Modeling lamprey distribution using flow, geomorphology, and elevation in a terminal lake system
Objective: Lampreys are an ecologically important group of fishes. Several species are imperiled and lack key distribution and habitat data, particularly those in arid/semi-arid ecosystems. The terminal Goose Lake Basin, U.S.A. is home to two such species, the Goose Lake Lamprey, Entosphenus sp. (formally undescribed), and the Pit-Klamath Brook Lamprey, E. lethophagus. Species distribution models (SDMs) are useful for identifying key habitats; however, SDMs are subject to accuracy impairments caused by spatial autocorrelation and scale mismatches—both exacerbated by the hierarchical structure of dendritic stream networks. Our objective was to examine factors influencing distribution for both species in the Goose Lake Basin across scales.
Methods: We integrated count and presence–absence data from five surveys and relevant habitat variables 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 watershed-scale elevation were associated with lamprey presence. The non-spatial model 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 improved after accounting for spatial relationships across multiple scales. Developing accurate and efficient modeling strategies incorporating the hierarchical structure inherent to stream ecosystems aids in the management and conservation of native fishes such as lampreys.