Insect declines: an exploration of diversity in trends and traits through time
Bibliographic record
Abstract
Biodiversity is undergoing rapid transformation due to human activities, and yet healthy, biodiverse systems are essential for humankind. Although evidence is lacking for most parts of the world and many species groups, the evidence we do have for biodiversity change shows that not only are vulnerable species disappearing at unprecedented rates, but the abundance of what were once common species is declining. This is potentially disrupting the processes on which the functioning of ecosystems relies. Insects and other arthropods are diverse organisms that are essential for providing ecosystem functions and are under threat from an array of environmental pressures. Yet, the scope of declines and their wider impacts are not fully understood. In this thesis, I aim to address knowledge gaps around the extent of insect declines and the relationship between insect abundance, diversity, and ecosystem functions, by focussing on functional traits. Chapter 1 introduces the current literature around the relationship between biodiversity and ecosystem function and the recent exploding interest in insect declines, pointing out the major sources of controversy in this area. In Chapter 2, I explore how the abundance of freshwater insects and other invertebrates has changed over time in England. I reveal heterogeneity in trends amongst different taxa, trophic groups and across different river systems, warning against sweeping statements of declines. In Chapter 3, I investigate how environmental pressures impact insect communities, quantifying change in abundance and biomass of Diptera under intensive agriculture in Québec, Canada. Chapter 4 expands on this, using theoretical relationships between body size, population size and the number of species to predict declines in the number and population sizes of large species and a positive impact on small species of Diptera. Chapter 5 demonstrates that diversity in functional traits, such as body size, can contribute to resilience in insect communities by being positively associated with population asynchrony. In Chapter 6, I predict how functional diversity described by trait spaces has changed over the past few decades under abundance change for a variety of insect taxa in the UK. The final chapter summarises the key findings and presents thoughts on the direction of future research and conservation actions. Overall, the thesis extends our understanding of the consequences of insect declines, imparting evidence that links environmental drivers of biodiversity change through to the undermining of long-term functional resilience.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".