NIAB EMR: J.V. Cross
University of Reading: J. Bishop, R. Walters & R. Girling
There is growing consensus that improving the sustainability of future food production will require an integrated approach that profits from beneficial species interactions such as natural pest regulation. A key threat of projected climate change to ecosystems is the disruption of species interactions. Disruptions are predicted to occur as a consequence of species different responses to temperature and temperature variability. This can arise from differences between species in 1) thermal optima, 2) thermal specialisation, and/or 3) heat stress response. The disruption of complex species interactions such as the natural regulation of herbivorous insects, is problematic. Parasitic wasps in apple orchards, for example, can control the growth of aphid populations at low temperatures, but often fail to do so during and/or following periods of higher temperature. Aphid pests can then become detrimental to both apple yield and quality. This can force agricultural practitioners to resort to the use of chemical pesticides.
In this project, the student will use technically demanding controlled environment experiments and ecological fieldwork to study the temperature responses of a complex species interaction that is tri-trophic, incorporating apple trees, aphids, and a parasitoid wasp. A key novel aspect will be to consider how this interaction is affected by short-term temperature perturbations, in addition to gradual changes in temperature. By using experimental observations of the tri-trophic system to parameterise mathematical models, and long term datasets to validate them, key insights revealed into how projected climate change will impact ecosystem service provision and sustainable food production can be applied to this and to other systems.
- Experimentally determine the role of species interactions by quantifying thermal responses for each species of an important tri-trophic system (apple saplings, an apple aphid pest, and a parasitoid wasp) in isolation vs. in species combinations.
- Explore the theoretical consequences of asynchronous responses to temperature under different species interactions and verify these predictions with data from both the laboratory and a large-scale field experiment.
- Develop a process-based model to simulate pest regulation by natural enemies under different i) weather (short-term, e.g. heat waves) and ii) climate change (long-term) scenarios and validate these models against field observations.
- Develop a decision support tool to communicate findings to agricultural practitioners.
Approaches and work packages
The student will utilize laboratory microcosms in controlled environments and a large scale field experiment, to quantify how population growth rates of an aphid pest of apple, and its natural enemies are affected by temperature per-se and by perturbations in temperature. This approach allows predator-prey dynamics to emerge as a by-product of species-specific thermal physiology, providing a means to disentangle species interactions in a changing environment. The student will conduct a literature review and initial experimentation to determine suitable species for study, but based on economic importance and culturing feasibility we envisage the model organisms will be woolly Aphid (Eriosoma lanigerum) and Aphelinus mali. The student may perform additional work with a generalist parasitoid wasp species, and a generalist predator, the Common Earwig.
WP1. Theoretical exploration of changing predator-prey dynamics with temperature
Potential consequences of asynchrony in species response to temperature will be explored using the mathematical model of Maynard-Smith and Slatkin under different density-dependent scenarios. These initial results will inform the experimental design (WP2) and a more complex process-based model including detailed species life-histories (WP4).
WP2. Empirical laboratory study to determine the thermal responses of the host plant, aphid, and natural enemies
Laboratory common-garden experiments on selected species identified in the field experiment (WP3) will determine the consequences of temperature and different levels of temperature variability on species in isolation and species interactions.
WP3. Field observations of a large-scale climate change experiment to validate theoretical and laboratory findings
The experiment is based at the National Fruit Collection, Kent, and has treatments modifying temperature and rainfall. The student will conduct passive sampling to determine, e.g. how predation/parasitism changes in response to the different treatments.
WP4. Development and application of a process-based model
A process-based model tailored to species life-histories will be developed and used to simulate the consequences of primarily short-term variation (e.g. heat waves days to weeks in length) and also long-term climate changes (e.g. IPCC scenarios for 2050). These results will be used as the basis of a decision-making tool.
Three research papers are expected: (i) contrasting the thermal optima of species in a tri-trophic interaction, (ii) a weather-dependent model of pest growth rate and control by natural enemies; (iii) projected impacts of increasingly variable weather on the efficacy of natural pest control in apple orchards.
The student will engage in both innovative laboratory studies and field sampling developing a wide range of fieldwork skills in, for example, invertebrate taxonomy. The project will facilitate engagement with relevant stakeholders in the food supply industry (e.g. through work at the industrial standard climate change experiment) and directly translates research into practice by building predicative bio-climatic models to improve crop management by agricultural practitioners.
The student will learn programming skills in open-source languages through using R and NetLogo for statistical analysis and mathematical modelling, and master statistical, mathematical and analytical skills through the development of a sampling protocol, and the manipulation and analysis of varied and complex data sets (e.g. experimental and in-situ observations, long term datasets, climate change projections).