• 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.

Models on
spatial distribution and density
data

First Model occurrence
data 
on wild boar

Proposals for harmonization data collection
on hunting statistics and census

 Modelled WB distribution based
on hunting statistics and census

 Actively contact data providers to explain DCM

Upload data in the EFSA DCF and to GBIF

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

Harmonization of hunting statistics
for abundance estimation

 Model and validation  WB distribution based
on hunting statistics and census

 Actively contact data providers to explain DCM

Upload data in the EFSA DCF and to GBIF

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.