IAP-25-080

Integrating molecular dietary analysis, nutritional ecology and network inference to assess ecosystem service trade-offs in omnivorous beetles

This project will use dietary DNA metabarcoding, micro-scale nutritional analysis, ecological field surveys and cutting-edge network inference and analysis methods to enhance our ability to predict the trophic interactions and ecosystem services of omnivorous ground beetles.

Understanding how ecological interactions underpin ecosystem structure and functioning is central to understanding environmental resilience under global change. Interactions are difficult to predict though, given the many resources available, and the way in which these interactions dynamically change over space and time. As our ecosystems are impacted by global change, it is even more important that we can predict these interactions to mitigate potential impacts to ecosystem stability. This is also crucial for understanding and optimising the provision of ecosystem services, which determine the benefits we gain from these interactions, such as predation of crop pests or, conversely, herbivory of crops.

Ecological networks are a valuable means for investigating interactions across whole communities or ecosystems to understand their function and stability, and how interactions change across space and time. This can be particularly crucial for understanding the impact of disturbances like global change on interactions and their outcomes, such as ecosystem services. Constructing these networks can, however, be time-consuming and challenging, so finding streamlined ways to do so is paramount if we are to use networks to assess these impacts. Inferring interactions involves logically linking consumers and resources in a way that should resemble the interactions actually occurring. This is particularly important for difficult-to-observe systems such as the interactions between invertebrate consumers and their resources.

Many ground beetles (Carabidae) are highly abundant generalist omnivores, although some specialise on invertebrate prey or seeds. Given that they regularly consume weed seeds and crop pests, they are thought to be highly beneficial for agricultural productivity, but they can also consume beneficial invertebrates, such as other predators of crop pests, and they may also consume crop seeds. To advance our ability to infer interactions between invertebrate consumers and their resources, we first need to compare our inferences with known interactions. The trophic interactions of invertebrate omnivores are, however, difficult to observe. Molecular dietary analysis (e.g., DNA metabarcoding) can circumvent this though by allowing reconstruction of dietary interactions long after they have occurred.

Using interaction and resource availability data, we can also begin to investigate the preferences of invertebrate consumers in the field by comparing their interactions with what we would expect them to interact with if foraging randomly. Understanding these preferences can help to refine network inference by defining likely preferential links between consumers and their resources. Such preferences are likely driven by the fundamental currency of trophic interactions: nutrients. By integrating nutritional data into these ecological networks, we may be able to enhance our ability to infer interactions greatly.

This project will use existing ground beetle-seed interaction data to test network inference models, and then apply these to data generated from the field using dietary metabarcoding, nutritional analysis and null network modelling. These data will guide enhancement of inference models to improve our ability to predict interactions for the management of ecosystem services provided by ground beetles and other consumers. This project will also generate crucial and novel insights into the foraging ecology and nutrition of generalist invertebrate omnivores beyond the reach of previous studies in this field.

The successful student will analyse an existing dataset of ground beetle-seed interactions and apply different network inference methods to determine their comparative accuracy in predicting the recorded interactions of these beetles through comparison with existing interaction data. Beetle and seed trait data will be used to refine inferences and assess the importance of traits in determining the accuracy of inference, and, simultaneously, the identity and ecosystem service implications of interactions.

To test these inference methods further and integrate new interactions and context to the data, the student will build new empirical datasets. This will involve fieldwork at Newcastle University’s experimental farms. During fieldwork, ground beetles and the prey and seeds available to them will be collected from different crop types and adjacent semi-natural habitats across the site. Ground beetles will be identified and undergo dietary analysis in Newcastle University’s Molecular Diagnostics Facility using high-throughput robotics and cutting-edge diagnostics equipment. The gut contents of beetles will be analysed for both animal and plant DNA to determine their omnivorous diet. These interactions will be compared between taxa, habitats and across time to determine how these factors influence trophic network structure and ecosystem service provision.

The seeds and prey available to the beetles will be identified, and these data will then be used to generate null models of expected interactions. These will be compared to the actual interaction data to assess resource preferences of the beetles and how these change across space and time, and between species. Seed and prey nutrient contents (proteins, lipids, carbohydrates) will also be determined by colorimetric assays and compared between resource taxa and habitats. These will be used to construct ‘nutritional networks’ (see references) and determine how nutrients drive interactions and wider ecological network structure. The resource choice and nutrition results will be used in subsequent network inference using the interaction data generated in the project to refine predictions of interactions and build increasingly accurate models of network inference.

The successful student will collaborate with leading researchers across Newcastle University, UKCEH and INRAE, with excellent opportunities to gain skills and connections across these institutions and their communities. Access to cutting-edge equipment and facilities across these institutions will provide valuable skills, training and experiences for the project and beyond.

Year 1

• Settling in and inductions
• Reviewing the literature
• Using network inference approaches with existing beetle-seed interaction data
• Fieldwork

Year 2

• Morphological identification of invertebrates and seeds
• DNA metabarcoding of beetle gut contents
• Construction and analysis of trophic networks
• Assessment of ecosystem service provision trade-offs

Year 3

• Nutritional analysis of invertebrate prey and seeds
• Construction and analysis of nutritional networks
• Integrate nutritional data into network inference models
• Assess the nutrition as a driver of ecosystem services

Year 3.5

• Complete and refine analyses
• Explore wider implications and future steps for this work
• Complete writing of the thesis

The following skills will be developed throughout the project:
• Molecular dietary analysis
• Macronutrient analysis
• Network inference
• Null network modelling
• Ecological network analysis
• Scientific writing and publishing
• Open research
• Academic service