Wild boar in focus: initial model outputs of wild boar distribution based on occurrence data and identification of priority areas for data collection

Croft, Simon; Smith, Graham C.; Acevedo, Pelayo; Vicente, Joaquı́n

doi:10.2903/sp.efsa.2019.en-1533

Cited by 7 publications

(6 citation statements)

References 19 publications

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“…In this study, we used an expert elicitation approach to assess the relative contributions of natural and anthropogenic factors in limiting wild boar distribution in northern Eurasia. Doing such analysis in quantitative terms is difficult because of differences in data quality between countries and regions, especially in relation to the effects of hunting and natural predators (ENETWILD-Consortium et al 2019. The main disadvantage of the expert elicitation approach is that experts' opinions reflect personal knowledge and views, and cannot be verified or reproduced by independent researchers.…”

Section: Factors Limiting or Promoting Wild Boar Range Expansion In N...mentioning

confidence: 99%

The wild boar Sus scrofa in northern Eurasia: a review of range expansion history, current distribution, factors affecting the northern distributional limit, and management strategies

Markov

Economov²,

Hjeljord

et al. 2022

Mammal Review

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The wild boar Sus scrofa is one of the most widely distributed large mammal species in the world, existing on all continents except Antarctica. In the late 20th Century, its geographical range expanded naturally and through intentional releases. Despite the environmental, social, and economic importance of the wild boar, its current distribution in northern Eurasia remains uncertain, and the factors that limit and promote expansion in northern ecosystems are unknown. We aimed to summarise the history of wild boar range expansion and current distribution in the countries of northern Eurasia. We also assess the relative importance of climate (both harshness and warming), habitat (both current diversity and possible change), predators, releases, supplementary feeding, and hunting in limiting or promoting the distribution and range expansion of the species. We review hunting management and other regulations that may affect further northward expansion. Information on wild boar expansion and distribution was collated from available scientific publications, official statistics, volunteer reports, and expert knowledge. The effects of natural factors (climate harshness, habitat variation, predators) and anthropogenic factors (climate warming, habitat change, releases, supplementary feeding, hunting) on wild boar distribution were assessed using estimates (scores) provided by experts from the target regions. The wild boar in Europe is distributed up to 64°N. In Asia, the northern distributional limit is up to 61°N. The species' northern distributional limit is further north in the west than in the east of the geographic range. Experts regarded climate harshness, habitat, and hunting as the most important factors limiting wild boar distribution. Important factors that promote the expansion of the wild boar's range include climate warming and supplementary feeding. Our analysis of the official approaches to wild boar management suggests that the northern Eurasian countries do not have a united approach to the challenge of wild boar expansion. Collaboration between managers, policymakers, and researchers is needed for monitoring the wild boar distribution and range expansion throughout northern Eurasia. This data collection is especially important now, as parts of Europe and Asia are facing the challenge of African swine fever as well as other human–wildlife conflicts related to increasing wild boar populations.

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Section: Factors Limiting or Promoting Wild Boar Range Expansion In N...mentioning

confidence: 99%

The wild boar Sus scrofa in northern Eurasia: a review of range expansion history, current distribution, factors affecting the northern distributional limit, and management strategies

Markov

Economov²,

Hjeljord

et al. 2022

Mammal Review

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“…To model the ecological process, we considered explanatory variables describing climate, land cover, topography, and human disturbance as in previous ENETWILD reports (Table 1). Prior to model fitting we used a principal component analysis, rearranging this set of variables to minimise co-correlation, and applied a scaled average-eigenvalue test (Kaiser 1960) to remove any redundancy (ENETWILD consortium et al, 2019b). For the observation process we only considered a constant to reflect that the number of trials was derived from other presence records whose detectability within any given cell was likely to be similarly affected by the environmental condition, therefore detectability was represented in relative terms compared to that of other species .…”

Section: Models Based On Occurrence Datamentioning

confidence: 99%

“…As in previous reports (ENETWILD consortium et al, 2019b;2021), we estimated survey effort using a target group approach (Phillips et al, 2009), aggregating sightings across multiple species considered "similar" to the focal species which we wanted to model. In this case we defined target groups based on most common recording method (Ranc et al, 2017): large terrestrial mammals (visual); small terrestrial mammals (trapping); bats (acoustic); and, riverine.…”

Section: Wild Ruminant Occurrence Datamentioning

confidence: 99%

Update of model for wild ruminant abundance based on occurrence and first models based on hunting yield at European scale

Illanas¹,

Croft²,

Acevedo³

et al. 2022

EFS3

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The present document has been produced and adopted by the bodies identified above as authors. This task has been carried out exclusively by the authors in the context of a contract between the European Food Safety Authority and the authors, awarded following a tender procedure. The present document is published complying with the transparency principle to which the Authority is subject. It may not be considered as an output adopted by the Authority. The European Food Safety Authority reserves its rights, view and position as regards the issues addressed and the conclusions reached in the present document, without prejudice to the rights of the authors.

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“…According to previous reports (ENETWILD consortium et al 2018(ENETWILD consortium et al , 2019b we selected environmental variables closely related to wild boar distribution describing topography, climate, land cover and human density (Table 1). The present document has been produced and adopted by the bodies identified above as authors.…”

Section: Environmental Variables and Other Predictorsmentioning

confidence: 99%

“…Figure 5: Hunting yield (HY) predicted at 10x10 km EEA grid from the previous report (ENETWILD consortium et al, 2019 -A), from the smooth bioregion modelling approach (B) and from the two-step individual bioregion modelling approach (C). Grid cells were assumed as municipalities(ENETWILD consortium et al, 2019b). Red squares are beyond the environmental domain of the model according to MESS analyses.…”

mentioning

confidence: 99%

Update of occurrence and hunting yield‐based data models for wild boar at European scale: new approach to handle the bioregion effect

Acevedo¹,

Croft²,

Smith³

et al. 2020

EFS3

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The ENETWILD consortium updated in August 2019 suitability maps of wild boar occurrence and relative abundance based on hunting statistics, providing predictions at 10x10 km. External validation of this relative abundance model and a new downscaling on a 2x2 km grid was addressed in the ENETWILD report in January 2020. In this report, we update and incorporate additional data to provide new maps of wild boar suitability with a resolution of 2x2 km, obtained from a presence‐only algorithm, and a new model based on hunting yield data for MS and neighbouring countries. Hunting yield‐based modelling provides further novelties in two ways: new predictor variables and new (two) modelling approaches, i.e. smooth bioregion modelling and two‐step independent bioregion modelling). Internal validations and comparisons among previous and new suitability and hunting yield models were also addressed, as well as external evaluation of the best new approach at European scale (at country level). The suitability map showed a good agreement with the expert‐derived species range published by the International Union for Conservation of Nature. New models of relative abundance performed in general better than the previous one according to internal validations, concretely the two‐step independent bioregion approach gives the best validation scores. This approach solved the abrupt changes in predictions between bioregion boundaries. As with the previous model, the external evaluation of the new model based on hunting yield presented certain over‐prediction of the total hunting bags reported per country, although a high linearity between observed and predicted values was achieved. Previous and new hunting yield model predictions showed disagreements particularly in North and East regions, and other scattered areas in South and West, being areas in which the new model provides more reliable predictions. Hunting yield model outputs showed a relevant improvement in smoothing transitions between bioregions due to the flexibility provided by the new approach. Our analysis showed only partial agreement between suitability and relative abundance models, and reasons for these differences are discussed in this report.

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Wild boar in focus: initial model outputs of wild boar distribution based on occurrence data and identification of priority areas for data collection

Cited by 7 publications

References 19 publications

The wild boar Sus scrofa in northern Eurasia: a review of range expansion history, current distribution, factors affecting the northern distributional limit, and management strategies

The wild boar Sus scrofa in northern Eurasia: a review of range expansion history, current distribution, factors affecting the northern distributional limit, and management strategies

Update of model for wild ruminant abundance based on occurrence and first models based on hunting yield at European scale

Update of occurrence and hunting yield‐based data models for wild boar at European scale: new approach to handle the bioregion effect

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