Skip to content
#data science Open access

Invasive species: fundamental and applied science

Oct 2026 · Research Portal (Queen's University Belfast)

Abstract

Management of invasive alien species (IAS) is notoriously difficult, with many examples of expensive, failed attempts. While there is growing consensus that prevention is better than cure, successful prevention requires user-friendly, effective methods to quantify the ecological impacts of established, emerging and future IAS. In this thesis I develop one such method: the Relative Impact Potential (RIP) metric. Based on the effective Comparative Functional Response method, which highlights damaging IAS by comparing their greater per capita maximum feeding rates relative to trophically analogous natives, it enhances prediction by accounting for proxies of numerical response, such as abundance. It therefore captures the impacts of abundant invaders with low per capita effects alongside low numbers of invaders with high per capita effects, while still maintaining the benefits of the CFR method, such as the ability to incorporate a wealth of biotic and abiotic context dependencies and ease of interpretation. In Chapter 1, I outline the history of the metric and develop it further, outlining a roadmap for future use. Some of these aspects I go on to implement across the different data chapters. In Chapter 2, I use RIP to experimentally assess how sea freshening may affect the impacts of the emerging amphipod IAS, Pontogammarus maeoticus, relative to an established IAS, Gammarus tigrinus, and a trophically analogous native, Gammarus salinus, in the Baltic Sea. I show that this often-overlooked aspect of climate change enhanced the relative impacts of both IAS. In the third chapter, I continue with the abiotic context of Baltic Sea freshening, but here assess the consequences of decreasing salinity on the ecological impact exerted by a native keystone predatory starfish, Asterias rubens, at the limits of its range. Using three experimental salinities, I combine FRs with larval recruitment estimates and show that attack and maximum feeding rates of the starfish are reduced by decreasing salinities, with no instances of predation found at the low salinity. With similar patterns for larval recruitment, the overall Impact Potential of this keystone predator species was lessened by decreased salinity, with potential implications for Baltic community structure. Chapter 4 assesses the role of oxygen saturation on the impact of the predatory invasive fish, the Ponto-Caspian round goby (Neogobius melanostomus), relative to a native endangered analogue, the bullhead (Cottus gobio). Across three oxygen saturation levels, I assess impact using FR, RIP and a new metric called the Relative Total Impact Potential that assesses combined IAS and native impact upon a system across invasion stages. At low saturation, the IAS was shown to have a significantly higher feeding rate relative to the native, RIP revealed that low oxygen exacerbated the high relative impact of the invader, and RTIP was consistently higher at low oxygen. In Chapter 5, I assess the impacts and risks of four commonly traded pet turtles – Trachemys scripta scripta, T. s. troostii, Sternotherus odoratus, Kinosternon subrubrum – using Relative Invasion Risk, an adapted version of RIP that incorporates propagule pressure. T. s. scripta was found to have high impact, corroborating its now banned status in the EU, but still a high risk. In Chapter 6, I assess the potential impacts of two readily available fish species in the pet trade: Tanichthys albonubes and Carassius auratus. Again, I assess impact and risk, but this time incorporate “dispersal enhancing” behaviour measures. C. auratus, the species with the greater invasion history, is shown to be high impact and high risk. While the experiments performed and conclusions drawn vary across the different chapters of this thesis, overall this work highlights the efficacy and flexibility of the RIP family of metrics in answering a wealth of ecological questions, across numerous abiotic contexts and taxa. Finally, in Chapter 7, I call for its enhanced use in IAS risk assessments.

View source

Similar papers

#computer vision Review Sep 2017

Agile Software Development Methods: Review and Analysis

This publication proposes a definition and a classification of agile software development approaches and analyses ten software development methods that can be characterized as being "agile" against the defined criterion.

P. Abrahamsson, O. Salo, Jussi Ronkainen et al. · 727 citations · ⚡54
#computer vision Jun 2008

The impact of agile practices on communication in software development

The study shows that agile practices improve both informal and formal communication, but indicates that, in larger development situations involving multiple external stakeholders, a mismatch of adequate communication mechanisms can sometimes even hinder the communication.

M. Pikkarainen, Jukka Haikara, O. Salo et al. · 401 citations · ⚡48
#machine learning Review Open access Oct 2014

Software development in startup companies: A systematic mapping study

The results indicate that software engineering work practices are chosen opportunistically, adapted and configured to provide value under the constrains imposed by the startup context.

Nicolò Paternoster, Carmine Giardino, M. Unterkalmsteiner et al. · 394 citations · ⚡54

Trajectory Balance: Improved Credit Assignment in GFlowNets

It is proved that any global minimizer of the trajectory balance objective can define a policy that samples exactly from the target distribution, and empirically demonstrate the benefits of the trajectories balance objective for GFlowNet convergence, diversity of generated samples, and robustness to long action sequenc...

Esmeralda S. Whitammer, Moksh Jain, Emmanuel Bengio et al. · 302 citations · ⚡60

Related blog posts

Microsoft Research Blog Oct 6, 2026

What AI gets wrong and what failure teaches us

Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity.  The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.