Examples of data structure and program flow implemented by <i>MetaModel</i><i>Manager</i>.

<p>(A) Nested data representing a species in a metamodel. Global state variables (GSvar), population state variables (PSvar), and individual state variables (ISvar) are descriptors of the overall system, each population, and each individual, respectively. (B) Flow of control among component models. Curved arrows represent access to and modification of data. Block arrows represent control passed among models. (C) A two-species metamodel, with one modifier and one translator model acting on one species and two modifier models acting on the second species. Control alternates between the species, as illustrated by solid block arrows. Each system, modifier, and translator model has access to change any property of its populations and individuals as well as any shared global state variables.</p

Metamodel that integrates demography, landscape change, dispersal, and disease status.

<p>A PVA program acts as the system model (solid outline) to simulate individual survival and reproduction based on individual and population state variables (shown in italics) passed from other models. Modifier models (dashed outlines) simulate habitat dynamics, individual movements, and individual transitions in disease status. A central facilitator program passes state variables between the system and modifier models at appropriate time steps. The ultimate results are measures of population dynamics and extinction risk for a species impacted by habitat change and disease.</p

Metapopulation dynamics influenced by dispersal.

<p>Metapopulation size is projected by (A) a PVA model in <i>Vortex</i> assuming varied rates of dispersal, annual fluctuations in demographic rates, and inbreeding depression; (B) a metamodel that linked a PVA model in <i>Vortex</i> to an infectious disease model in <i>Outbreak</i>, assuming varied rates of dispersal, minimal annual fluctuations in demographic rates, and no inbreeding depression; and (C) a metamodel that linked a PVA in <i>Vortex</i> to an infectious disease model in <i>Outbreak</i>, assuming varied rates of dispersal, annual fluctuations in demographic rates, and inbreeding depression. In (A), higher rates of dispersal increase growth and stability of the metapopulation because stochastic effects in local subpopulations are dampened. When disease was introduced but stochasticity was removed, as in (B), higher rates of dispersal depress population size because of the faster spread of disease. Finally, when stochasticity, disease, and dispersal were considered in (C), higher dispersal initially reduced population size because of the faster spread of disease. In later years, disease was largely eliminated from the system, and higher rates of dispersal stabilized the population against stochastic fluctuations. During a few years in the middle of the simulation, disease and stochastic processes were equally important, and intermediate rates of dispersal led to the highest population size.</p

Population trajectories for a prey species subjected to different levels of predation.

<p>Mean prey population size through time is predicted by a single-species PVA model that assumed a fixed predator population size. Simulations were run for predator populations of 50, 60, 70, 80, and 100 individuals. The prey population was sustained at a size of N = 10000 or more if there were 80 or fewer predators.</p

Population trajectories for a predator species at different levels of prey availability.

<p>Mean predator population size through time is predicted by a single-species PVA model that assumed a fixed prey population size. Simulations were run for prey populations of 5000, 6000, 7000, 8000, 10000, and 15000 individuals. Approximately 6000 prey was sufficient to sustain growth of the predator population from its initial N = 50 to more than 100.</p

Mean predator-prey dynamics in coupled metamodels that (A) did not include and (B) did include stochastic variation.

<p>Mean population densities (N/K) for a predator and a prey species are predicted by a two-species metamodel, which assumed that the density of one species would impact the other species. In (A), externally driven sources of stochasticity (e.g., environmental variation, catastrophes) and inbreeding did not impact either population, and we found that the predator population grew rapidly, causing collapse of the prey population followed by collapse of the predator population. In (B), externally driven stochasticity and inbreeding depression could impact each population. For this scenario, the average trajectory shows that the predator population grew, followed by a decline in prey, causing subsequent decline in the predator, eventually resulting in a possibly stable state in which a reduced prey population sustained a reduced predator population.</p

Average percent gene diversity lost annually before inbreeding thresholds were reached and population growth rates after thresholds began influencing mate availability in simulated African wild dog populations experiencing a range of levels of inbreeding avoidance.

<p>Average percent gene diversity lost annually before inbreeding thresholds were reached and population growth rates after thresholds began influencing mate availability in simulated African wild dog populations experiencing a range of levels of inbreeding avoidance.</p

Sensitivity analyses for selected model input variables with a ±25% variation range in values for a simulated African wild dog population.

*<p>Indicates the variables with the highest model sensitivity (S).</p

Carrying capacity determines persistence.

<p>Average projected size of simulated wild dog populations over 100 years with the carrying capacity parameter set at varying levels in relation to initial population size. Model assumes an inbreeding avoidance threshold of F = 0.20.</p

Occasions where inbreeding was possible versus observed in the field within natal packs, after reproductive vacancies, and among siblings in the KZN African wild dog population (adults and yearlings) from 1997 through 2008.

§<p>Mother-son pair that bred together multiple years.</p>†<p>Full siblings unfamiliar to each other due to being born 2 years apart and present in the natal pack at different times.</p