Joint Cetacean Database and Mapping (JCDM) in Italian waters: a tool for knowledge and conservation

Anno
2020
Proponente Giovanna Jona Lasinio - Professore Ordinario
Sottosettore ERC del proponente del progetto
PE1_14
Componenti gruppo di ricerca
Componente Categoria
Luca Tardella Componenti strutturati del gruppo di ricerca
Componente Qualifica Struttura Categoria
Edoardo Bompiani Funzionario tecnico qualifica D1 dipartimento di scienze statistiche Altro personale aggregato Sapienza o esterni, titolari di borse di studio di ricerca
Abstract

Today, besides than carrying out new researches, it is pivotal for science to make data and results directly accessible to the public and, in particular, to decision-makers for conservation purposes. In this light, statistical methods, data visualization, and data sharing tools make it easy to visualize and share raw data (databases) as well as data elaborations.
Cetaceans are strictly protected in many sectors of the Mediterranean Sea, though our understanding of species spatial distributions and habitat use is still deficient. These represent basic information to better understand cetaceans' ecology and identify zones overlapping with human activities. However, these mammals are elusive and highly mobile, able to migrate for thousands of kilometers. Hence, targeted surveys are expensive and occurrence data are sparse in space and time. We aim at building the most comprehensive database of cetaceans' occurrences in the Italian waters to estimate the abundance and distribution patterns of single species and entire taxa. The database will archive records provided by different sources (social media and scientific surveys). The database has to be nestled in a standardized framework controlling for heterogeneous observation efforts yielded by data sources. The statistical methodology must take into account these sources of variability and also the specific features of presence-only data. Elaborations will be presented in a web app in the form of interactive descriptive maps. Users could navigate through the map and simulate different predictive scenarios of occurrence probability based on environmental predictors. These maps could directly represent an easily readable tool for managers and decision-makers to plan conservation actions; data will be available to the scientific community for further investigations through direct downloads from the app. The latter will be regulated according to different access levels defined according to legal regulation on data ownership.

ERC
SH2_7, PE1_14, LS8_11
Keywords:
STATISTICA AMBIENTALE, BIOLOGIA AMBIENTALE E MARINA, STATISTICA COMPUTAZIONALE, INFERENZA STATISTICA, ZOOLOGIA

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