Periodic Reporting for period 2 - MechAnt (Behavioural biomechanics of insect herbivory - a case study on leaf-cutter ants)
Reporting period: 2021-07-01 to 2022-12-31
Insect herbivores are almost everywhere, and have substantial impact on the structure and diversity of plant and soil invertebrate communities, habitat health, the success of exotic plant invaders, and crop yield; they consume a significant fraction of crops grown for human consumption, and may threaten global food security. Surprisingly little is known about a key determinant of herbivore success: All herbivory must at some point involve a mechanical interaction between the relevant insect mouthpart and the food source in question; if the insects cannot drill, pierce or cut into the plant, they cannot feed on it. In this project, we study the fundamental biomechanics of plant-feeding in insects, using the major ecosystem engineers and principal insect pest of the New World, the leaf-cutter ants, as a model system.
Using a multi-scale approach ranging from nanoscale-mechanics to colony-level ecology, we hope to: (i) provide quantitative insights into the rules governing the social organisation of leaf-cutter ant colonies, showcasing how biomechanics can provide a powerful framework to render complex behavioural questions tractable; (ii) link the mechanical properties of plants and mandible morphology with feeding performance, and hence develop predictive tools to study plant-herbivore interactions; (iii) identify the mechanical properties of plants which cause mandibular wear, gaining insights relevant for insect pest management; (iv) develop and use a novel method to study wear resistance on small scales, paving the way for comparative follow-up studies across biological materials; and (v) deploy computer vision and machine learning to behaviour of social insects, generating a versatile tool for future research.
Using a multi-scale approach ranging from nanoscale-mechanics to colony-level ecology, we hope to: (i) provide quantitative insights into the rules governing the social organisation of leaf-cutter ant colonies, showcasing how biomechanics can provide a powerful framework to render complex behavioural questions tractable; (ii) link the mechanical properties of plants and mandible morphology with feeding performance, and hence develop predictive tools to study plant-herbivore interactions; (iii) identify the mechanical properties of plants which cause mandibular wear, gaining insights relevant for insect pest management; (iv) develop and use a novel method to study wear resistance on small scales, paving the way for comparative follow-up studies across biological materials; and (v) deploy computer vision and machine learning to behaviour of social insects, generating a versatile tool for future research.
Because the ability to mechanically process plant material is fundamental to all herbivory, our first aim was to understand how both the morphology and physiology of the biting-chewing apparatus of insects interact with the mechanical and structural properties of the plant to determine feeding performance. To this end, we developed experimental tools to directly quantify (i) the 3D architecture of the muscles responsible for force generation during feeding; (ii) the maximum bite forces insects can generate at different mandible opening angles; (iii) the forces required to cut through leaf-like sheets; (iv) and how this force varied with the size and wear state of the mouthpart used for cutting. Our experiments demonstrate that leaf-cutter ants are extraordinarily specialised to generate large bite forces; the size-specific force they generate is the highest ever recorded. This specialisation is manifested in several remarkable adaptations, such as an indirect attachment of muscle fibres to the mandible tendon in order to optimise volume occupancy of muscle in the head capsule, or changes in head capsule shape with size to accommodate a disproportionate increase in the amount of muscle. It also brings with it ecological advantages: leaf-cutter ants can forage on the fast majority of tropical plant leaves without having hefty investment into extremely large workers. Our methodological approaches and biomechanical modelling of the bite performance is general, and can be used to assess head functional morphology and bite performance across the insect tree of life.
Because we are ultimately interested in understanding how the mechanical aspects of plant feeding may influence behaviour and evolution, we also worked on tools which enable us to analyse behaviour in various experimental conditions and with large numbers of individuals. For example, we are interested in how ant colonies “assign” workers of different sizes to forage on food sources of different mechanical properties. Traditionally, addressing such a question would involve tedious and time consuming manual labour – individual ant workers are extracted from foraging sites and weighed by hand. To overcome the limitations and potential for bias associated with this approach, we made use of recent advances in computer vision and machine learning, and taught a computer to perform these tasks for us: We designed and built a photogrammetry platform to generate photorealistic 3D models of insects, and then placed these models into various environments, using engines developed for computer games. By generating tens of thousands of these images, and associating with them relevant information on the number, position and size of the imaged animals, we taught deep neural networks to detect, track and size-estimate ants, so enabling us to collect large amounts of data on ant foraging behaviour.
Because we are ultimately interested in understanding how the mechanical aspects of plant feeding may influence behaviour and evolution, we also worked on tools which enable us to analyse behaviour in various experimental conditions and with large numbers of individuals. For example, we are interested in how ant colonies “assign” workers of different sizes to forage on food sources of different mechanical properties. Traditionally, addressing such a question would involve tedious and time consuming manual labour – individual ant workers are extracted from foraging sites and weighed by hand. To overcome the limitations and potential for bias associated with this approach, we made use of recent advances in computer vision and machine learning, and taught a computer to perform these tasks for us: We designed and built a photogrammetry platform to generate photorealistic 3D models of insects, and then placed these models into various environments, using engines developed for computer games. By generating tens of thousands of these images, and associating with them relevant information on the number, position and size of the imaged animals, we taught deep neural networks to detect, track and size-estimate ants, so enabling us to collect large amounts of data on ant foraging behaviour.
Plant feeding requires to apply a force. This force is generated by muscle, in a process which consumes metabolic energy. How much energy do insects have to invest to feed on plants, and how does this energy vary with insect size and plant mechanical properties? To answer these questions, we will compare the mechanical and metabolic costs of cutting plant leaves. The ratio of both costs indicates the “efficiency” of the cutting process, i.e. how much metabolic energy is needed to generate a unit of mechanical energy. By studying how efficiency varies with worker size and plant mechanical properties, we will be able to determine the energetically optimal strategy for assigning workers of different sizes to forage on plant materials of different mechanical properties.
Next, we will turn our attention to the effects of continued “cutting” – do insect cutting tools wear just like human knives, and if so, how does it affect efficiency, how can plants maximise wear, and how can insects minimise it? We will address these questions by studying the wear resistance of mandibles both at very small and at macroscopic scales. We will quantify mandible wear state, and link it to knock-on effects on cutting performance and efficiency.
With this knowledge at hand, we will design experiments to test if ant colonies actually assign workers in a way which is consistent with the idea of an “ergonomic” organisation of their colonies. To this end, we will leverage the automated tracking, detection and size-estimation tools we have developed as part of this project, and quantify the “demography” of foraging parties as a function of the mechanical properties of the food source.
Through a combination of experimental and theoretical approaches from different scientific disciplines, our work will provide a comprehensive insight into the role of mechanical constraints on insect herbivore performance, behaviour and evolution.
Next, we will turn our attention to the effects of continued “cutting” – do insect cutting tools wear just like human knives, and if so, how does it affect efficiency, how can plants maximise wear, and how can insects minimise it? We will address these questions by studying the wear resistance of mandibles both at very small and at macroscopic scales. We will quantify mandible wear state, and link it to knock-on effects on cutting performance and efficiency.
With this knowledge at hand, we will design experiments to test if ant colonies actually assign workers in a way which is consistent with the idea of an “ergonomic” organisation of their colonies. To this end, we will leverage the automated tracking, detection and size-estimation tools we have developed as part of this project, and quantify the “demography” of foraging parties as a function of the mechanical properties of the food source.
Through a combination of experimental and theoretical approaches from different scientific disciplines, our work will provide a comprehensive insight into the role of mechanical constraints on insect herbivore performance, behaviour and evolution.