A macroevolutionary mosaic: episodic host‐switching, geographical colonization and diversification in complex host–parasite systems
Bibliographic record
Abstract
Abstract Aim To integrate ecological fitting, the oscillation hypothesis and the taxon pulse hypothesis into a coherent null model for the evolution of complex host–parasite associations. Location Global. Methods This paper reviews and synthesizes literature that focuses on phylogenetic analyses and reciprocal mapping of a model system of hosts and their parasites to determine patterns of host–parasite associations and geographical distributions through time. Results Host‐switching and geographical dispersal of parasites are common phenomena, occurring on many temporal and spatial scales. Diversification involving both co‐evolution and colonization explains complex host–parasite associations. Across the expanse of Earth history, the major radiations in host–parasite assemblages have been preceded by ecological disruption, ecological breakdown and host‐switching in a context that can be defined by the concept of ecological fitting. This cyclical process sets the stage for co‐diversification during periods of relative stability, punctuated by host‐switching during episodes of regional to global environmental disruption and climatological change. Main conclusions Most observed host–parasite associations can be explained by an historical interaction between ecological fitting, oscillation (episodes of increasing host range alternating with isolation on particular hosts) and taxon pulses (cyclical episodes of expansion and isolation in geographical range). Major episodes of environmental change appear to be the main drivers for both the persistence and diversification of host–parasite systems, creating opportunities for host‐switching during periods of geographical expansion and allowing for co‐evolution and co‐speciation during periods of geographical isolation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".