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Data from: Using structured eradication feasibility assessment to prioritise the management of new and emerging invasive alien species in Europe

Citation

Booy, Olaf et al. (2020), Data from: Using structured eradication feasibility assessment to prioritise the management of new and emerging invasive alien species in Europe, Dryad, Dataset, https://doi.org/10.5061/dryad.8pk0p2nk1

Abstract

Prioritising the management of invasive alien species (IAS) is of global importance and within Europe integral to the EU IAS regulation.  To prioritise management effectively the risks posed by IAS need to be assessed, but so too does the feasibility of their management.  While risk of IAS to the EU has been assessed, the feasibility of management has not. We assessed the feasibility of eradicating 60 new (not yet established) and 35 emerging (established with limited distribution) species that pose a threat to the EU, as identified by horizon scanning.  The assessment was carried out by 34 experts in invasion management from across Europe, applying the Non-Native Risk Management scheme to defined invasion scenarios and eradication strategies for each species, assessing the feasibility of eradication using seven key risk management criteria.  Management priorities were identified by combining scores for risk (derived from horizon scanning) and feasibility of eradication. The results show eradication feasibility score and risk score were not correlated, indicating that risk management evaluates different information than risk assessment. Seventeen new species were identified as particularly high priorities for eradication should they establish in the future, while fourteen emerging species were identified as priorities for eradication now. A number of species considered highest priority for eradication were terrestrial vertebrates, a group that has been the focus of a number of eradication attempts in the EU.  However, eradication priorities also included a diverse range of other taxa (plants, invertebrates and fish) suggesting there is scope to broaden the taxonomic range of attempted eradication in the EU. We demonstrate that broad scale structured assessments of management feasibility can help prioritise IAS for management.  Such frameworks are needed to support evidence based decision making.

Methods

A combination of expert elicitation, review and consensus building methods were used to produce and validate a risk management assessments for (invasive) alien species (feasibility of eradication from Europe). 34 experts were engaged in an elicitation process grouped into five taxonomic specialisms: freshwater animals, terrestrial vertebrates, terrestrial invertebrates, marine species, and plants (excluding marine plants). Each group comprised 5-8 experts. Each species was independently assessed by at least three different experts using the non-native risk management scheme (NNRM) (Booy et al. 2017) using predefined invasion scenarios (a factual description of the current or potential distribution and spread of the species in the EU) and eradication strategies (a realistic combination of methods and techniques for eradication). Experts provided response and confidence scores for seven risk management components (i.e. effectiveness, practicality, cost, impact, acceptability, window of opportunity and likelihood of reintroduction) as well as scoring the overall feasibility of eradication. A two-day workshop (17-18 May 2016) was then held to review, refine and ultimately agree scores by consensus using a simplified, facilitated Delphi approach including two rounds of consensus, within and across expert groups.

The dataset contains the consensus score resulting from this exercise. It contains the following fields:

  • Species: Scientific name of the species
  • Common Name: Common name of the species
  • RM_exp_grp: Expert group (Freshwater, Marine, Plants, Tinverts = terrestrial invertebrates, Tverts = terrestrial vertebrates)
  • Environment: Freshwater, Marine, Terrestrial
  • Taxa: Plant, Invertebrate, Vertebrate
  • Est_in_EU: Established in the EU (Y) or not (N)
  • Scen_code: Scenario code. Letters A-D represent the number of discrete populations (respectively 1-3, 4-10, 10-50, +50) and numbers 1-6 represent total combined area (respectively <1ha, 1-10ha, 10ha-1km2, 1-10km2, 10-100km2, >100km2). For example, the code B2 indicate a species with 4-10 populations covering a total area 1-10ha.
  • Effectiveness: consensus score for effectiveness (VH = very high, H = high, M = medium, L = low, VL = very low)
  • Practicality: consensus score for practicality (VH = very high, H = high, M = medium, L = low, VL = very low)
  • Cost: consensus score for cost (VH = very high, H = high, M = medium, L = low, VL = very low)
  • Impact: consensus score for non-target impact (VH = very high, H = high, M = medium, L = low, VL = very low)
  • Acceptability: consensus score for acceptability (VH = very high, H = high, M = medium, L = low, VL = very low)
  • Window of Opportunity: consensus score for window of Opportunity (Vlong = very long, Long, Med = medium, Short ,Vshort = very short)
  • Likelihood of Reinvasion: consensus score for likelihood of Reinvasion (VH = very high, H = high, M = medium, L = low, VL = very low)
  • Overall RM: overall risk management score for feasibility of eradication (VH = very high, H = high, M = medium, L = low, VL = very low)
  • Econf: Confidence in effectiveness score (H = high, M = medium, L = low)
  • Pconf: Confidence in practicality score (H = high, M = medium, L = low)
  • Cconf: Confidence in cost score (H = high, M = medium, L = low)
  • Iconf: Confidence in impact score (H = high, M = medium, L = low)
  • Aconf: Confidence in acceptability score (H = high, M = medium, L = low)
  • Wconf: Confidence in window of opporunity score (H = high, M = medium, L = low)
  • Lconf: Confidence in likelihood of reinvasion score (H = high, M = medium, L = low)
  • RMconf: Confidence in overall risk management score (H = high, M = medium, L = low)
  • Priority: Priority for eradication (takes into account horizon scanning risk scores, which are not in this dataset) (Highest, Very High, High, Medhigh, Medium, Medlow)

Funding

Newcastle University,

Research Institute for Nature and Forest (INBO),

Austrian Science Foundation FWF, Award: I2086-B16

Darwin plus Improving biosecurity in the SAUKOTs through Pest Risk Assessments, Award: DPLUS074