To assess the effectiveness of protected areas in two catchment scales (local and network) in conserving regionally common fluvial fishes using modelled species distributions.
Conterminous United States.
A total of 150 species were selected that were geographically widespread, abundant, non‐habitat specialists and native within nine large ecoregions. Species distribution models were developed using boosted regression trees, and modelled distributions were assessed for protection status under two alternatives: lands strictly managed for biodiversity (Highly Restricted Use) and those allowing multiple uses (Multiple Use), with protection target levels (i.e., the amount of protected area required for protection) for local and network catchments being developed from ecoregion‐based urban and agricultural land use thresholds from fish responses.
Overall, less than 2% of fluvial catchments in the conterminous USA are meeting both local and network catchment protection target levels under the Highly Restricted Use alternative, whereas 16% of catchments met protection levels for the Multiple Use alternative, with protection largely concentrated in the western USA. For common native species distributions within ecoregions, only one species had >10% of streams meeting combined local and network catchment protection target levels under the Highly Restricted Use alternative, whereas 50 distributions (~14% of species distribution models) met this level under the Multiple Use alternative.
Even for fishes considered widespread and abundant, protection levels are lacking, particularly when considering only lands that are actively managed for biodiversity. Given the increasing intensification of anthropogenic activities and substantial uncertainty associated with climate change, considering the conservation status for all species, including those currently considered common, is warranted.
|Publication Subtype||Journal Article|
|Title||Protected areas lacking for many common fluvial fishes of the conterminous USA|
|Series title||Diversity and Distributions|
|Contributing office(s)||Science Analytics and Synthesis|
|Google Analytic Metrics||Metrics page|