Population Viability Analysis
Population Viability Analysis
Introduction
Over the last few lectures we’ve talked about the stochastic threats to persistence in small populations. We identified five classes of threats and some of their qualitative properties:
1. Genetic stochasticity — Not a problem in populations with Ne greater than a few hundred. Therefore, not likely to be a problem in populations large enough to buffer environmental stochasticity
2. Demographic stochasticity — Unlikely to be a problem in populations with more than
50–100 individuals
3. Environmental stochasticity — Likely to be a problem unless population sizes are on the order of 1000–10,000
4. Demographic heterogeneity — In the one case I am aware of where the magnitude of environmental stochasticity, demographic stochasticity, and demographic heterogeneity were compared, demographic heterogeneity contributed more to variability in population growth rate than either of the other two, suggesting that populations must be on the order of several thousand to buffer against this source of heterogeneity.
5. Natural catastrophes — No single populations can ever be large enough to buffer against natural catastrophes
These general guidelines are useful, but suppose you’re asked to design a recovery plan for the northern spotted owl.1 How do you go about determining
• How many breeding pairs are necessary to provide a reasonable chance of long-term survival? • What are the prospects for increasing the number of breeding pairs?
1
We’ll talk in some detail about the northern spotted owl next time.
c 2001–2013 Kent E. Holsinger
• What management manipulation will are most necessary to prevent extinction?
• What are the most critical stages of the life-cycle, i.e., have the largest impact on population dynamics?
Recall that the models we’ve discussed so far are based on very general assumptions.
To answer these questions for any specific species, perhaps even for any population, a demographic model
Introduction
Over the last few lectures we’ve talked about the stochastic threats to persistence in small populations. We identified five classes of threats and some of their qualitative properties:
1. Genetic stochasticity — Not a problem in populations with Ne greater than a few hundred. Therefore, not likely to be a problem in populations large enough to buffer environmental stochasticity
2. Demographic stochasticity — Unlikely to be a problem in populations with more than
50–100 individuals
3. Environmental stochasticity — Likely to be a problem unless population sizes are on the order of 1000–10,000
4. Demographic heterogeneity — In the one case I am aware of where the magnitude of environmental stochasticity, demographic stochasticity, and demographic heterogeneity were compared, demographic heterogeneity contributed more to variability in population growth rate than either of the other two, suggesting that populations must be on the order of several thousand to buffer against this source of heterogeneity.
5. Natural catastrophes — No single populations can ever be large enough to buffer against natural catastrophes
These general guidelines are useful, but suppose you’re asked to design a recovery plan for the northern spotted owl.1 How do you go about determining
• How many breeding pairs are necessary to provide a reasonable chance of long-term survival? • What are the prospects for increasing the number of breeding pairs?
1
We’ll talk in some detail about the northern spotted owl next time.
c 2001–2013 Kent E. Holsinger
• What management manipulation will are most necessary to prevent extinction?
• What are the most critical stages of the life-cycle, i.e., have the largest impact on population dynamics?
Recall that the models we’ve discussed so far are based on very general assumptions.
To answer these questions for any specific species, perhaps even for any population, a demographic model
References: [1] H Caswell. Matrix Population Models: Construction, Analysis, and Interpretation. Sinauer Associates, Sunderland, MA, 2nd edition, 2001. American Naturalist, 176(3):410–428, 2006. [4] M Groom, G K Meffe, and C R Carroll. Principles of Conservation Biology. Sinauer Associates, Sunderland, MA, 3rd edition, 2005. [6] E E Holmes. Estimating risks in declining populations with poor data. Proceedings of the National Academy of Sciences USA, 98:5072–5077, 2001. [9] K H Redford. The empty forest. BioScience, 42:412–422, 1992.