Modelling Approaches (Lec 7)

Front 1

PVA (population viability analysis)

Back 1

adaptive framework for incorporating mathematical and statistical models, risk assessment and uncertainty, extinction probability, and management options

Front 2

what is PVA used for?

Back 2

to put conservation science and modelling into practice

Front 3

Step one of PVA

Back 3

Objective

start with general question

(eg. what is the best way to protect the eastern ribbon snake in NS)

Front 4

Natural history (of eastern ribbon snake in NS)

Back 4

semi-aquatic

low movement rate

over-wintering

Front 5

Steph 2 of PVA

Back 5

model structure

Front 6

Model structure

Back 6

choose specific model after youve a good understanding of natural history, available data, and time frame of study

(eg. stochastic age structured demographic model)

make a list of model assumptions and keep it updated

Front 7

Step 3 of PVA

Back 7

Model parameters

Front 8

model parameters

Back 8

estimate model parameters from available data

(eg. mean and standard deviation of lambda)

Front 9

step 4 of PVA

Back 9

build/improve model

Front 10

build/improve model

Back 10

run the model many times under different scenarios

does it capture population dynamics reasonably well

does it need improvement

Front 11

step 5 of PVA

Back 11

extinction/ recovery

Front 12

extinction/recovery

Back 12

what is the probability of extinction over an appropriate time-scale

(eg. a 50% chance of extinction over the next 50 years with no management intervention)

Front 13

step 6 of PVA

Back 13

sensitivity analysis

Front 14

sensitivity analysis

Back 14

determine which parameters need to be estimated more carefully

(eg. model is very sensitive to juvenile mortality rate)

if possible acquire more data on the parameters

Front 15

if more data is collected on the parameters

Back 15

feedback to step 3

Front 16

step 7 of PVA

Back 16

ranking the options

Front 17

ranking the options

Back 17

use a cost-benefit analysis to fin the optimal management solution

(eg. a 20% chance of extinction costs $100 000 to implement, a %5 chance of extinction costs $1 million)

model and rank each possible scenario explicitly

Front 18

step 8 of PVA

Back 18

implementation

Front 19

implemenation

Back 19

present management options to stakeholders

(eg. government, NGOs, communities)

Front 20

Step 9 of PVA

Back 20

monitoring

Front 21

monitoring

Back 21

long-term monitoring of management success

(eg. annual surveys of snake populations in each county)

changes in range size?

short-term responses may be transient

Front 22

step 10 of PVA

Back 22

evaluation

Front 23

evaluation

Back 23

revision of model structure and parameter estimates if necessary

(eg. refine estimates of standard deviation of lambda)

as you adjust the model, your management plan may change - called adaptive management

Front 24

Example 1

Back 24

African elephants

Front 25

African elephant: a population viability analysis for African elephant: how big should reserves be

Back 25

extinction probability calculated by PVA for different sized reserves

helps in setting up effective reserves on semi-arid land

Front 26

Example 2

Back 26

Marsh fritillary butterfly

Front 27

Marsh fritillary butterfly

Back 27

minimum viable metapopulation size, extinction debt, and the conservation of a declining species

Front 28

Limits of PVA

Back 28

data quality

a model cannot identify reasons for decline- need to establish these independently

errors and uncertainties are magnified with each time step into the future

rare or unforseen events can change the populations trajectory

socio-economic factors are hard to predict, but often play a key role

Front 29

Summing up PVA

Back 29

PVA = adaptive management tool that incorporates population models, sensitivity analysis and management decisions

allows assessment of extinction risks over time

requires continuous monitoring, updating and re-evaluation

modelling populations is only one (important) step towards effective conservation

Front 30

Types of models

Back 30

conceptual

mathematical

statistical

Front 31

conceptual model

Back 31

a schematic or verbal description of a process

Front 32

mathematical model

Back 32

a formal mathematical representation of a process

Front 33

statistical model

Back 33

a mathematical description of a data set

Front 34

what do we do with conservation models

Back 34

observing general patterns

finding general laws

applying tools to specific problems

modelling population extinctions

harvesting of resources

coservation and resource management

Front 35

examples of conservation models

Back 35

individual based models

reserve-siting models (optimize resources)

metapopulation models

genetic bottleneck models

Front 36

decision making involves more than a good knowledge of species ecology

Back 36

interest groups: socio-economic demands

policy makers: political constraints

biologists: biological background

modellers: quantitative rigour

Front 37

3 golden rules

Back 37

always be clear about your question and objective

always be aware of assumptions and uncertainties and communicate them together with the results

do not allow yourself to get detached from the real world