
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life history patterns
- small size =
- higher metabolic rate
- faster growth
- higher r values
- short generation time
27
r/K selection theory
- r selected = grow fast but die sooner
- suggests trade-offs have taken place among growth and reproduction
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problem with r/K selection theory
- Many species possess traits of both r and K selected species
- E.g. sea turtles – live for many years, and yet produce massive numbers of eggs at a time, with limited parental care
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new focus on life history
A shift to age-specific life history theory, also referred to as demographic or optimality theory
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important life history parameters
- Age that reproduction begins
- Age that reproduction ends
- Age of maximum reproductive output
- Together, these determine the total reproductive output of an individual
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life history trade-offs
- age at first reproduction (earlier reproduction but lower adult survival)
- reproductive effort (higher quality offspring but lower adult survival)
- reproductive frequency (iteroparous vs semelparous breeding)
32
Iteroparous breeding
- common for K selected species
- species that breed more than once, investing significant energy in their offspring each time, such as through child-rearing
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Semelparous breeding
- common for r selected species
- breeding only once, generally producing many offspring in one event with a low energy invested in each individual offspring
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reproductive strategy when environment is unpredictable
selection favours adult survival over offspring survival and an iteroparous or bet-hedging strategy
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reproductive strategy when environmental is stable
offspring survival can be higher than adult survival and semelparity is favoured
36
how predation influences life history traits (guppys)
- Different predation regimes in stream led to a shift in offspring size and a change in reproduction allocation
- Proved a change in life history traits according to the costs and benefits of reproductive strategy
- Where predators prefer mature fish, guppies devote a high percentage of body weight to reproduction, have shorter inter-brood intervals and mature at a smaller size
37
reproductive senescence
- defines the upper limit of reproductive lifespan
- Grandmother theory – can look after your children’s children
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What life history factors protect against extinction risk?
- Large populations
- Short generation time
- Early age at first reproduction
- Fast growth
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sustainable harvesting more likely to succeed when life history includes:
- Rapid development
- Early AFR
- High fecundity
- Low body mass
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density independent growth
- population growing without constraint
- exponential growth
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density dependent growth
- The regulation of the size of a population by factors that are controlled by the size of the population
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allee effects
Any mechanism that can lead to a positive relationship between a component of individual fitness and either the numbers or densities of conspecifics
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example of allee effect
- Predator dilution
- Antipredator vigilance and predator defense
- Cooperative breeding
- Modification of the local environment
- Reduction in deleterious effects of inbreeding
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example of allee effect (species)
- wild dogs
- critical group size required to successfully hunt, raise young and defend resources from competition
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sustainable harvesting
Harvesting of a wild population that allows the population numbers to be maintained or increased over time
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reasons for sustainable harvesting
- Subsistence
- Direct consumption
- Use as feedstock for other food species
- For derived by-products like oils, etc.
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what happens if we don't sustainably harvest?
- Population collapse
- Can lead to ecological collapse and economic collapse
- Examples: Orange Roughy; Newfoundland Cod
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newfound cod (unsustainable harvest)
- stock collpase in early 1990s
- no reasonable quota set
- technology improved and so did harvest rate
- example of the tragedy of the commons
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how to harvest sustainably
- harvest at the rate at which population is growing most quickly
- Most wild population have an r of 0 > so before harvest can occur, a population must be stimulated to increase
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problems with maximum sustainable yield
- for MSY to be sustainable, very accurate population data is required
- if MSY is exceeded, the population will shrink
- assumes individuals are identical
- growth rate is limited by environment - may change every year
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calculating a sustainable harvest
Modify normal logistic growth model to calculate population growth under harvesting (should also include environmental stochasticity)
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information needed to calculate a sustainable harvest
- Population size
- Age structure
- Fecundity
- Recruitment rates
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types of harvests
- constant (harvesting quota set to an absolute number)
- proportional (H varies with N)
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economics vs biology in harvesting
- Economics emphasizes maximizing profit, whereas biologists work to maximize resource persistence
- “Future discounting” is the higher value of resources used now than being saved for the future
- The best biological strategy for the best economic strategy only coincide when the populations r max exceeds the discounting rate
- When r max is lower than the discounting rate, it remains most profitable to over-harvest
- This is a particular problem for shared resources = tragedy of the commons
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PVA
- Essentially a quantitative risk assessment for the future that is species-specific
- Estimates the likelihood of population extinction
- Estimates the MVP size for a population to be self-sustainable
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what does PVA attempt to answer
- how large must a population be to have a reasonable chance of survival for a reasonably long period of time?
- Reasonable chance = 95%
- Reasonably long period of time = 100 years
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quasi-extinction
populations cease being ecologically functional well before they became extinct
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stochastic events that affect population parameters
- extrinsic (environmental)
- intrinsic (demographic)
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what is a meta-population
- population of populations
- immigration and emigration rates between populations are important
- These differences make their dynamics different from closed, single populations
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meta-population ecology
- Migration rates influence populations dynamics
- Connectivity between populations is key and extinction of local populations may be commonplace
- Single populations are less stables than meta-populations
- Connectivity between populations allows movement between areas, making meta-populations less vulnerable to stochastic events
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why is meta-population ecology a useful concept?
Many population models assume that natural populations are widespread and continuous – this is not correct
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why is meta-population ecology important?
- populations are much more fragmented in today's world
- critical population sizes, intensive intervention and management
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meta-population types
- classical/levins
- mainland-island
- non-equilibrium rate
- patchy
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classical/levins meta-population type
- Assumes equal size and quality of patches
- An early and simple method for occupancy of habitat
- “Patches” are considered either occupied or unoccupied
- Interaction among individuals within patches is assumed to be considerably higher than between patches
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mainland-island meta-population type
assumes a constant source of species (mainland)
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non-equilibrium rate meta-population type
rate of extinction exceeds colonization (without intervention > extinction)
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patchy meta-population type
mobility between populations so high that act as a single population
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The MacArther and Wilson equilibrium theory
- There is a relationship between area and species number
- Species number is based on the ratio of colonization and extinction
- Size and distance of habitat from other sources of species will affect immigration rate
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source-sink dynamics
- Habitat patches are likely to be of different quality
- Some patches would go extinct without immigration from source areas
- Different from mainland and levin models in that differences in habitat quality are recognised as key in regulating population numbers
70
incidence function model
- Combines mainland-island, classical and source-sink meta-population assumptions
- Developed to create a more realistic set of measures that could be applied to real populations
- Predicts patch occupancy as a function of the spatial structure of the entire meta-population (the location and size of other patches)
- Identifies long-distance dispersal events are important, and animals move with different ease through the landscape
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what does incidence function model assume
- Assumes: finite number of patches, patches of different size, interactions amoung patches are localized in space
- Assumes: extinction probability depends on population size, which is a function of patch areas
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Meta-populations and genetic diversity
- Smaller patch size and decreasing connectivity results in lower genetic diversity
- Lower connectivity leads to increase in inbreeding
- Leads to increase in susceptibility to disease, infertility
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competition
An interaction between two (or more) individuals, due to both requiring a shared resource in limited supply, that leads to a reduction in the survival, growth, condition and/or reproduction of all competing individuals
74
intraspecific competition
- Limits population growth by energy being diverted to competing
- Causes adaptation for sexual differentiation through competition for mates
75
types of intraspecific competition
- Interference – a limited resource can be completely monopolized
- Scramble – a limited resource that all individuals can access
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costs of competition
- Why does the winner of competition still incur a cost?
- Because competing costs energy
- Even without injury, time and energy is used when that could have been used to forage, mate, reproduce, nest, etc.
- Time allocation
77
inter-specific competition
- Limits population growth
- Leads to adaptations that enable niche differentiation
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niche differentiation
Complete competition cannot coexist indefinitely, but niche differentiation does allow species to coexist when using similar (but not identical) resources
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fundamental vs realised niche
- A fundamental niche depends on physical, abiotic conditions
- The realised niche depends on biotic as well as abiotic conditions
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how to determine if a species is being outcompeted? IMPORTANT
- Competitive release – niche of the competitively-inferior species expands in the absence of the competitively-superior species
81
lotka-volterra competition model
- Very useful to determine if one species will drive the other to extinction and the effect that one species will have on another
- Uses the single species framework and converts the density of the other (competing) species into an equivalent number of the focal species
82
predation
True predation is the direct killing and consumption of one thing (generally an animal) by another
83
numerical response
the extent to which predator abundance changes according to variation to food supply
84
functional response
the extent to which per capita kill rate fluctuates according to prey density
85
functional + numerical response
total response, or overall predation rate
86
Lotka-Volterra model
assumes:
- In the absence of predators, prey population grows logistically or exponentially
- Population growth of predators is entirely regulated by prey
- Environment does not change to favour one species over the other
- Predation rate is related to encounter rate (i.e. it’s density dependent)
- All individuals are identical (both population)
87
prey population growth
The growth of a prey population will be its intrinsic growth rate minus the rate at which individuals are removed by predators
88
predator population growth
The growth of a predator population will be its intrinsic growth rate minus its mortality rate limited by the encounter probability with prey and efficiency at converting them to predators
89
graphing predator-prey relationships
- When the predator population’s rate of increase is positive, prey density declines
- Equally, when the rate of increase in prey is negative, predator populations decline
- the combination of the two processes overlapping leads to a cycling of the rates
90
Why is defining functional response important?
- Because it reflects the stability of predator-prey interactions
- If prey are at greater risk when prey density is high, predation will have a stabilizing effect
- If prey are at greater risk when prey density is low, predation will have a destabilizing effect
91
four factors that affect predation rate
search, capture, handling, digestion
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type 1 response
A linear relationship between prey density and their consumption by predators
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causes of type 1 response
- Search time limits predation
- If prey are scattered in the environment, and they cannot hide, type 1 response is the most common functional response
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example of animals that use type 1 response
Filter feeders, grazers, specialists
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type 2 response
An initial non-linear increase in consumption with prey density, followed by deceleration to a plateau as handling time begins to affect consumption rate more than searching time
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causes of type 2 response
- Predator handling time of captured prey is the limiting factor, rather than search time
- If prey are easy to catch, but take time to consume, this leads to a type 2 response
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example of animals that use type 2 response
invertebrate predators, some mammals (leopard)
98
type 3 response
- Prey consumption rates are low until a critical density is reached where rate increases
- Consumption rate then increases rapidly before reaching a plateau
- Characteristic of prey-switching interactions
99
expected situations where type 3 response is used
- Where predators need time to learn to capture a new prey type efficiently
- Where prey has a refuge, so at low densities the ability to capture them is reduced
- Where the predator has multiple prey species, leading to the economics of profitability
100
Why do we care about functional response curves?
It could affect our management decision, e.g. biological control of agricultural pests ( would not choose type 3 response as it may have limited effect on pest)
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Applications for functional response type
- Cane toads are from Venezuela, were introduced to control beetle pests of sugarcane plantations
- They are very effective prey switchers and their population and range is expanding rapidly
- Native water rats in the Kimberley eat them but die from eating them
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Stable age distribution
mortality and fecundity have been stable for some time
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reproductive value
current and future contribution of offspring to the population of females at any given age
