Details of Award
NERC Reference : NE/V007173/1
GLobal Insect Threat-Response Synthesis (GLiTRS): a comprehensive and predictive assessment of the pattern and consequences of insect declines
Grant Award
- Principal Investigator:
- Dr L Dicks, University of Cambridge, Zoology
- Grant held at:
- University of Cambridge, Zoology
- Science Area:
- Freshwater
- Terrestrial
- Overall Classification:
- Unknown
- ENRIs:
- Biodiversity
- Environmental Risks and Hazards
- Global Change
- Science Topics:
- Animal organisms
- Insects
- Conservation Ecology
- Biodiversity conservation
- Ecosystem function
- Ecosystem services
- Land use change
- Abstract:
- With increasing recognition of the importance of insects, there are growing concerns that insect biodiversity has declined globally, with serious consequences for ecosystem function and services. Yet, gaps in knowledge limit progress in understanding the magnitude and direction of change. Information about insect trends is fragmented, and time-series data are restricted and unrepresentative, both taxonomically and spatially. Moreover, causal links between insect trends and anthropogenic pressures are not well-established. It is, therefore, difficult to evaluate stories about "insectageddon", to understand the ecosystem consequences, to devise mitigation strategies, or predict future trends. To address the shortfalls, we will bring together diverse sources of information, such as meta-analyses, correlative relationships and expert judgement. GLiTRS will collate these diverse lines of evidence on how insect biodiversity has changed in response to anthropogenic pressures, how responses vary according to functional traits, over space, and across biodiversity metrics (e.g. species abundance, occupancy, richness and biomass), and how insect trends drive further changes (e.g. mediated by interaction networks). We will integrate these lines of evidence into a Threat-Response model describing trends in insect biodiversity across the globe. The model will be represented in the form of a series of probabilistic statements (a Bayesian belief network) describing relationships between insect biodiversity and anthropogenic pressures. By challenging this "Threat-Response model" to predict trends for taxa and places where high-quality time series data exist, we will identify insect groups and regions for which indirect data sources are a) sufficient for predicting recent trends, b) inadequate, or c) too uncertain. Knowledge about the predictability of threat-response relationships will allow projections - with uncertainty estimates - of how insect biodiversity has changed globally, across all major taxa, functional groups and biomes. This global perspective on recent trends will provide the basis for an exploration of the consequences of insect decline for a range of ecosystem functions and services, as well as how biodiversity and ecosystem properties might be affected by plausible scenarios of future environmental change. GLiTRS is an ambitious and innovative research program: two features are particularly ground-breaking. First, the collation of multiple forms of evidence will permit a truly global perspective on insect declines that is unachievable using conventional approaches. Second, by validating "prior knowledge" (from evidence synthesis) with recent trends, we will assess the degree to which insect declines are predictable, and at what scales.
- Period of Award:
- 14 Nov 2020 - 13 Nov 2024
- Value:
- £218,018 Split Award
Authorised funds only
- NERC Reference:
- NE/V007173/1
- Grant Stage:
- Awaiting Event/Action
- Scheme:
- Directed (Research Programmes)
- Grant Status:
- Active
- Programme:
- Highlights
This grant award has a total value of £218,018
FDAB - Financial Details (Award breakdown by headings)
| DI - Other Costs | Indirect - Indirect Costs | DA - Investigators | DI - Staff | DA - Estate Costs | DA - Other Directly Allocated | DI - T&S |
|---|---|---|---|---|---|---|
| £14,077 | £76,295 | £9,524 | £66,970 | £25,652 | £4,521 | £20,980 |
If you need further help, please read the user guide.