Turtles and Population models

•The loggerhead turtle (Carettacaretta): Very high egg loss due to beaches being developed, eggs poached, Also very high early juvenile loss due to predation –as they disperse into the ocean
•Turtle conservation in the 1980s focused on protecting eggs and beaches

•1987 Crouse et al. -programs focusing on preserving turtle eggs will be un-effective; late juvenile/ early adult survival is more important (learned by conducting life tables) (by doing life tables they learned that morsality in young is very high, species plans for this by producing a lof of young; what wasn't natural was death of adults (due to fishing nets)
•Often caught in fish nets –huge source of mortality
•Create TEDs (tutrle excluder device) to prevent turtles and other large by-catch species drowning
•1997 Grand and Beissinger –we must protect eggs on beaches AND use TEDs

-effective since divided up mortaity to different age grous and looked where conservation efforts would have the greatest impact

How can you split a population up

1. sex

2. age

3. size: meant more for plants (for ex, large plants produce more seeds than small plants)

-birth death and movements rates vary by sex, age and size

Structured Data

Life Tables (different ways of sampling)

Notation

x= age of the individual
nx= number of individuals of age x
lx= number (or %) of individuals alive at age x: lx= Nx/N0

(ex: probabiity of making it from age 0 to age 11-probability

of surving to a certain age)
mx= fecundity rate
average # of female offspring produced per female per time period
px= survival rate:the probability of surviving from x to x+1 (ex. porbability

of surviving from age 10 to 11; it can icrease)
                      px= Nx+1/Nx
qx= mortality rate:probability of dying between age xand x+1

Fecundity table

Net Reproductive Number

R0: the mean number of female offspring produced by a female during her lifetime.
     R0< 1population is declining
     R0> 1 increasing population
     R0= 1indicates a stationary population
If lx is a proportion:

R0=Σ lx*mx

this is the number of individuals alive at a given age * how many young each female produces

Node Arc Notation

3 ages or stages

small bird reproduces in its second year

-if you cant tell exact ages of a species you can create stages that you can recognize

Why are life tables useful?

Grizzly Bear example

Definitions:

1.biogeography

2. zoogeography

3. phytogeography

4. richness

5. abundance

[image]

[image][image]Biogeography-study of the distribution patterns of living organisms
Zoogeography-study of animal distribution (and richness) patterns
Phytogeography-study of plant distribution patterns
Richness= total number of species
Abundance= number of individuals

richness+abundance=diversity

Questions zoogeographers ask

General Patterns of distribution

1) Most species occur on only one continent
2) Distribution differs across taxonomic groups (each group of animals has its own pattern of distribution)
3) Matches between patterns of species occurrence and geographical barriers suggest the world can be divided into Zoogeographic realms (looking at where species occur (species occurance) and where barriers are allows you to draw a zoogeographic map

-barriers tend to be oceans, sahara desert

Zoogeographic realms

Terminology to describe species ranges

European Stalring

Factors affecting distribution of a species

1. History: Many of the animal distributions we see today can be explained by movements of land masses over geological time; There used to be two big land masses (Gondwanaland has south america and Laurasia has north america). marsupials evolved on gondwanaland so how are they in north america?. This is because of the little peice of land that now connects the two.

2. Isoloation: Many of the animal distributions we see today can be explained by connectivity or isolation of land masses over geological time. Species on an island chain are generally seperated and so they evolve into new species.

- ex Wallace's line

Alfred Russel Wallace

First scientist to relate species range to geographic features
Co-founder of theory of evolution
Discovered Wallace’s Line: most dramatic change in species composition of any realm boundary
     -West of line: Asian fauna and flora
     -East of line: Australian fauna and flora

This barrier that caused this change was a deep gulch along his line; kept animals apart and they eolved seperately, now ou are beginning to see them together

Factors affectng distribution cont.

1. dispersal (ability to reach new areas): Taxonomic differences in dispersal: some animals will be spread more widely because of their vagility
                    birds>mammals>reptiles>amphibians

Barriers affect dispersal including:

     a.  Physical barriers (e.g., extreme cold or heat, limited nesting/breeding sites, water limitation)

     b. Biological barriers (e.g., competitors, predators, disease, hunting)

-ex wolves and coyotes: wolves are coming into US and pushing coyotes back

Global patterns of species richness

Global Extinction

Where does extinction occur the most?

Defintions:

1. population

2. abundance

3. density

4. census

5. survey

Wildlife Count Issues

Counting Techniques

1. Direct (count actual animal): you can either do a census or a survey.

Aerialfixed wing/helicopter Expensive: ~$5000/day
Ground: drives, transects
lots of people/time
Live trapping
(catch per unit effort)
Mark-recapture
Camera trapping

2. Indirect (index)

Tracks/droppings
Camera trapping (take a picture and then go through and coutn afterwards)
Call stations (Record wildlife)

Sampling Techniques

1. Quadrats:

-Calculate avg. number of individuals per quadrat, divide by quadrat size to calculate density
-Multiply density by the area to get a population size

equation:

2. Circular Plots: Often used for bird counts. Stand at the center, count all within a certain radius

3. Strip Transects: Walk a line, count everything within a certain width.

4. Distance Transects: Walking, driving, bikes, horses, etc.Airplane, helicopter, ultra lights; record number and how far away from you they are

Assumptions of transect sampling methods

Aerial Studies

The Good
•survey huge areas
•low cost per km
•little training besides pilot
•repeatable
The Bad
Detectability varies by
•habitatn(denser habitats have lower detection)
•time of day (animal behavior & lighting)
•observer
•height, speed
•species
The Ugly: get sick

-large groups are easier to spot but harder to count

Detectibility (ways to control for errors in detectibility)

Detectibility and counting on either side of you

Mark Recapture Sampling

Used with fish, amphibians, small and large mammals, birds
Does not require any actual capture, could be done by re-sighting known individuals.
Assumptions:
•no emigration/immigration/birth/death, if there is mortality, then equal survival of marked and unmarked, no loss of markers, equal detectability of marked and unmarked, random mixing of marked individuals, marked individuals are a representative sample of the population, all individuals are independent of one another

-you can mark with: branding, PIT tag, string tags

Brief Review of Population Models

1. Unlimited resources:Exponential growth model

2. Finite carrying capacity:Logistic growth model

3. Life table analysis:Age-structured models

-these are all closed population models: viewed as a single population where immigration and emigration isn't included; population changes in these modles are driven by birth and death

Limitations of Old Models and Closed Population Models/Observations Point Out that we aren't closed: # 1

1. Ehrich looked at populations of checkerspot butterflies and how they changed over time. He noticed that popultations go extinct but then are reastablished; in closed model, once population goes extinct it can't come back

Limitations of Old Models and Closed Population Models/Observations Point Out that we aren't closed: # 2

2. Huffaker's Experiment: Looked a mites that ate orange. He set up oranges in different arrangements and then looked at pop dynamis 

a. Well-connected habitats: mites could easily move beyween oranges:, Concentrated resources, No subdivisions

-result: Unstable populations:  Predator (and sometimes prey) driven to extinction: at first prey greatly increase and then predator increase as a result. Prey crashes since predator found them all and predator crashes since no more prey

Limitations of Old Models and Closed Population Models/Observations Point Out that we aren't closed: # 2b

2b. Spatially subdivided habitats: created oranges in patches and put posts in betweeen them. Prey can move in between them; Same amount of resources but different dynamics
-Dispersed resources
-Subdivisions (barriers)
-Wooden posts that increased prey dispersal capability

-result: Spatial heterogeneity allowed for coexistence of predator and prey populations; population oscialates but is stable. By the time the predator caught up with the prey, the prey would go to a new location

-closed population models do not incorporate spatial subdivisions

Limitations of Old Models and Closed Population Models/Observations Point Out that we aren't closed: # 3

3. observe that some populations have more deaths than births. This means their population should go extinct but it doesn't

-The long-term persistence of some local populations depends on immigration
-Closed population models inadequate for describing maintenance of sinks

Limitations of Old Models and Closed Population Models/Observations Point Out that we aren't closed: # 4

4.Closed population models donot reflect the increasingly fragmented nature of Earth’s habitats

-before we had large habitats so closed models would be okay. However, now we have a whole bunch of fragmentation

Sink Population

• Low reproductive success and high mortality (births < deaths)
• Population receives immigrants from other populations (immigration > emigration)
• Population would face extinction in the absence of dispersal
• Often in the periphery of a species’ range in areas of poor habitat quality

-sink populations are usually found in the outside of a species range which tends to have poorer quality

Source Population

Summary of limitations of
closed population models

Metapopulation

-META comes from the Greek word μετά (metá) meanin “beyond” or “after”

• Metapopulation = a population of populations, coined by Levins (1970)

ASSUMPTIONS:

• Local breeding populations in relatively discrete habitat patches surrounded by an unsuitable matrix

     -matrix: area where individual can pass through but can't live on; get patches of good land surrounded by bad
• Limited dispersal necessary for recolonization: if get a lot of dispersal it looks like one large pop.
• Dynamics of local populations are asynchronous (independent): if 1 pop is doing bad doesnt mean all are: local factors affecting each pop

Types of Metapopulation Models: 1

1 linked closed-population models

-Models anundance (N) of all local populations
-Local populations have density-dependent growth
-Complex and data-intensive: must estimate b, d, i, e
for each local population

Types of Metapopulation Models: 2

(2) Spatially implicit (all patches same size, shape etc) patch occupancy models

• Models proportion of occupied patches (P) (also called occupancy)
• Assumes infinite # of equally connected patches
• Simple and not data-intensive
• Example: Levin’s model

- look at how patch occupancy changes

individual based models vs patch occupancy models

Levin's Patch Occupancy Model

• Variation on the logistic model
• Proportion of occupied patches (P) is modeled over time as
a function of colonization and extinction rates
-P/dt = cP(1 - P)- eP
-c = probability of colonizationd
-e = probability of extinction

-cp(1-p): colonization rate; in order for a patch to colonize another patch it depends on how many patches started with

-if start with high P, have more potential to colonize (thus c is proportional to P); also need there to be empty patches if you re going to colonize thus c is proportional to 1-P

-ep: extinction rate
Change in patches occupied over time
Colonization rate Extinction rate
• Assumes no variation in patch size or quality
• Assumes all patches are equally connected

Levin's Model (graph)

Types of Metapopulations Models: # 3

(3) Spatially realistic patch occupancy models

•Models proportion of occupied patches (P)
•Incorporates spatial structure of a finite patch network
•Moderately data-intensive
•Example: Incidence function model (IFM), Hanski

Hanski’s incidence Glanville Fritillary
function model (IFM)

-Patch colonization probability is positively related to CONNECTIVITY: more likely to get colonists the closer patches are to one another

-Patch extinction probability is negatively related to AREA: bigger patches have more indifiduals and are harder to dirve to extinction

Hank's IFM cont

• Calculate area and connectivity for all patches
• Set initial occupancy
• Calculate colonization and extinction probabilities (based on size and connectivity)
• Assign stochastic colonizations and extinctions to
patches (using a random number generator)
• Re-calculate connectivity
• Simulate again…

-Persistence = probability that the metapopulation persists (does not go extinct) over a given time scale

Extinction Deffinitions

Local extinction: Extinction of an individual patch (local population)

Regional extinction: Extinction the entire metapopulation (all local populations)

-As the number of local populations is increased, the probability of regional extinctions goes up rapidly

-Having multiple patches “spreads the risk” of extinction. BUT:  this assumes that
populations fluctuate independently!

-x = number of local populations

-the more patches, the more likely population will persist

-important from a conservation perspective that u dont lose patches

Real-world metapopulation:
American Pika

• ‘Colonization potential’ – expected contribution a patch makes in colonizing other patches
• Large well connected well-patches have high colonization potential

-Relatively few key patches may be responsible for the persistence of the metapopulation

-After removal ofthe 4 patches with the highest colonization potential population went to extinction

-shows some sites play a key role in maintaining the system

Another real-world example: California Black Rails

-they live in patches that are surrounded by an unsuitable matrix

-population fluctuated and then in 2006 it crashed (extinction rate increased)

-what factors caused local extinctions and colonizations(hypothesis): west nile virus, weather, irrigation water management, grazing, habitat quality, competitors

-Results: Area and isolation appear to drive extinction & colonization rates 2002-06

     •Extinction prob. decreases as sites became larger
     •Colonization prob. decreases as sites became more isolated (less    connected)

     •Extinction prob. increases as sites became more isolated

The Rescue Affect

Another metapopulation: meadow vole (Krebs 1969)

• Fence constructed around wild vole population
• “Fence effect”: vole population increased rapidly and then crashed
• Likely cause: voles no longer able to disperse and area becomes overpopulated

-it was most likely a souce population where it depleted resources and then crashed

-if didn't fence the population stayed relatively low

Trophic Interactions and trophic web

trophic interactions: movement of energy across animals at different levels of the food chain

Trophic web: depiction of trophic interactions in a community

-allows you to think about the implications of removing one of the animals

Trophic Structures in Communities

- for every 1000kg of vegetation, there's about 100 kg of primary provider etc: given rise to the rule of ten

-Rule of thumb: only about 10% of the energy is transferred from one trophic level to the next: Most ecosystems have 3-4 trophic levels, rarely 5

-thus for every large predator there will be 10% biomass of small producers

Species Interactions

Patterns of Abundance in Communities

Spatial Distribution of Communities: Biomes

Competition

deffinition: the use or defense of a resource by one individual that reduces availability of that resource to others

-Interspecific competition: competition between species (a community-level process)

-Intraspecific competition: competition within species (a population-level process)

*Resource distribution, timing and abundance determines level of competition*

-competition is important where resources are limited

Niche overlap is greater between individuals than species
Result: intraspecific competition > interspecific

-intraspecific competition is more powerful than interspecific competition since animals within a species have the same tools

-Intraspecific competition drives divergence within populations: competition makes it advantageous to select prey for which theire is less competition

How to minimize Intraspecific competition

1) Sexual dimorphism
*males and females have different morphology (size, shape, body parts, etc.)
*males and females use different resources different resources which decreases competition

-ex. cooper's hawk: female is much larger than male, thus it eats
2) Distinct size and age classes
*larger size takes larger prey
*different needs at different stages

-individuals within a population don't keep seperating due to interspecific comp

Example of Intraspecific Competition

Finches: good example of how intraspecific competition can push individuals so far that they become seperate species

-no 2 species can occur in the same niche at the same time because one will be a better competitor and will outcomepete the other

--can indentify the size of seed they eat by the size of their beak: smaller beak eats smaller seeds: this is how the same three species can co-occur since they are in different niches

Fundamental and Realized Niche and their relationship to competition

-Fundamental niche-entire spectrum of conditions in which a species can survive and reproduce

-Realized niche-the set of conditions actually used by a species due to competition with other species: this is where see species after they adjusted to competition

Competition and niche shifts:carnivore example

Competitive exclusion principal (Gause)

Example of resource partitioning in nature

example: north american ungulates

-Niche differences between 4 ungulate species inhabiting North American prairie
habitat.
-Little overlap exists between the species due to diet and spatial partitioning

-even though these ungulates have similar digestive systems and skills, they segregate their food type and habitat type to decrease competition

 3 results of resource paritioning

Modes of Competition: #1

Modes Of Competition: #2

2. Interference/Contest: individuals actively interfere with one another’s access to resources, monopolization (few r-selected, mostly K-selected)

*Territoriality
–division and exclusive occupation of space by an individual or group with a defended boundary
*Dominance hierarchies
–pecking order among individuals in a group that spatially overlaps: primates is an example where larger males eat first then the smaller ones. Acsess is limited by power

-both can be intra and interspecific

Lotka-Volterra competition model

-this is the logistics model but it takes into account competition

-Predicts the outcome of inter-specific competition between weak and strong competitors–the change in population sizes of the two species in the presence of each other

-N1:Number of species 1
-N2:Number of species 2
-a:proportional impact of species 2 on species 1
-b:proportional impact of species 1 on species 2

Predation: deffinitions and types of predation

What are the costs for a predaor for killing a particulr prey

-What is the cost of obtaining the prey item and what is the payoff?
-Costs:
1. Searching: time and energy required to find prey
2. Capturing: energy expense and risk of acquisition
3. Handling: time and energy of eating and digesting prey

-you expect the predator to always get the biggest prey, but in reality they don't since it isn't the most profitable

Example of Profitability of a given prey item (predator weighs the costs and the benefits (usually energy in a prey))

example: seaguls and clams

Seaguls choose the intermediate size clam shells. They break open the shells of the clams by flying and then dropping them. Large clams have to be flown higher to be dropped which costs more energy, however payoff from smaller shells isn’t worth the effort thus choose intermediate size prey

Prey choice: learning

-Predators can learn to become more efficient at locating, catching and handling prey

-Functional response: change in behavior of a an individual predator in response to prey availability (process by which anima learns to be more efficient)

I. as prey increase, individual predators eat them faster

II. predator increases its efficiency but eventually becomes full/saturated

III. a: pred. doesn’t yet recognize prey as food
b: pred. is learning to locate and catch prey (becoming more efficient)
c: pred. reaches maximum rate of prey consumption

Prey Choice: Availability

Prey choice: Prey defense

Regardless of their tastiness, some prey are not worth the trouble

-prey have their own defenses such as horns or they are toxic

-this leads to an evolutionary arms race

Prey Choice: Risk

-Prey are less attractive if they expose the predator to its own predators

-ex: skink movement with and without predators: In the sutdy there were two groups: 1 that were raises in captivity and didn't know predators (control) and those that were predator wise. They let them forage in forest or open areas. Control was constant, but predator wise skinks were seen to forage more in forested/safe areas than in open.

-Shows how prey respond to predators

Optimal Foraging Theory

2 theories of predation: Does predation just eat the excess animals (doesn't have much of an effect) or is it a force redulation populations (structures communities)?

1. Top Down Control: World is green/HSS Hypothesis: Herbivore abundance determined by predators rather than vegetation. As a result, herbivores do not regulate plants (which are regulated by nutrient supply); predators are why land looks green: carnivores limit the number of herbvores which then can't eat all the plants: Carnivore predation drives herbivore regulation

2. Bottom Up Control: everything is resource limited. Plants are limited by the sun, herbivores are limited by plants and carnivores are limited by herbivores.: Plant limitation drives herbivore and carnivore regulation

Experiment 1 to test bottom up/top down control

Experiment 2 to test bottom up/top down control

Predator/no-predator comparisons in nature:

1. water birds with and without skunks: very few hatchings of birds when skunks present. When no skunks where present many eggs were hatched

2. red kangaroos with and without dingos: kangaroos where very high in areas with no dingos and very low in areas where there where.

-both support top down

Experiment 3 to test bottom up/top down control: Bothbottom-up and top-down forces regulate populations in complex communities

-in 1 experiment they looked at large prey (ex girafee) and small prey (ex mouse) and saw the effects of predation on them. Found that the number of predators that fed on a given prey depended on that prey's size. The mouse has many predators that can eat it thus it is more influenced by the predators (top down); However the large prey has very few predators that can eat it and is not influenced by the predators but is controlled by the amount of food it has (thus bottom up)

-other experiment looked at prey numbers when predators where and where not absent. Found that # of large prey did not change in either situation but small prey increased when predators where gone and decrease when they were back

Predator an Prey Synchrony: nestng gulls example

-most young hatching within same time period

     -# predators increase when prey increase, however predator can't keep up with large increase in prey

-if you are born in the beginning or the end there will be a lot more predators than prey. If you are born when there is a lot of prey it is like predator swamping and thus less likely to die

Predator and Prey Synchrony: Cicadas Example

Predation and Grouping of Prey

-“Dilution effect”: for any one predator attack, the larger the group of prey animals, the smaller the chance that any particular individual will be the victim

-Safer in middle of group compared to edge
Nearer you are to others, more chance they are killed rather than you

     -way a group of fish stay together is that each individual is constantly trying to get in the center of the group

Predation and Vigilance

Many species put their heads down to feed
Grouping could bring double advantage:
     •Many eyes –predator detected sooner
     •Each individual does less vigilance –more time for feeding (when in a group each individual has more time to feed

     •Overall vigilance increases with group size

Why no Cheating

Trophic Cascade and Mesopredator Release Definition

•chain reaction of events caused by the removal of species at higher trophic levels that changes the dominance and impacts of species at lower levels

-Mesopredator release: predator at a middle trophic level increases in abundance following the loss of a top predator; it takes on a new role

Example of a Cascade

Killer whale -> sea otter-> sea urchin -> kelp forest

-humans killed sea otters. A decrease in salmon which the whales eat made them eat seat otters. This decrease in sea otters caused an increase in sea urchins and thus a decrease in the kelp forest

-shows a change in the top causes affects at the bottom

Baboob example of trophic cascase

large carnivores such as lions were hunted/poisened/isolated (land is fragmented and lions need large land; also they can't find mates). These large predators controlled the intermediate predators (baboons). One way they control them is through fear. If baboons live in areas with predators they forage close to escape areas. Thus with lions gone they will forest in many areas.

     -There is a huge increase in baboons population as large predators decrease

What are the consequences of baboon eruptions for biodiversity?

-they are now the top predator: loss of the top species leads to release of mesopredator: they increase in number as well as change their behavior which decrease their prey (this is in Africa)

-baboons also eat fruits of invasive trees, which spreads the trees. These trees are now all over. These trees are toxic to some insects so now there is a decrease in the insects

Cascading effects of mesopredatorrelease:

1)Baboon outbreaks are occurring across Africa
2)Loss of food and income from collapse of wildlife populations (baboons eat birds nests, antelope, small mammals etc humans eat baboons prey)
3)Baboons are Africa’s #1 mammalian crop pest
4)Baboons are Africa’s #1 predator of livestock

5)Baboons share water sources with humans

6)now live in closer proximity so more likely to tranfser disease: example hook worm causes anemia and malnutrition  (see more hook worm where there is more baboons

-since baboons are now a pest to humans children have to quit school and guard the livestock/crops

Keystone vs. Dominant species

-Keystone: a species whose impact on its community or ecosystem is large and disproportionate relative to its abundance (large impact but little of it)

-dominant species: there is a lot of them so they dominate an area

Ecosystem enigineers

-species that create, modify and maintain habitats

-ex beaver: they build dams which create ponds which changes hydrology of the area

-ex woodpeckers:beak and head can drill holes in trees/plants which creates nesting places for other animals

-ex hippos: they gather during dry season in water. They escalate pool with their feet which makes the pool deeper

-ex giant kangaroo rat: they dig holes underground: creates burrows for other species

Trophic Cascade Example: Flathead Lake in Montana

-most lakes have large amounts of interactions.

-Each ball represents a species. Differen shades means different tropic levels.

-What does number of links between species mean about the stability of the community

-stability: ability of community to respond to shocks (ex fire)

Diversity-Stability

Different models of diversity/stablity

-hypothesis

     -null: # species doesnt affect stability

-Rivet:each species adds to ecosystem function, although the rate of increase may slow as more species are added. Below a threshold ecosystems fail.
     -Redundancy:function increases as more species are present, up to a point. Then additional species are redundant.Each species adds a lttle bit of ecosystem function
     -Idiosyncratic:unpredictable due to the complex and varied roles of individual species.

-ecosystem function: service that a community could provide to us; how functional community is

Factors affecting distribution cont

2. Adaptive Radiation (enter an area where no other species is in the niche and rapidly evolve to fill up the niche; ex when finches came to Galapagos the rapidly evolved to fil up all the niches; based on colonization and evolutionary plasticity)

-what makes a sucessful colonist:

•Diet: generalists vs. specialists
•Habitat: generalists vs. specialists
•Presence/absence of predators and competitors

In the simplest sense, a newly arrived animal will be a successful colonist if:
r >0

Population index

Species interactions part 2

3 results of resource partitioning

3. Partitioning to fill empty niches and natural selection has given rise to common patterns in communities and convergent evolution

-ex convergent evolution: 3 speciesof birds have similar diets (neectar) so you would think they are closely related but they're not. They independently evolved a similar eating behavior (came up with the same solution to the same problem=the problem was the untapped resouce of nectar and all evolved the same skill to get it)