Spatial scale and structure of complex life cycle trematode parasite communities in streams
Bibliographic record
Abstract
By considering the role of site-level factors and dispersal, metacommunity concepts have advanced our understanding of the processes that structure ecological communities. In dendritic systems, like streams and rivers, these processes may be impacted by network connectivity and unidirectional current. Streams and rivers are central to the dispersal of many pathogens, including parasites with complex, multi-host life cycles. Patterns in parasite distribution and diversity are often driven by host dispersal. We conducted two studies at different spatial scales (within and across stream networks) to investigate the importance of local and regional processes that structure trematode (parasitic flatworms) communities in streams. First, we examined trematode communities in first-intermediate host snails (Elimia proxima) in a survey of Appalachian headwater streams within the Upper New River Basin to assess regional turnover in community structure. We analyzed trematode communities based on both morphotype (visual identification) and haplotype (molecular identification), as cryptic diversity in larval trematodes could mask important community-level variation. Second, we examined communities at multiple sites (headwaters and main stem) within a stream network to assess potential roles of network position and downstream drift. Across stream networks, we found a broad scale spatial pattern in morphotype- and haplotype-defined communities due to regional turnover in the dominant parasite type. This pattern was correlated with elevation, but not with any other environmental factors. Additionally, we found evidence of multiple species within morphotypes, and greater genetic diversity in parasites with hosts limited to in-stream dispersal. Within network parasite prevalence, for at least some parasite taxa, was related to several site-level factors (elevation, snail density and stream depth), and total prevalence decreased from headwaters to main stem. Variation in the distribution and diversity of parasites at the regional scale may reflect differences in the abilities of hosts to disperse across the landscape. Within a stream network, species-environment relationships may counter the effects of downstream dispersal on community structure.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".