FOSS4G 2024 Academic Track

Marine mammals occur in low densities and usually in areas that are difficult to access. One of the main sources of information for marine mammals are stranded animals. However, strandings are rare events and to be biologically meaningful they need to be accumulated over large distances, long times, or both. This work describes SIMMAM (Sistema de Apoio ao Monitoramento de Mamíferos Marinhos), a project aimed at organizing a database of marine mammal sightings and strandings along the Brazilian coast and available at https://libgeo.univali.br/simmam. It began as an internal research project by UNIVALI but now is used by IBAMA and ICMBio. Its initial implementation has already been described [Moraes, 2005; Barreto et al., 2006]. However, it was almost completely rewritten since its initial implementation and SIMMAM 3.0 now conforms to the DarwinCore (DwC) standard, which is an international scientific initiative of the Taxonomic Database Working Group - TDWG. The data architecture adopted is compatible with GBIF, which allows SIMMAM to become a data publisher of marine mammal occurrences.
For the development of SIMMAM 3.0 free source code tools were adopted. On the server side, PHP 7.4 was used with Symfony 5.x framework. For the web client side, the site is rendered on the server side and delivered to the browser as an HTML + JavaScript page with Bootstrap 5. The data exchange API was also implemented in PHP, following the XML standard of DwC. Data is stored in PostgreSQL 11.x with PostGIS 3.x which allows manipulation of geospatialized data. Tables were structured according to the DwC standard, to reduce the complexity of the communication API.
As all occurrences in SIMMAM need to have a geographic position, the main interface for users to view the data is through an interactive WebGIS. The implemented WebGIS has filters by taxon and by type of occurrence (sighting, stranding, incidental capture) to allow users to focus on specific data. To better display areas with high density of records without generating visual clutter, the occurrence layer was clustered, grouping and ungrouping records according to the zoom level. Leaflet Map [Agafonkin, 2020] was used with the OpenStreetMap base map, as it is a modern map engine, has functionalities optimized for mobile devices, and does not have any external dependency. Leaflet supports multiple layers and is compatible with the Open Geospational Consortium (OGC) standard such as support for map mosaics, georeferenced images, WMS [Leaflet, 2020] and GeoJSON [IETF, 2021].
One key aspect of biological information is the taxonomic identification. To avoid taxonomic instability in SIMMAM, it uses the taxonomic list provided by the Integrated Taxonomic Information System – ITIS (www.itis.gov). As the taxonomic classification of mammals is very stable, it was decided to keep a copy of the ITIS database locally to reduce latency, being updated on demand.
The types of occurrence records currently supported by SIMMAM are stranding, incidental capture and sightings. All these occurrence records have fields for defining the best taxonomic level, geo-referencing the occurrence, information on biological material collected and the person responsible for the data. Stranding and incidental capture records contain information regarding the state of the animal (alive or dead), the condition of the carcass (decomposition stage), sex and length. For sightings it is possible to inform environmental parameters such as weather condition, sea state, wind speed, as well as if it was a single animal, part of a group and group size.
The first version of SIMMAM was made available in 2007 to the Centro Mamíferos Aquáticos - CMA, that started to use it as the main tool to integrate data for the Brazilian Stranding Network of Aquatic Mammals (Rede de Encalhes de Mamíferos Aquáticos do Brasil, REMAB). On the same year, SIMMAM was presented to the then General Coordination of Oil and Gas (Coordenação Geral de Petróleo e Gás – CGPEG), current General Coordination of Marine and Coastal Enterprises (Coordenação-Geral de Licenciamento Ambiental de Empreendimentos Marinhos e Costeiros – CGMAC), that used it to aggregate and organize marine mammal sighting data generated by marine mammal observers [Barreto et al., 2019; Britto; 2009]. Presently, sighting data are regularly uploaded to SIMMAM directly by the licensed companies.
As of June 2024, SIMMAM has 423 active users and holds 75,340 aquatic mammal records. Of these, 61% records are private, but this proportion is very different depending on the type of record. For strandings, that are in most part submitted by research institutions, 91% are private as they are the results of individual efforts. But for sightings 61% are public, as they come mostly from the oil industry as part of the environmental licensing of their operations, and they mirror the public reports that have been delivered to IBAMA. As mentioned before, all the data held in the SIMMAM database, regardless of its public availability, can be seen by Brazilian environmental agencies (IBAMA and ICMBio).
The option to allow government agencies to use the whole dataset is extremely important for management purposes, as it enables environmental agencies to use even unpublished data generated by research institutions. But as the data is not available for the general public, it does not compromise their future use in academic publications. Also, a limited visualization of private data in the WebGIS, where details of the record such as species and date are not shown, serves as an indication for other researchers that a specific institution has data on marine mammals in a specific area, fostering collaborations among institutions.
We believe that presenting this work at FOSS4G 2024 will allow us to discuss SIMMAM with the geospatial community and receive input to further improve the system. It shows a successful implementation of open geospatial technologies that is being used both by government and the academic community.