Final Review (Weeks 9-15)

Climate change

Long-term shifts in temperatures and weather patterns

Evidence that we have to support climate change

Temperature, greenhouse gases, biological and physical changes on earth

What impacts will climate change have on wildlife?

• Habitat fragmentation, degradation and loss

• Migration disruptions

• Food web disruption

• Range shifts

• Phenology changes

• Sex ratio bias

• Human-wildlife conflicts

How can animals survive climate changes?

Colonization or adapt to new environment

How do we manage wildlife for climate change?

• Establish refugia or safe havens

• Optimizing migration pathways

• Build evolutionary resilience

• Use biodiversity for climate mitigation

• Develop green infrastructure

Why do we harvest wildlife?

• Commercial activity

• Sustenance

• Recreation

• Management

Sustainable harvest

• Population is at self-sustaining level prior to harvesting

• # of individuals removed less than or equal to # of recruitments

Maximum sustainable yield (MSY)

• Highest # of individuals that can be harvested w/o population collapsing and going into extinction

  • Risky, can lead to unstable population and extinction

Which part of the equation represents the number of individuals being added to the

population?

Logistic growth equation

Fixed Harvest Quota

a set number of animals is removed annually, regardless of population changes, aiming for sustainable yield but carrying high risk of overharvesting and collapse if the population declines

• recruitment > harvest= pop. increase

• recruitment < harvest= pop. decrease

• recruitment = harvest= stable

For now, let’s say 0 individuals are being harvested (H=0). What is recruitment (ΔN) if K=100, R=1.0 and Nt=70, rounded to the nearest integer?

21

If K=100, R=1.0 and N=70, what will happen to the population at the next time step if H=30?

Decreases

If K=100, R=1.0 and N=70, what will happen to the population at the next time step if H=15?

Increases

4

B.) 25

If K=200 and R=0.5, what is maximum sustainable yield?

25

Fixed proportion

“Traditional” Management

• Personal experience and traditions

• Untested, no formal process

• Conservatism, a lack of interest in trying new ideas

• Often provides a starting point for experiments

“Experimental” Management

• Driven by data and analysis

• Tests ideas, new and old

  • Test and refine, cont.

● Outcome-based objectives

● Most objective

Technical judgement

• Testable idea that can be evaluated according to a strict criteria

- Fact-based assessments

-”how many”

Value judgement

Based on ethics and beliefs

• “Should”

Hypothesis

A proposed explanation for a phenomenon or observation

Null hypothesis (H0)

A statement that the phenomenon or relationship being tested has no effect, no difference or no association

Alternate hypothesis (Ha)

A statement that proposes a significant effect or difference exists between populations

Steps of scientific process

1. Observation

2. Question

3. Hypothesis

4. Prediction

5. Test

6. Results

7. Refine or propose new hypothesis

We have observed that Rocky Mountain elk population sizes have

been declining for years. Through aerial photos, we notice their

habitat is becoming more and more fragmented.

What would be your null hypothesis?

The degree of habitat fragmentation has no significant effect on the

elk population size

We have observed that Rocky Mountain elk population sizes have

been declining for years. Through aerial photos, we notice their

habitat is becoming more and more fragmented. What would be your alternative hypothesis?

The degree of habitat fragmentation has a significant effect on elk

population size

6 Steps of testing hypothesis

1. Pose a research question

2. Convert it to a null hypothesis

3. Collect data that will test the null hypothesis

4. Run the appropriate statistical test

5. Accept or reject the null hypothesis in light of that testing

6. Convert statistical conclusion to a biological conclusion

4 components that make a good experiment

• Generalizable - findings can be applied more broadly than the experiment itself

• Verifiable - the design and methods can be demonstrated to contain no major flaw

• Validatable - results consistent with data not used in the experiment

• Replicable - experiment can be repeated and results would be the same (or at least similar)

Predictor variable

• Aka independent variable

  ○ Variables expected to affect the response variable

  ○ “cause”

Response variable

• Aka dependent variable

○ Variables that will be affected by the predictor variable

○ “effect”

Factor

Factors are typically a general type or category of treatment

Levels

Represent the number of variation of the factor

What is the factor and level?: How effective is tree removal at promoting movement of pronghorn? We tested 0%, 50% and 100% removal of trees

Factor: tree removal

Levels: 3 → 0%, 50% and 100%

Fixed factor

Typically if investigator controls the level of the factor, then the factor is fixed

Random factor

If the investigator randomly sampled the levels of a factor from the population then the factor is random

Fixed or random: How effective is tree removal at promoting movement of

pronghorn? We tested 0%, 50% and 100% removal of trees

Fixed

Fixed or random: We measured the movement of the first 10 individuals we found

(out of the 100 that exist in this population).

Random

3 Common mistakes in experimental design

• Pseudoreplication- non-independent observation treated independently

• Unbalanced design- treatments are not equal in come capacity

• Small sample size (low statistical power)

Statistical power

Probability that a test can correctly detect a true effect when one exists

Extinction

A species ceases to exist

Global extinction (total extinction)

a species once existed, but no longer exists anywhere on Earth

Local extinction (extirpation)

a species ceases to exist within a specific geographic area, but still exist elsewhere

Extinct in the wild

a species ceases to exist in its natural habitat but living individuals remain in captivity (typically in a zoo)

Mass extinction

Widespread species extinctions within a relatively short period

of time

○ Leads to rapid decrease in the biodiversity on Earth

○ Typically ~ 70-75% of all species are lost during these

events

Demographic Stochasticity

= random variation in birth, death and reproductive rates

An individual has a certain probability of…

- Surviving

- Breeding

- Dispersing

“Normal” Environmental Stochasticity

= variation in population growth due to the environmental fluctuations

e.g., Kangaroos = grazers in arid Australia

“Extreme” Environmental Stochasticity

Catastrophes

○ Volcanic eruptions

○ Hurricanes

○ Large wildfires

○ Severe drought

Population Viability Analysis (PVA)

Estimates the probability of persistence (or extinction) over a specified time interval

Components of a PVA

1. Population model

   2. Demographic variation

   3. Temporal variation

   4. Spatial variation

   5. Individual variation

   6. Genetic variation

   7. System stability

Variation

concept of how spread out data points are

Variance

a statistical measure that quantifies the spread of the data

Challenges with PVA

1. Lack of data to account for variation

a.. Ex. insufficient genetic data

b. Ex. poor spatial coverage of data

2. Model is too simplistic

a. Ex. model is static but often the real world is dynamic

3. High uncertainty over time

a. Ex. 100 years may be acceptable to look at but modeling

beyond that is very uncertain

Model

hypothesis that is usually expressed mathematically

Adaptive Management

Learning while doing (update management goals and plans as new information becomes available)

• “Decision process that promotes flexible decision making that can be adjusted in the face of uncertainties as outcomes from management actions and other events become better understood.”

Passive Adaptive Management

• Make the best possible use

of historical data to

determine the best practice

•Continue monitoring and

collecting new data

Active Adaptive Management

• Conduct manipulative

experiments to improve our

understanding of the

managed system

• Test different management

strategies and identify

which one is best

Evolution

-Genetic adaptation of organisms to their environments

- Change in the properties of groups of organisms over the

course of generations

- Descent with inherited modification

4 Steps Required for Evolutionary Change

1)Variation

2) Heritability

3) Competition

4) Adaptation

Four mechanisms of evolution

1.Mutation

2. Genetic Drift

3. Gene flow (migration)

4. Natural selection

Fitness

The genetic contribution by an individual’s descendants to future generations of a population relative to those of other individuals

Sources of Variation

Hardy Weinberg Equation- What is p? What is q?

p= proportion of A allele (dominant) q= proportion of a allele (recessive)

Hardy-Weinberg Equilibrium Assumptions

No mutations (i.e. no new alleles)

No gene flow can occur (i.e. no migration)

Random mating must occur (i.e. individuals must pair by chance)

No genetic drift occurs

No selection can occur

Natural selection

process by which random evolutionary changes are selected for

by nature in a consistent, orderly, non-random way

Artificial selection

an evolutionary process in which humans are consciously selecting for or against a particular trait

Kin selection

selection in favor of behavior by individuals that may decrease their chance of survival but increases that of their kin (who share a proportion of their genes)

Sexual selection

selection arising through preference by one sex for certain characteristics in individuals of the other sex

Three modes of selection

Adaptation

Trait or characteristic that improves an organism's ability to survive and reproduce (fitness)

Forms of Adaptations

Behavioral

- Structural

- Physiological

- Molecular

Rapid Evolution

the process of significant genetic change in a population over a relatively short timescale (sometimes a couple generations)

How to promote genetic diversity

1. Gene flow

a. Build corridors between

populations

b. Translocations

c. Captive breeding programs

2. Increase population numbers

a. Effective population size

i. Actual number of

individuals that are

reproducing and

capable of adding to the

gene pool

Productivity

percentage of energy entering the ecosystem that becomes incorporated into

biomass at that trophic level

Following the 10% rule, if our primary producers store 10,500 kcal/m 2/year, how much of that energy will be transferred to the secondary consumer?

105

Why is energy lost between trophic levels?

Second Law of

Thermodynamics:

- During transfer of energy,

some energy is always lost

as heat

Bottom up control

Community structure and function is primarily controlled by productivity

and abundance of primary producers

Top down control:

Community structure and function is primarily controlled by productivity and abundance of predators (secondary or above typically)

What type of environmental changes could shift a system

from bottom-up to top-down or vice versa?

Trophic Cascades

- Removal of top predator triggers

a chain reaction that affects

lower trophic levels

- Bottom-up trophic cascades

- Changes to abundance and

structure of primary

producers influences higher

trophic levels.

Bioaccumulation

Increasing concentration of persistent, toxic substances in organisms at each trophic level

Macroecology

Explores the domain where ecology, biogeography, paleobiology, evolution and community ecology come together

Three hypotheses for explaining why there is higher biodiversity at the equator than the poles

1. Species - energy hypothesis

2. Time and stability

hypothesis

3. Area hypothesis

Bergmann's Rule

Species size increases in the cooler portions of their geographic range

Cope’s Rule

Lineages tend to increase size over geological time periods

The Island Rule

Gigantism: tendency of small species

to evolve towards larger size in islands

Dwarfism: tendency of larger species

to evolve towards smaller size in

islands

Drive extinctions

-Environmental fluctuations

- Catastrophes

Stochastic extinctions

Demographic malfunction

- Small population size

leading to issues

- Genetic malfunction

- Loss of heterozygosity

Conservation Biology

Scientific discipline that draws on diverse fields to carry out research on biodiversity, identify threats to biodiversity, and play an active role in the preservation of biodiversity

Biodiversity

The variety of living organisms considered at all levels of organization, including the

genetic, populations/species, and higher taxonomic levels; and the variety of habitats, ecosystems, and landscapes as well as the processes occurring within

Why is biodiversity important?

1. Intrinsic value

2. Ecosystem function

3. Ecosystem services

S.L.O.S.S. Debate (single large and several small - connected)

Single Large:

1. Species with large ranges

(home and geographic)

2. Species with variable habitat

needs

3. Animals sensitive to edge

effects

4. Animals with inbreeding

Several Small:

1. Species with narrow ranges

and niches (specialists)

2. Species with high disease

transmission (catastrophes)

3. Animals that do well in edge

habitats

4. Smaller organisms

Community

a group of populations of two or more different species in a specific space and/or time

Keystone species

species that have a disproportionately large impact on the ecosystem relative to its abundance

Ecosystem engineers

species that significantly modifies the landscape that other organisms rely on

Ecosystem

Communities exist within a set of abiotic and biotic conditions and these combinations

Landscape ecology

studies how the arrangement (spatial patterns) of habitats, land uses, and ecosystems (the landscape) affects animal movements, populations, biodiversity, and overall ecological processes

Potential Management Strategies

If we have a population with the following parameters, what is our

maximum sustainable yield?

K = 300

R = 0.5

N = 200

37.5