ArticleTransactions of the American Fisheries Society2025
Modeling lamprey distribution using flow, geomorphology, and elevation in a terminal lake system.
Article in Transactions of the American Fisheries Society, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Objective: Lampreys are an ecologically important group of fishes; however, several species are imperiled and lack key distribution and habitat data, particularly those in arid and semi-arid aquatic ecosystems. The terminal Goose Lake Basin, U.S.A. is home to two such species, the Goose Lake Lamprey, Methods: We integrated fish count and presence-absence data from five previously collected surveys and relevant habitat variables sourced from publicly available, geospatial datasets to build logistic regression models. To account for potential mismatches of scale, we compared three sample grains for slope and sinuosity (i.e., stream segment lengths: 250, 500, and 1,000 m), and two scales of elevation (site and watershed). We accounted for spatial autocorrelation by incorporating network-based and Euclidean spatial dependencies using a spatial stream network (SSN) modeling approach. Using the best-fit spatial and non-spatial models, we predicted basin-wide lamprey distribution. Result: Flow, slope, and sinuosity at our largest sample grain (1,000 m), and area-weighted elevation at the watershed scale were associated with lamprey presence. The non-spatial model generally predicted lamprey presence among sinuous, low-gradient streams, whereas the spatial model, which identified Euclidean and flow-connected spatial relationships, predicted contiguous patches with a high probability of occurrence near areas with previously observed presences. Conclusion: Our study revealed ecological relationships and produced an accurate, basin-wide SDM. Prediction and inference were both improved after accounting for spatial relationships across multiple scales. Developing accurate and efficient modeling strategies that incorporate the hierarchical structure inherent to stream ecosystems aids in the management and conservation of native fishes such as lampreys. Impact Statement: Lampreys are ecologically important and understudied; knowledge gaps regarding habitat and spatial distribution hinder their conservation. Our riverscape-based approach used multiple datasets to produce an accurate species distribution model linking lamprey distribution to flow, slope, sinuosity, and elevation.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.