- Home
- Companies
- Ramas (Applied Biomathematics)
- Software
- RAMAS - Version Metapop 6.0 - ...
RAMAS - Version Metapop 6.0 -Predicting Extinction Risks and Exploring Management Software
In nature, most species exist in metapopulations, seen in fragmented habitats or on archipelagos, where the spatial structure of the environment affects the population dynamics. RAMASMetapop is a powerful tool for population viability analysis (PVA), as well as an interactive program that allows you to build models for species that live in multiple patches. The program has a multitude of uses such as predicting extinction risks and exploring management options such as reserve design, translocations and reintroductions, and to assess human impact on fragmented populations. In addition, RAMAS Metapop incorporates the spatial aspects of metapopulation dynamics, such as the configuration of the populations, dispersal and recolonization among patches and the similarity of environmental patterns the populations experience.
Use RAMAS Metapop to build models that incorporate
- Spatial structure and multiple populations
- Age or stage structure
- Density dependence
- Variability (stochasticity)
Features of RAMAS Metapop Include:
- Age or stage structure for each population
- Random variation and temporal trends in vital rates (survivorships, fecundities) and carrying capacities of populations
- Several types of density dependence
- Age or stage-specific dispersal rates and catastrophes.
Recent developments make it easier to use RAMAS Metapop and RAMAS GIS to develop and analyze population models.
Using mark-recapture data
Mark-recapture data are collected by marking individuals (e.g., using bands or tags) at their first capture and recording their subsequent recaptures. This type of data is immensely valuable for estimating parameters of population models, including survival rates and fecundities. Many methods have been developed for analyzing such data, but most of them are either incomplete (i.e., they do not allow a full population model) or are too complex. A new method, implemented as an R script, allows building fully-specified population models for RAMAS, based only on mark-recapture data (Ryu et al. 2016). It creates a fully specified RAMAS model file, which includes stage structure, standard deviations, and density dependence functions.
Its main features include:
- estimating true survival based on apparent survival estimates and population trends (population viability analysis: PVA);
- fecundity as an unbiased estimate of juvenile:adult ratio, by using the relative capture probabilities of juveniles and adults;
- estimating density dependence in survival and fecundity;
- estimating natural temporal variability in survival and fecundity (excluding sampling variability);
- creating ready-to- run RAMAS input files;
- incorporating uncertainties and preparing the files necessary for a global sensitivity analysis (see below).
The new method, including the R script, data for case studies and sample results, is freely available at: https://github.com/Akcakaya/MAPS-to-Models.
Global sensitivity analysis
The sensitivity analysis module of RAMAS GIS (see Chapter 13 of the manual) allows analyzing sensitivity to one parameter at a time. A more comprehensive method, called global sensitivity analysis, considers all parameters simultaneously. A new method, implemented as an R package, allows global sensitivity analyses using RAMAS (Aiello-Lammens and Akçakaya 2016). The R package, including sample data and a tutorial, is freely available at: https://github.com/mlammens/demgsa.