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Identifying and prioritising conflicts between human and wildlife interests in Great Britain

Palphramand, K. L.; Cowan, D.; Warren, D. A.; Smith, G. C.

2025-07-05 ecology
10.1101/2025.07.02.662702 bioRxiv
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O_LIA literature review was conducted to identify human-wildlife conflicts associated with British terrestrial mammal species. Conflicts were classified as economic, health, environmental or social, divided into 32 subcategories, and ranked using a Generic Impact Scoring System (GISS). C_LIO_LIWe identified 48 species associated with 200 conflicts. Sika deer were involved in the most conflicts. The highest ranked conflicts were measurable on an economic scale (involving rabbits, badgers, brown rats, grey squirrels), with the total estimated cost of all economic conflicts exceeding {pound}0.5 billion. C_LIO_LIThe most common conflicts were reservoirs of disease and zoonotic disease, with non-native species scoring statistically higher than native species for the latter. Generally, we scored these conflicts low, deemed localised and mild, but highlighted the importance of surveillance to monitor and control disease spread. C_LIO_LIMost species caused minimal conflict, likely due to their limited distribution. We identified potential impact increased as a function of biomass and population size, therefore a GISS may help identify species capable of expanding beyond their current range, such as recently reintroduced beavers. C_LIO_LIA GISS is useful for identifying conflict species but there is also the need to understand the value of British wildlife. We identified costs-to-benefits trade-offs for several high impact species, including rabbits, deer, badgers and foxes, which underlie human-conflict and/or coexistence and are critical for informed decision-making. As one in four British mammal species face local extinction, the emphasis should encourage focus away from conflict resolution to acceptance and/or tolerance where wildlife and people coexist. C_LI

Published in Mammal Review · not in our set (fewer than 10 published preprints to learn from) · training set

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