Open Source Fortran Ecosystem Sciences Software for Mac

Input 1 - A training dataset (multiple observations) of up to four variables (predictors) against one (response variable) Input 2 - A test dataset (multiple observations) of the same four variables with unknown response variable Output - Calculation of the response variable for each test observation using fuzzy logic or fuzzy rule-based Bayesian algorithms HABFUZZ is a habitat model, which can be used in ecohydraulic modelling applications for the calculation of the instream habitat suitability in various discharge scenarios in a simulated river reach. It comes with no graphical user interface but it's a one-click tool. Just provide your input and let HABFUZZ provide you the output. The HABFUZZ manual https://github.com/chtheodoro/habfuzz/blob/master/HABFUZZ_v2.5_manual.pdf HABFUZZ in the Journal of Open Source Software http://joss.theoj.org/papers/1ad27db8f0976c28a75e20d34eba5ee2 HABFUZZ website https://chtheodoro.wixsite.com/habfuzz

Oxygen Model for Microtidal Estuaries and Lagoons-OMMEL. Initially designed to describe O2 dynamics in Alfacs Bay (Ebre Delta, NW Mediterranean, Spain), but usable for any marine coastal ecosystem with small tides. http://tdr.cesca.es/TDX-0222108-113814

Implementation of HYCOM physical ocean model with coupled biogeochemical component to study nitrogen fixation in the Amazon plume. This project is still in development, the code may not be functional at this time.

We have moved, the project is now at http://distancesampling.org

WHATCH’EM simulates the highly non-linear manner in which atmospheric conditions and container characteristics determine water temperature and height, leading to results that are not always intuitive and likely not simulated by simpler empirical models. WHATCH’EM has the capacity to be utilized for other mosquitoes and other container-inhabiting arthropods.

GeoSciPy is a set of C and Python functions that provide an API for all aspects of Geoscience and Remote Sensing Applications. Functions include reading/writing of many data formats, images, vectors, ..., and processing of images, vectors, ... including map projections, ... The library is written C, using HDF5 as the file format for storage of all remotely-sensed data and ancillary data, as well as processed data. The C functions assume a particular format for the HDF5 file contents, and provide functions for reading and writing data to such files. There is also a Python API that provides a procedural as well as an object-oriented interface to these functions. A Python GUI for interacting with such datasets is also part of the project. While there are other open-source GIS, and image-processing packages available, this one is designed to be comprehensive, work on 3 major platforms, user-extensible, fast, and able to handle huge datasets. Click the Blog tab for more info.