TY - JOUR T1 - A <em>Numerus</em> Population Viability and Harvesting Analyses Web App JF - bioRxiv DO - 10.1101/074492 SP - 074492 AU - Wayne M. Getz AU - Oliver Muellerklein AU - Richard Salter AU - Colin J. Carlson AU - Andrew J. Lyons AU - Dana Seidel Y1 - 2016/01/01 UR - http://biorxiv.org/content/early/2016/09/14/074492.abstract N2 - Population viability analysis (PVA) is used to assess the probability that a biological population will persist for a specified period of time. Such models are typically cast as Markov processes that may include age, stage, sex and metapopulation structures, density-dependence and ecological interaction processes. They may also include harvesting, stocking, and thresholds that trigger interventions. Here we present Numerus PVA, which is a web app that includes extensible user-selected options. Specifically, Numerus PVA allows for the specification of one to ten age classes, one or two sexes, single population or metapopulation configurations with 2 or 3 subpopulations, as well as density-dependent settings for inducing region-specific carrying capacities. Movement among subpopulations can be influenced by age, metapopulation connectivity, and attractivity of regions based on the relative fitness of the youngest age classes in each region. Simulations can be carried out deterministically or stochastically, with a user-specified combination of demographic and environmental processes. Numerus PVA is freely available at http://www.numerusinc.com/webapps/pva for running directly on any browser and device. Numerus PVA is easily modified by users familiar with the NovaModeler Software Platform.Biomass:The total mass of a population is commonly used in ecology and resource management in lieu of population size as an alternative to the number of individuals. In Numerus PVA, biomass is used to implement density-dependence (DD) effects.DD effects:Demographic or environmental limits that reduce population growth as populations get larger. Numerus PVA provides density-dependence options that affect survivorship of the youngest age classes youngest female (DD1) and male (DD2), oldest female (DD3) and male (DD4), and mature male (DD5) age-classes, as illustrated in Fig. 1.Demographic stochasticity:Random fluctuations arising from the probabilistic nature of applying vital rates to individuals at every life stage in both sexes.Environmental stochasticity:Random, environmentally-induced fluctuations in survivorship. In Numerus PVA, environmental stochasticity is an option for survivorship of the first life stage only (i.e. environmentally-induced juvenile mortality).Leslie matrix:A transition matrix underlying a discrete-time, linear, age-structured population dynamic model.Metapopulation:A set of connected subpopulations. In Numerus PVA, metapopulations are modeled as a weighted node network with implicit movement of individuals along vertices.Metapopulation connectivity:An underlying matrix with entries, scaled to take values on the interval [0,1], that represent the relative ease-of-transition among different nodes in the metapopulation.Perron root:The dominant eigenvalue of a square non-negative matrix; the Perron root of a Leslie matrix is the rate of population growth.Propensity to move:In Numerus PVA, movement propensity is an age- and sex-based demographic state specifying the likelihood of emigration to another area (independent of destination).Pseudoextinction:The event horizon of population size, below which extinction is certain. In Numerus PVA, pseudoextinction levels can also be treated as thresholds for interventions such as ex situ captive breeding programs.Regional attractivity:In Numerus PVA, once the decision to move has been made, and the connectivity of nodes accounted for, an intrinsic variability in quality of possible destination regions remains. We use the comparative intensity of density-dependent (DD) effects on survivorship of the youngest age class (quantity φ in Eq. 3, with c pertaining the youngest female age class) to scale this quality so that individuals are more likely to go to regions with smaller rather than bigger DD1 effects. ER -