Workshop 1: Wild boar abundance and distribution data

Workshop 1: Wild boar abundance and distribution data

1.- What kinds of data are usable for abundance maps (models)?

2.- Where are data? (especially grey/unpublished data)

3.- To review networks/stakeholders with potential to contribute

4.- How approaching data providers

5.- Inputs for the “hunting statistics collection frameworks”

6.- Practical criteria for validation and quality assessment of wild boar presence data

1.- What kind of data are usable for abundance maps?

  • First step the group should collect occurrence data, i.e. presence/absence; this could be used to develop species suitability models (SDM) for all EU countries
  • For abundance, hunting bags are the only common data we have across Europe. It has the potential to be converted into categories of abundance
  • We need first to see what data is available for each country: hunting statistics
  • Are we collecting also covariate information? Covariate datasets widely available – unlikely to be limiting
  • Validate data from different methods against measurement known to be accurate
  • Can we come up with categories from 0-very no- very high for abundance data?
  • Suggestions:
  • Density map, normalized abundance, or abundance category map instead abundance map. Also produce an uncertainty map to be able to evaluate reliability of data in certain locations. Still not clear what spatial and temporal scale would be available and needed for risk assessment, but multi-scale data collection should be fine
  • Aggregated presence to give proportion area present
  • When recording hunting bags/density, we should be careful with the following elements: what is the area from which the hunting bag comes from? (forest area, or all land area ?); which hunting method is used: driven/silent/fenced? What is the time of density estimate: before or after reproduction?
  • In any case categories should correspond to numerical ranges of abundance since it is needed quantitative information.
  • Data may occur at four levels:
  • Single spot: Georeferenced shooting of boar (e.g. northern Belgium and study in Brandenburg); camera traps, killed on roads data (Slovenia, Czech Republic, part of Netherlands); App-based recording (Netherlands, Belgium) – needs a web search to find others. Also ASF submissions
  • Grid: Slovenia, Finland and Norway report wild boar hunting in small grid (e.g. 1km2)
  • Hunting ground: Hunting areas vary from 100ha to 4000ha. Bag numbers reported are a minimum shot, also poaching nos. unknown. Also need to record – are quotas set (reporting will always be within quota!), how are they set, has this varied between years, and what is the intended aim of hunting quota – the political angle. For example Poland sets exact quota per hunting ground, but has increased this this year to ‘eradicate’ wild boar
  • Regional level: aggregated and summarized information (raw data are not recorded)
  • Data need to be over the last five years, possibly more if available.

2. Where are data?

  • Official agencies/bodies
  • Research groups
  • Management group
  • Hunting stats

Suggestion: to ask each ENETWILD participants what they know about wild boar hunting data collection frameworks – a questionnaire. A protocol for whom (list of people) and how to reach potential data providers need to be established (e.g. first you contact official agencies/bodies, if not answer or in parallel you contact hunting associations, if not answer, try expert opinion or gather data from literature?)

3. To review the network of stakeholders

Suggestion: the list of data providers and stakeholders need to be defined as well as the order or way to approach them

4. How approaching data providers

Need to create profiles of organizations and institutions to be approached for data

Need to locate where certain types of data are (occurrence, density, abundance) using a questionnaire

Target different stakeholders for occurrence data (“citizen-science” organizations) and density/abundance data (governmental agencies)

Prepare and provide agreement for data use (“Data sharing agreement”), also for organization owing citizen-science data on occurrence

We risk potential conflict with animal welfare groups if harvest data is made public on the project website (embargo on some specific, sensitive, data)

First: Identifying data providers: administration, hunters, scientist, laboratories (Trichinella analysis), wildlife managers, APP users (citizen science), damage reports (landowners)

Need to differentiate sources (providers) for presence and for abundance data. Data type and accuracy will depend on the data provider type

Once identified, how to approach them?

  • Design a specific approach and strategy to fit to each provider type and interests
  • Promoting national meetings and discussions among the different stakeholders (data providers), perhaps at a National level
  • Explain the motivation to have the data and put it in the context of national interests
  • Communication, hunters could be involved in decision taking

5. Inputs for the “hunting statistics collection framework”

Need for review of what kind of harvest data (numbers, spatial units, hunting effort, methods, flow of data) countries are collecting to be able to harmonize; review of the national hunting statistics collection frameworks (draft and circulate questionnaire), identifying target contacts to ask for data (where data still is disaggregated)

Need to maximize data collection, i. e. construct a database in a way to allow for collection of all potentially useful variables (not all mandatory)

We can use EU regulations to demand detailed explanation of the national hunting (data collection) systems

Some data are public, but communication with hunters is essential. They should trust and rely on the objectives of sharing the data. Meetings with hunters should be carried out in order to make them participate

Regional and national variability in data availability and hunter collaboration may hamper harmonisation and a good coverage of the data collected

Data sources: hunting, studies on specific spots with actual densities (useful to infer densities to non-surveyed areas), additional efforts (photo-trapping, other abundance determination methods). They should be prioritized in this order and they complete each other sequentially

Situation and problems:


  • Regional variability, national data. Problem of Federal nature
  • Hunting bags available per year and hunting unit from the 17 regions (not centralized)
  • Distribution available
  • Abundance index available for about 20 populations
  • Density estimate scarce


  • National Agency (ISPRA) collects data from all the regions, so national data can be split to regional data
  • Hunting districts, organized trough hunter associations, may provide detailed information


  • ONCFS collects all the information (aggregated), also for local hunting areas


  • Wild boar is a protected species, there is a quota. Data from hunters registered in a non-harmonized way with different accuracy on location and animal data. Provinces starting to manage the data
  • Hunting bag available in the 12 provinces per hunting unit
  • Road kills are difficult to access
  • Some abundance index may exist


  • 26 cantons, registering the data from each canton with a different hunting system
  • Data for each hunting ground exists but they are not centralised.
  • Data are submitted by the hunters
  • Cantons transmit the data to a National level but there is a loss of metadata from local to national level


  • Data for whole country (compulsory to get the hunting license).Problem of not differentiating farmed vs wild boar


  • 600 small hunting areas, reporting annual hunting bag to the administration, with some data loss from local to administration/national level


  • Hunters must put much information for every single wild boar, including GIS in a 1×1 m grid


  • It is compulsory to report immediately a hunted wild boar by the hunter to a National level. Data is public and available, and very straightforwardly transmitted


  • Compulsory to report, but there can be a one-month time lag. Latvia has already provided 2017 data to EFSA


  • Hunters (users of hunting grounds) are obligated to report


  • Every hunting ground user must provide the data to the state


  • Specialists from the Forest Agency collect all data from the regions and transmit it to a national level. No involvement of hunters.


  • Hunters report voluntarily, but it corresponds very well with Trichinella analyses (which are also non-mandatory). They report directly to the national responsible


  • 16 federal states. Two ways of reporting, either hunters or hunting grounds. They report to the respective hunter association, and then to the regional and national levels


  • Hunting bag /year and /hunting unit are available at the national agency
  • Density is available for 2-3 area


  • From citizen science for other population (check SASA): occurrence and abundance index
  • Density (distance sampling) from forestry
  • Information one 1 population: hunting bag and road kill

Trichinella analyses (when geo-located) could be used as quality control for the data gathered. Also perhaps car accidents, which are mandatory to report in some countries (e. g. Sweden) and/or crop damages.

PROBLEMS: Compliance in reporting (reliability, at all steps hunter-reporter-administration), farms (most food from human origin), record of found dead. Definition of hunting year against natural year. Variability in metadata. Level of digitalization of the data (web service against written submission)

Suggestion: To Identify areas with data coverage and white areas, and involve hunters in the interest to complete the area cover

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