IAP-24-101

Disentangling the interactions between climate change and land-use change in a 3D world

There is now unequivocal evidence that land use and climate change cause biodiversity change. Changing biodiversity can have drastic impacts on ecosystems and the value we derive from nature including, not least, the provisioning of food. Yet, the need to feed people is precisely what drives most land-use change, and it is also responsible for a large proportion of global greenhouse gas emissions. Moreover, there is an increasing recognition that climate at ecologically relevant scales – ‘microclimate – is directly affected by both land-use and climate change, and that microclimate, in turn, likely mediates the response of ectotherms like insect pollinators. This project will disentangle the various interacting factors at play to better understand how feeding the human population impacts insect pollinators, and vice versa.

The project will be largely desk-based, utilising existing databases to identify spatially explicit responses of insect pollinators to land-use and climate change. We will expand on previous studies, including by external collaborator Dr Tim Newbold, through the integration of vegetation structure and microclimate data. This will involve a combination of remote sensing, microclimate modelling and potentially some fieldwork to validate model outputs.

Year 1

The first year will be used to build the basic database of insect pollinator species, their geographic locations, and responses to documented land-use and climate change. Most
data will be sourced from the PREDICTS project. The spread of data across different geographic regions and vegetation types will be assessed, and targeted manual additions from other data sources will be carried out as needed.

Year 2

The second year will focus on building vegetation structure metrics and microclimate models for the sites included in the database produced in year 1. This will involve collation of various different sources of remote sensed data and integration into a mechanistic microclimate model, to map microclimate across study sites in high resolution. Microclimate data will be summarised into bioclimatic variables of particular relevance to insects, for multiple heights depending on the height typically occupied by the species of interest. With these data, we will begin building statistical models of the interacting effects of land-use and climate change on insect pollinator species globally.

Year 3

In the final year, we will expand on results from year 2 by exploring whether modelled relationships are consistent across geographic regions and predominant vegetation types. There will be scope here to explore how the responses of insect pollinators in turn impacts the crops that they pollinate, with a view to extrapolation in space and time to better understand impacts on future crop yields.

Year 3.5

The final 6 months will be used to synthesise previous results. If there are different responses depending on insect pollinator, geographic region and/or crops, we will explore here the potential policy implications of our findings. As an example, we may consider the role of agroforestry in maintaining yields through provisioning of microclimate refugia for insect pollinators.

Training will be given in microclimate modelling, spatial analyses and programming in R, Python and Google Earth Engine as needed. Fieldwork would utilise microclimate sensors, for which we will provide training in designing representative sensor networks.