Tool
In the IIASA Strategic Initiative fairSTREAM, we create a toolkit of participatory methods that can be adapted to facilitate co-production of knowledge. Co-produced knowledge integrates diverse scientific and social discourses to create relevant and legitimate opportunities in the context of complex problems.
Dataset
We provide a global spatially explicit characterization of terrestrial and marine habitat types, as defined in the International Union for Conservation of Nature (IUCN) habitat classification scheme, which is widely used in ecological analyses, including for assessing species’ Area of Habitat. The maps broaden our understanding of habitats globally, assist in constructing area of habitat (AOH) refinements and are relevant for broad-scale ecological studies and future IUCN Red List assessments.
Model
The ibis.iSDM package provides a series of convenience functions to fit integrated Species Distribution Models (iSDMs). With integrated models we generally refer to SDMs that incorporate information from different biodiversity datasets, external parameters such as priors or offsets with respect to certain variables and regions.
Dataset
Stochastic Quasi-Gradient (SQG) methods have been developed for solving general optimization problems without exact calculation of objective function and constraints (let alone of their derivatives). SQG methods enable a sequential revision of approximate solutions towards the optimal using newly acquired information on the system, obtained via either direct on-line observations or(and) simulations.
Model
The linkage algorithms solve the problem of linking models, e.g. sectorial and/or regional, into an inter-sectorial inter-regional integrated model. Linkage enables to avoid “hard linking” of models in a single code, which saves the programming time and enables parallel distributed computations of individual models instead of a large scale integrated model. Models linkage preserves the structure of the original models taking into account critically important details, which are usually missing in aggregate models.