Population Viability Analysis: Understanding Extinction Risk through Population Dynamics -, Study notes of Conservation biology

Download Population Viability Analysis: Understanding Extinction Risk through Population Dynamics - and more Study notes Conservation biology in PDF only on Docsity! What is Population Viability Analysis (PVA)? One definition: a quantitative analysis of population dynamics, with the goal of assessing extinction risk. PVA is a process involving: (1) demographic data for the species of interest and (2) some kind of mathematical analysis of those data. The product of the analysis is (at least) (3) some quantitative prediction of extinction risk. The development and use of PVA has been (at least partially) driven by certain policy/legislation, especially the National Forest Management Act (1976) What is meant by “population dynamics”? Population sizes change over time. Why? Many things affect population size: competition and other interactions, population structure, environmental variation, disturbance and succession, chance events, habitat attributes (habitat quantity, quality, configuration, and connectivity) Let’s take a look at three (simple) models of population growth 1. Exponential growth In a “closed” population (no immigration or emigration), population growth can be modeled as a function of the per capita birth rate (b) and the per capita death rate (d). The intrinsic rate of increase (r), or more generically, the population growth rate, is the difference between the birth and death rates (r=b-d). We can use this model to predict population size at any desired point in time in the future if we know just two things: (1) the population size at some point in time (either the present or the past) and (2) r, the intrinsic rate of increase! Question: What does this model suggest about how many individuals are needed for a “viable” population? Why don’t populations follow the “J-curve” predicted by the exponential model? 2. Logistic growth In this model, the population growth rate declines with increasing population size. Birth rates go down and/or death rates go up as the population gets bigger. (Why?) The result is that the population has a “carrying capacity”, a stable population size that it tends towards. Question: What does this model suggest about how many individuals are needed for a “viable” population? Alternatively, it may be that the population growth rate increases with population size when the population is small. That is, birth rates go up and death rates go down as population size increases (Allee effect). Why might this happen? Examples? 3. Structured population growth What is meant by “structure”? Individuals in a population often differ in their contribution to population growth (or decline) because they differ in their chances of survival or successful reproduction. This may be because of differences in age, developmental stage, or size. What does a structured population model look like? It’s a matrix. More specifically, it’s referred to as a “transition” or “projection” matrix. The matrix model allows you to project into the future how many individuals there will be in the different classes, and the total population size. Analysis of a matrix population model yields a number of useful things: a. The dominant eigenvalue (λ). This is the growth rate to which the population eventually converges. b. Sensitivities. These are the sensitivity of λ, the asymptotic population growth rate, to an absolute change in each element in the projection matrix. The sensitivities allow one to see what would happen to the population growth rate (and hence, extinction probability) if we could improve survival and fecundity values in the projection matrix, one at a time, by a particular value. In the loggerhead turtle example, we can answer the question: would it be better to focus conservation efforts on improving the survival of hatchlings or large juveniles or adults? How much bang do you get for your management buck? c. Elasticities. Elasticites tell us the proportional change in the population growth rate that will result from a proportional change in each matrix element. How much percent change in the population growth rate will result from some given percent change in each life history transition (survival or fecundity)? As above, we can answer the question: would it be better to focus conservation efforts on improving the survival of hatchlings or large juveniles or adults of loggerhead turtles? So which do we use to guide management, sensitivities or elasticites? Generally, elasticities are considered more useful for management considerations. 4. Stochastic models a. environmental stochasticity In reality, the environment varies from one year to the next. Some years may be good, others bad, for a population of an endangered species. We want to be able to say what the trend is for that population. On average, is it growing or declining? Some populations grow or decline with regular or somewhat predictable changes in their environment; that is, as a community recovers and changes after some sort of disturbance (e. g. fire, flood, hurricanes or other storms). This also can be modeled. Especially with respect to fire, which is now controlled in many natural communities, we can ask questions like, how often should we conduct controlled burns for an endangered species to persist in that community? b. demographic stochasticity Very small populations are vulnerable to extinction via demographic stochasticity. The analogy is tossing a coin (in the case of survival vs. death, or offspring being male vs. female) or rolling a die (for example, when the number of offspring can be a number between 1 and 6).