| RAMAS Stage | RAMAS
Generalized Stage Modeling for Population Dynamics
RAMAS Stage lets a user build, run and
analyze discrete-time models for species with virtually any life history.
It is useful for modeling species with complex life histories or other
biologies in which stage membership (rather than age) determines the
demographic characteristics of an individual.
RAMAS Stage comes with templates for species
from many taxa (such as mammals, insects, fish, birds and plants) which
are easy to customize. RAMAS Stage allows a model to include environmental
factors which vary through time, and it yields summaries of the expected
abundance of stages and the uncertainty of those expectations. It also
estimates the risks that an abundance will fall below, or grow above,
General life histories. Simple models can be based on developmental
stage. These include widely used transition matrix models such as Leslie
or Lefkovitch formulations. More complicated models can be constructed
to represent more complex life histories that may include multidimensional
structure (for example age and size simultaneously) and linear or nonlinear
Environmental fluctuations. Models may include information
on environmental factors that influence the population such as temperature
or rainfall. These are specified in terms of their means, variances,
and temporal autocorrelations. Specifying environmental fluctuation allows
the user to introduce stochasticity into models.
Risk assessment. RAMAS Stage estimates the chance that a population
will go extinct or suffer a decline. It also estimates the chance that
the population will grow to some level. It can also compute the risks
for any function of the stage abundances.
RAMAS Stage is a novel implementation
of a Lefkovitch matrix. It generalizes RAMAS Age which was based on
the traditional Leslie matrix. In a Lefkovitch matrix, any of the transition
elements may have non-zero values. This is necessary to represent phenomena
observed in some species that cause individuals to skip stages, revert
to previous stages, or produce offspring of different status. RAMAS
Stage allows you to substitute a function for any of these coefficients.
These functions can take constants, the abundances of other stages,
or the values of environmental factors as arguments.
RAMAS Stage supports generalized models
of life histories based on stages (such as seeds, seedling, ..., canopy
trees), simple or complex transitions (skipping, regression), single-
or multidimensional structure (such as age and size), linear or nonlinear
transitions, pulse or event-structured dynamics. Its interface features
a wide variety of example models for several taxa, a graphical model
editor, a matrix editor, and an equation list editor.
The outputs produced by RAMAS Stage include
average population size over time, interval and terminal quasi-extinction
risk, percent decline and quasi-explosion probability, and time to
cross predefined threshold levels. The program also computes the asymptotic
growth rate (dominant eigenvalue), the stable distribution, reproductive
values, average stage residence times, sensitivities and elasticities.
RAMAS Stage was originally developed for
the United States electric power industry under the sponsorship of
the Electric Power Research Institute.
Requirements: IBM PC compatible; DOS 3+; 380K RAM; VGA,
EGA, MCGA, CGA, or Hercules video. A math coprocessor is recommended.
Cost: See Software Price List and Ordering
In each case, a model of population dynamics
and toxicant kinetics is constructed using a simple Windows interface,
and linked to bioassay data. Parameters can be specified as scalars,
intervals or distributions, to take account of environmental variability
and ignorance. Monte Carlo simulations are then used to predict future
population trajectories, and calculate the risk of adverse events such
as extinctions or algal blooms.RAMAS Ecotoxicology and RAMAS Ecosystem
are practical tools that highlight the importance of including ecological
interactions in risk assessments.
Population-level Ecotoxicological Risk Assessment (RAMAS Ecotoxicology)
RAMAS Ecotoxicology is used to make population-level
ecological risk assessments for environmental contaminants. It imports
data from standard laboratory bioassays, incorporates these data into
the parameters of a population model, and performs a risk assessment
by analyzing population-level differences between control and impacted
Bioassays for assessing the impact of
toxins on natural systems are usually expressed in terms of individual-level
assessment endpoints such as growth, survivorship and fecundity. RAMAS
Ecotoxicology translates such results into a forecast of their likely
consequences at the level of the entire population. For instance, if
there is an increase in mortality rate due to a contaminant, the meaning of
this effect can only be determined by projecting the consequence in
terms of the total population’s future abundance and vitality. It is
generally important to do this projection to the poulation level because
impacts at the organismal level cannot be easily extrapolated to predict
their population-level consequences. For instance, minor and inconspicuous
impacts on individuals can sometimes cascade through population dynamics
into significant effects at the level of the population. Conversely,
seemingly major impacts on individuals may translate into only minor
population-level consequences once the normal population feedbacks
have been taken into account. Moreover, contradictory findings are
possible at the level of the individual (e.g., decreased survival but
increased fecundity) that must be resolved.
RAMAS Ecotoxicology uses stage-structured
single-population models and food chain models to make the necessary
projections. The software checks the validity of the input and model
structure specified by the user. It uses a sophisticated second-order
Monte Carlo engine to project both natural temporal variability and
measurement error, and expresses its results in risk-analytic outputs
such as the risk of the population’s declining to a given level.
RAMAS Ecotoxicology was developed by Applied
Biomathematics with support from the Electric Power Research Institute.
Ecosystem-level Ecotoxicological Risk Assessment
Manage variability and uncertainty, express results
as ecological risks.
- Specify parameters as scalar numbers, intervals (e.g. [10,15] mg
per liter) or distributions (e.g. [10,1]mg per liter) . Automatic
unit conversions and checking for dimensional consistency
- Dose-response model: Weibull, probit, logit
- Predator-prey interactions: Lotka-Volterra, Holling type II. Ratio-dependent
- Density dependence: ceiling, logistic, Ricker, Beverton-Holt
- Monte Carlo treatment of measurement error and evironmental variation
- Summarize results as biomass/abundance projections and risk statistics
- Display graphs and tables, save or paste into other applications
- Comprehensive online help
RAMAS Ecosystem was developed
by Applied Biomathematics with support from the Electric Power Research