1 / 13

Population Viability Analysis

Population Viability Analysis. Seeks relationship between population size and probability of extinction does not need to calculate MVP concerned more with determination of probability that a population will persist for some arbitrary time (Boyce 1992)

sawyer
Télécharger la présentation

Population Viability Analysis

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Population Viability Analysis • Seeks relationship between population size and probability of extinction • does not need to calculate MVP • concerned more with determination of probability that a population will persist for some arbitrary time (Boyce 1992) • combine all sources of stochasticity and deterministic population growth into one model (usually requires computer simulation).

  2. PVA is More than Modeling • It is the process of synthesizing information about a species or population and developing the best possible model for the dynamics of population size (Boyce 1992) • Learn what you do not know • Sensitivity analysis indicates what parameters may be especially influential • Suggests management starting points that should be monitored and adjusted through adaptive management

  3. Steps in PVA (Boyce 1992) • Project demographics of populations through time • basically simulate life tables if age-structure is needed • Forecast viability through time • affected by model of demographics and incorporation of stochasticity • errors get amplified as projections span longer periods

  4. Importance of Genetics versus Demographics in Modeling • Emphasis should be on ecological, environmental, and demographic factors not genetic ones • little evidence that genetic factors lead to extinction • allee effect, demographic stochasticity, disruption of dispersal by habitat fragmentation are important (Lande 1988) • allee effect: disruption of critical social behaviors when populations decline too far leads to rapid extinction for nongenetic reasons

  5. Dangers of Using Too Few Variables • Early PVAs and MVP calculations were quick to use genetic considerations only • Led to 50, 500 rule (Franklin 1980, Soule and Wilcox 1980) • Ne >50 needed for short-term survival (avoid inbreeding) • Ne>500 needed for long-term survival (ability to evolve in changing environments) • Spotted Owl and Red-Cockaded woodpecker conservation strategies were designed to maintain 500 breeders • Lande (1988) argues this would lead to extinction because dispersal ability in fragmented habitat was not accounted for

  6. PVA Shortcomings • Simple assumptions as already stated • but models are supposed to simplify! • So don’t rely on them for absolute management advice • Ignore ecology and focus on stochasticity, esp. genetics as mentioned • need to take into account habitat and spatial structuring of populations • Effects of other species (biotic interactions) • Need to account for interactions among various vortices

  7. Does More Data Help? • Yes, you can then estimate variation in demographics • Variance tends to increase as sample increases up to a point. (Boyce 1992) • Insects >8 years • birds and mammals may take 30-40 years

  8. Ongoing Improvement in PVA (Mann and Plummer 1999) • Workshop last year in Berkeley • Stretching PVAs to cover more types of life forms • application to plants will remain difficult • seed banks hard to model • Should genetic factors be modeled or are demographic ones sufficient? • Include human population growth and expected changes in landcover in models

  9. Example of PVA for Alala Double clutching and predator control may be effective

  10. Catastrophes Really Limit Ability to Recover Population

  11. Managing the Captive and Wild Populations Together Increases Chance of Recovery Two Populations are better than one even with catastrophes

  12. References • Dennis, B. Munholland, PL, and Scott, JM. 1991. Estimation of growth and extinction parameters for endangered species. Ecol. Monogr. 61:115-143. • Shaffer, ML. 1981. Minimum population sizes for species conservation. Bioscience 31:131-134. • Boyce, MS. 1992. Population viability analysis. Annual Review of Ecology and Systematics. 23:481-506. • Leigh, E. G. Jr. 1981. The average lifetime of a population in a varying environment. J. Theor. Biol. 90:213-239. • Lande, R. 1988. Genetics and demography in biological conservation. Science 241:1455-1460. • Simberloff, D. 1988. The contribution of population and community biology to conservation science. Ann. Rev. Ecol. Syst. 19:473-511

  13. More References • Thompson, G.G. 1991. Determining minimum viable populations under the endangered species act. NOAA Technical Memorandum NMFS F/NWC-198. • Mann, C. C., and M. L. Plummer. 1999. A species’ fate, by the numbers. Science 284:36-37. • Soule, M. E. 1987. Where do we go from here? In M. E. Soule (editor), Viable populations for conservation. P. 175-183. Cambridge University Press, Cambridge.

More Related