Clown fish

The role of life histories and population age structure in the invasion success of alien freshwater fish

Funding:

Funded PhD

Duration:

3.5 years

Application deadline:

Monday 7 January 2019

About this project

Alien species, those introduced outside their native range, can cause huge ecological and economic damage. With increasing global trade, the number of new alien species is growing rapidly, and identifying which ones will be future invaders is an urgent global challenge. However, with no history of invasion, it is hard to predict which new alien species will establish and which ones will go naturally extinct.

One solution is to identify what has promoted the establishment of species introduced in the past, and use this knowledge to predict the probability of success of potential future invaders. To this end, we need to address fundamental questions in basic and applied science.

Alien populations typically start small and differ greatly in age structure from natural, stable populations, being often biased towards one age class. Recent demographic models propose that a population’s age structure affects its response to natural disturbance and long-term persistence through transient population dynamics, but does so differently depending on the species’ life history. Thus, the probability of establishment in alien populations should be strongly influenced by their age structure. This emerging idea is potentially key to explain the great variation in the establishment success of alien populations but has yet to be tested.

This project will investigate how the age structure and size of alien founder populations interact with species life histories and determine the population’s growth trajectory and probability of establishment, in freshwater fish.

Since biological invasions have an important human dimension, next we need to identify the pathways of fish introduction into novel ranges and the species at risk of future release, for which to make statistically informed predictions of invasion potential based on their life histories and across a range of possible founder population size and age structure.

Freshwater fish are among the most frequently introduced vertebrates. Many established fish populations have major detrimental impacts on native biodiversity and ecosystem services of the most vulnerable Earth ecosystems – freshwater habitats.

To date, over 500 freshwater fish species have been successfully introduced into non-native regions all over the world, some intentionally (e.g. for commercial fishery or angling), others unintentionally (e.g. through the pet trade). Many historical fish introductions are well recorded, including those that failed, and offer the opportunity to identify the drivers of invasion success in freshwater fish.

Unlike for terrestrial vertebrates, however, we know surprisingly little about what makes some alien freshwater fish more likely to establish in novel regions than others, which is essential if we are to predict the potential for invasion of new alien fish species and mitigate impact on vulnerable freshwater habitats.

Objectives

This project will

  • build the largest, global scale database ever assembled of freshwater fish introductions, introduction pathways, and species life histories;
  • test how species life histories, founder population’s age structure and size, interact and determine successful establishment in alien freshwater fish populations;
  • quantify how different introduction pathways influence the probability of release in novel regions and identify the species at high risk of future release;
  • derive statistically informed predictions of introduction and establishment success for freshwater fish species at risk of being released outside their native range, by combining outputs from objectives (2) and (3).

The project combines cutting edge phylogenetic comparative approaches with novel theoretical models of population dynamics. This research builds on recent publications on terrestrial vertebrates’ invasion success led by the Lead Supervisor and supervisory team members (Capellini et al 2015 Ecology Letters; Allen et al 2017 Ecology Letters; Sol et al 2012 Science).

Training

The student on this timely project will receive training in data collection and management to assemble the database, and in cutting edge statistical methods in Bayesian framework in R and mathematical models of population dynamics to analyse the data using the University of Hull’s High Performance Computer VIPER. The student will have the opportunity to engage with stakeholders through a 3 months placement at Yorkshire Water.

Research Environment

The student will join Dr Capellini’s group in Evolutionary Comparative Ecology (UoHull), which addresses an array of fundamental questions in ecology, and work in a dynamic and diverse research environment within the Institute of Energy and Environment, the Ecology Research Group, and the Hull International Fisheries Institute.

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Funding

This project is funded by Panorama NERC Doctoral Training Partnership (DTP). They are offering a fully funded 3.5 year studentship (stipend + fees) to both UK and EU applicants at the standard UKRI rate.

We are unable to offer studentships to non-EU international candidates.

Entry requirements

The prospective student should have, or expect to receive, a first class BSc degree, or a distinction at Masters level, in an appropriate discipline.