Summary
Crayfishes and other freshwater aquatic fauna are particularly at risk globally due to anthropogenic demand, manipulation and exploitation of freshwater resources and yet are often understudied. The Ozark faunal region of Missouri and Arkansas harbours a high level of aquatic biological diversity, especially in regard to endemic crayfishes. Three such endemics, Orconectes eupunctus, Orconectes marchandi and Cambarus hubbsi, are threatened by limited natural distribution and the invasions of Orconectes neglectus.
We examined how natural and anthropogenic abiotic factors influence these three species across multiple spatial scales. Local and landscape environmental variables were used as predictors in classification and regression tree models at stream segment and segmentshed scales to determine their relation to presence/absence and density of the three species.
Orconectes eupunctus presence was positively associated with stream size, current velocity and spring flow volume. Orconectes marchandi presence was predicted primarily by dolomite geology and water chemistry variables. Cambarus hubbsi was associated with larger stream size, with highest densities occurring in deep waters. Stream segment and segmentshed scale models were similar, but there were important differences based on species and response variables (presence/absence versus density). Stream segment scale models consistently performed better than or equal to segmentshed scale models.
Anthropogenic abiotic environmental variables were of minor importance in most models, with the exception of O. marchandi being negatively related to road density and human population density. Classification tree models predicting distribution performed well when compared to random assignment, but regression trees were generally poor in explaining variation in density.
We found that a range of environmental variables were important in predicting crayfish distribution and abundance at multiple spatial scales and their importance was species‐, response variable‐ and scale dependent. We would encourage others to examine the influence of spatial scale on species distribution and abundance patterns.
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