Predicting future invasion impacts: Indicators and models to measure success in “bending the curve” of species accumulation.


Biodiversity decline is attributed to multiple anthropogenic threats and pressures, including the impacts of invasive species [1]. Given there is no evidence that species invasions are slowing [2], the impacts of invasions are predicted to increase without management [3]. Successful protection of biodiversity requires measures to mitigate the threat of impacts that species invasions pose. Emerging invasive species are best managed by preventative actions including biosecurity and pathway management and eradication measures (e.g. Asian Hornet). Established invasive species are typically managed by impact mitigation, containment or control measures (e.g. American mink) and in some cases complete removal (e.g. Ruddy Duck).

Removal of known impacts and the restoration of ecosystems can be easier to evaluate than assessing the potential impacts avoided by preventative measures. For example, it was possible to attribute the conservation success of avoiding species extinctions to removal of established invasive species [4] but there is little evidence to help inform the benefits of taking preventative action. From the decision makers perspective, the value of taking preventative action must outweigh the potential long-term impacts of inaction. Full assessment of the success of abatement measures requires prediction of the scale of impact that would have occurred without management action. Making informed decisions about the most appropriate management action to abate future impacts needs nuanced justification through demonstration of biodiversity benefits in terms of impacts avoided on ecosystem function. Predictive modelling approaches are needed to assess how preventative management action results in “bending the curve” of invasive species accumulations and a resultant reduction in ecosystem impacts.

Horizon scanning through expert elicitation has identified the most likely invaders into Europe, potential pathways of arrival and spread and potential preventative or control actions to minimise impact [5]. Yet to model future spread and impacts avoided on ecosystem functions, specific points of incursion in time and space need to be predicted. Climatic and habitat models can combine known species-environment relationships and behaviours such as dispersal to predict likely spread and area of impact in the invaded region. Our understanding of changes in species impacts in time and space is limited but can be incorporated into models to improve our knowledge of how the trajectory of both species accumulation rates and scale of impacts can be changed through management.

This research has three main aims to improve our knowledge of the link between future species invasions and potential environmental impact mitigation.

1. Assess evidence for INNS impacts on threatened native species and their associated ecosystem functions.
2. Develop predictive models of species likely entry and spread for a range of taxa to be used as a framework for further species assessments, incorporating natural and human mediated dispersal processes.
3. Develop species and taxa level indicators for abatement through different preventative and control actions, including area based, speed of spread and impacts avoided on ecosystem functions.

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This project will access extensive datasets on horizon scanning, risk assessment, impact assessment and risk management developed and maintained by UKCEH, GB Non-native species secretariat (GBNNSS) and Newcastle University. The student will conduct a systematic review of scientific and grey literature to identify all known impacts of invasive species on native species under threat as well on the ecosystem functions provided by the impacted native species.
The findings will be used to assess impact (using the IUCN standard EICAT protocol) and compare with an assessment of invasive species impacts previously conducted using expert elicitation. This review will also allow us to develop metrics of invasive species impact that consider impacts on biodiversity and ecosystem function independently of likely spatial extent of spread.

Species from a range of taxa on horizon scan lists will be selected to parametrise and construct models of future incursion and spread accounting for natural and human-mediated dispersal processes (e.g. trade, tourism and recreation). The student will access data from the GB non-native information portal to develop models, potential model types include spatial occupancy modelling, spatially explicit process based models and least cost paths depending on the species and taxa chosen.

The student will develop novel strategies for integrating impact into the predictive models, through incorporation of geographically variation in the distributions of native species and ecosystem functions (NBN data, Pollinator monitoring network data). To further understanding of the magnitude of impacts avoided through preventative and control actions, the student will integrate spatially and temporally varying abatement measures (from DEFRA and EC policies) into the models to predict changes in spatial extent and impacts on native species and ecosystem functions following abatement. Combining these species-specific models across taxa, will enable abatement indicators of species accumulation to be refined to add insights on ecosystem impacts.
Throughout the project the student will be in regular communication with GB NNSS to gain experience on the policy drivers for the research. In addition the student will spend some focussed time working with GBNNSS to learn about different types of abatement and the species and geographies to which these are applied. This will either be as a single 3-month placement or as a series of short-term mission/ projects in each year on an agreed topic/species/taxa of interest.

Project Timeline

Year 1

The focus in year 1 will be to fully assess the literature to build on previous expert elicitation of invasive impacts providing a comprehensive review and evidence for species impacts on native species and ecosystem functions, accounting for impact type as well as spatial scale of potential spread. The student will be trained in species distribution and occupancy modelling methods. The student will spend time engaging with DEFRA policy to better understand the modelling needs.

Year 2

In year 2 the research will focus on developing a framework for assessing likely points of incursion and routes of spread and associated impacts of a range of taxa.

Year 3

In year 3 and 4 the student will work on integrating abatement into spread and impact models and integrating species-specific models outputs into taxa level indicators of effectiveness of abatement policy. This will be informed by a policy workshop (with representatives of EC and UK IAS experts, IUCN and DEFRA) in which the student will present model outputs to participants and gain feedback on how to shape the frameworks to inform policy.

Year 3.5


& Skills

The student will be trained in the Modelling, Evidence and Policy group at Newcastle University. This is a collaborative research environment where the student will be supported in developing their skillset as a researcher for the needs of the project. Skills include data management, reproducible workflows and version control, modelling for large datasets, scientific writing and evidence synthesis. The supervisory teams at Newcastle, UKCEH and policy expertise of GBNNSS offer complementary expertise on invasive species research, science, policy and management and modelling. Regular visits to UKCEH will allow the student to learn occupancy and spread modelling. Additional specific training needs will be met through taught courses in spatial mixed model in INLA (e.g. PR statistics) and through postgraduate taught modules at Newcastle (e.g. remote sensing, meta-analysis). The student is encouraged to apply to be a fellow of the Newcastle Policy Academy for training in local and national policy environments and engagement. Engagement throughout the 3.5 years with the GBNNSS will allow the student to build relationships with relevant policy experts (e.g DEFRA, IUCN and EU).

References & further reading

[1] IPBES (2019) Global assessment report

[2] Essl, et al (2020) Global Change Biology

[3] Seebens, et al (2017) Nature communications

[4] Bolam et al (2020) Conservation Letters

[5] Roy et al (2018) Global Change Biology

Further Information

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