• A strong effort is needed to aggregate existing (previously) and validated data to build robust distribution models due to the current fragmentation of organizations, initiatives and data sources
  • By building networking, in parallel to developing quality standards and collection of data, ENETWILD will merge a large amount of data that is already available, and will promote the generation of data under harmonized protocol

Credits: Joaquín Vicente Baños

Harmonizing data collection is a long-term project; and ENETWILD will be a first step. We will harmonise the European data framework for our species and topics (distribution and abundance), which opens the space to aggregate these data from the whole Europe. Our strategy requires solid foundations in order to be able to collect and validate data that will support science based modelling and risk assessment. ENETWILD will firstly develop standards for presence / abundance data (of the required species) under the criteria of being (i) effective for filtering high quality data needed to produce high quality maps and models, and (ii) compatible with existing biodiversity data collection systems in order to optimize inter-operability between them. It will take several years to set up the data (plus metadata) standards to record species occurrence and abundance. Aggregating data will be then the second step, as they have to be transformed into this standard, but it will be feasible directly by data providers through the coming platform. If crucial data are not recorded, it will be not possible to assess correctly the value and the differences among the studies/sources of data, for comparison purposes.

Next, we indicate the main items of ENETWILD during the next years in relation to data collection, validation; modelling, tools development and networking for wild boar distribution and abundance.


Reports on existing standards, including an evaluation of their compatibility (Nov 2017)


· Annual General Meeting (Parma, 16-18th Jan).
· A census of European wildlife species presence databases, following a standardized protocol (Feb 2018)
· Description of national systems and organizations responsible for species’ presence, distribution and abundance data collections (Mar 2018)
· Presence standards ready (Mar 2018)
· Preliminary models on wildlife distribution based on already available (not necessarily validated) as a base for GAP analysis (Jun 2018).
· Citizen science platform incorporated to the website (Dec 2018).


· 2nd Annual General Meeting and Report (first quarter 2019)
· Presence standards for ENETWILD already implemented in a web tool (first quarter 2019)
· Abundance standards for some species ready (Mar 2019)
· First models based on presence data (Mar 2019)
· First data on presence available in EFSA data Warehouse (first quarter 2019)


· 3nd Annual General Meeting and report (first quarter 2020)
· Some abundance standards for ENETWILD already implemented in a web tool (first quarter 2020)
· Abundance standards for some new species ready (Mar 2020)
· Models based on presence data and first models based on abundance data (Mar 2020)
· Three-monthly updates of freely available published data of included wildlife species (included in the DCF)
· Three-monthly updates of the geographical distributions and abundance of wildlife populations suitable for publication as on-line maps and charts.
· First data on abundance available in EFSA data Warehouse (first quarter 2020)

Complete census of European Wildlife Species presence data bases, following a standardized protocol

Description of national systems and organizations responsible for species´ presence, distribution and abundance data collection


Presence standards ready

how to calculate reliable estimation of wild boar abundance:how it is possible to derive abundance from other data

  • Definition of items to collect in the Data Collection Model (DCM)
  • Data dictionary on wild boar density

Upload data in the DCF of EFSA Meeting

Actively contact data providers to explain DCM

Distribution of questionnarie: how hunting statistics are recording across Europe, who manages disaggregated data

This map illustrates the distribution each of the four regional partners will cover for data collection and quality assessment. These 4 groups will encourage active data sharing by our network of collaborators.

1. South West region: French National Hunting and Wildlife Agency (ONCFS) & National Institute on Wildlife Research (IREC, Spain).
List of Countries: France, Spain, Belgium, Switzerland, Portugal, and Luxemburg.

2. South East region: University of Torino (UNITO)/ University of Sassari (UNISS)
List of Countries: Italy, Slovenia, Serbia, Croatia, Bosnia & Herzegovina, Montenegro, Kosovo, Macedonia, Albania, Greece, Bulgaria, Rumania, Moldova, Turkey, and Cyprus.

3. North West region: Institute for Terrestrial and Aquatic Wildlife Research (ITAW)
List of Countries: Germany, UK, Ireland, Netherlands, Austria, Czech Republic, Slovakia, Hungary, Denmark, Norway, and Sweden.

4. North East region: Mammal Research Institute Bialowieza (MRI)
List of Countries: Poland, Finland, Russia, Belarus, Latvia, Lithuania, Estonia, Ukraine, Georgia, Armenia, and Azerbaijan.