Skip to main content

Predicting the outcomes of management strategies for controlling invasive river fishes using individual-based models.

Dominguez Almela, V., Palmer, S., Andreou, D., Gillingham, P., Travis, J.M.J. and Britton, J.R., 2021. Predicting the outcomes of management strategies for controlling invasive river fishes using individual-based models. Journal of Applied Ecology, 58 (11), 2427-2440.

Full text available as:

Journal of Applied Ecology - 2021 - Dominguez Almela - Predicting.pdf - Published Version
Available under License Creative Commons Attribution.

1365-2664.13981.pdf - Accepted Version
Restricted to Repository staff only

[img] PDF
Accepted_Dominguez Almela et al. J Appl Ecol.pdf - Accepted Version
Restricted to Repository staff only
Available under License Creative Commons Attribution Non-commercial.


DOI: 10.1111/1365-2664.13981


1. The effects of biological invasions on native biodiversity have resulted in a range of policy and management initiatives to minimise their impacts. Although management options for invasive species include eradication and population control, empirical knowledge is limited on how different management strategies affect invasion outcomes. 2. An individual based model (IBM) was developed to predict how different removal (‘culling’) strategies affected the abundance and spatial distribution of a virtual, small-bodied, r-selected alien fish (based on bitterling, Rhodeus sericeus) across three types of virtual river catchments (low/intermediate/high branching tributary configurations). It was then applied to nine virtual species of varying life history traits (r- to K-selected) and dispersal abilities (slow/intermediate/fast) to identify trade-offs between the management effort applied in the strategies (as culling rate and the number of patches it was applied to) and their predicted effects. It was also applied to a real-world example, bitterling in the River Great Ouse, England. 3. The IBM predicted that removal efforts were more effective when applied to recently colonized patches. Increasing the cull rate (proportion of individuals removed per patch), and its spatial extent was effective at controlling the invasive population; when both were relatively high, population eradication was predicted. 4. The characteristics of the nine virtual species were the main source of variation in their predicted abundance and spatial distribution. No species were eradicated at cull rates below 70%. Eradication at higher cull rates depended on dispersal ability; slow dispersers required lower rates than fast dispersers, and the latter rapidly re-colonised at low cull rates. Optimum trade-offs between management effort and invasion outcomes were generally when intermediate effort was applied to intermediate numbers of patches. In the Great Ouse, model predictions were that management interventions could restrict bitterling distribution by 2045 to 21% of the catchment (versus 90% occupancy without management). 5. Synthesis and application: This IBM predicted how management efforts can be optimized against invasive fishes, providing a strong complement to risk assessments. We demonstrated that for a range of species’ characteristics, culling can control and even eradicate invasive fish, but only if consistent and relatively high effort is applied.

Item Type:Article
Additional Information:Research Funding Natural Environment Research Council. Grant Number: NE/R008817/1; Environment Agency; Newton Fund. Grant Number: NE/S011641/1
Uncontrolled Keywords:Biological invasion; RangeShifter; River catchment,; Simulation model; Dispersal
Group:Faculty of Science & Technology
ID Code:35821
Deposited By: Symplectic RT2
Deposited On:23 Jul 2021 09:54
Last Modified:14 Mar 2022 14:28


Downloads per month over past year

More statistics for this item...
Repository Staff Only -