Katelyn B.S. King | USGS Science

USGS2022

Freshwater corridors in the conterminous US: A coarse-filter approach based on lake-stream networks

Maintaining regional-scale freshwater connectivity is challenging owing to the dendritic, easily fragmented structure of freshwater networks, but is essential for promoting ecological resilience under climate change. Although the importance of stream network connectivity has been recognized, lake-stream network connectivity has largely been ignored. Furthermore, protected areas are generally not designed to maintain or encompass entire freshwater networks. We applied a coarse-filter approach to identify potential freshwater corridors for diverse taxa by calculating connectivity scores for 385 lake-stream networks across the conterminous US based on network size, structure, resistance to fragmentation, and dam prevalence. We also identified 2080 disproportionately important lakes for maintaining intact networks (i.e., “hubs”; 2% of all network lakes) and analyzed the protection status of hubs and potential freshwater corridors. Just 3% of networks received high connectivity scores based on their large size and structure (medians of 1303 lakes, 498.6 km north-south stream distance), but these also contained a median of 454 dams. In contrast, undammed networks (17% of networks) were considerably smaller (medians of 6 lakes, 7.2 km north-south stream distance), indicating that the functional connectivity of the largest potential freshwater corridors in the conterminous US currently may be diminished compared to smaller, undammed networks. Network lakes and hubs were protected at similar rates nationally across different levels of protection (8-18% and 6-20%, respectively), but were generally more protected in the western US. Our results indicate that conterminous US protection of major freshwater corridors and the hubs that maintain them generally fell short of the international conservation goal of protecting an ecologically representative, well-connected set of fresh waters (≥ 17%) by 2020 (Aichi Target 11). Conservation planning efforts might consider focusing on restoring natural hydrologic connectivity at or near hubs, particularly in larger networks, less protected, or biodiverse regions, to support freshwater biodiversity conservation under climate change.

Ecosphere↗

USGS2020

Ecological prediction at macroscales using big data: Does sampling design matter?

Although ecosystems respond to global change at regional to continental scales (i.e., macroscales), model predictions of ecosystem responses often rely on data from targeted monitoring of a small proportion of sampled ecosystems within a particular geographic area. In this study, we examined how the sampling strategy used to collect data for such models influences predictive performance. We subsampled a large and spatially-extensive dataset to investigate how macroscale sampling strategy affects prediction of ecosystem characteristics in 6,784 lakes across a 1.8 million km2 area. We estimated model predictive performance for different subsets of the dataset to mimic three common sampling strategies for collecting observations of ecosystem characteristics: random sampling design, stratified random sampling design, and targeted sampling. We found that sampling strategy influenced model predictive performance such that (1) stratified random sampling designs did not improve predictive performance compared to simple random sampling designs and (2) although one of the scenarios that mimicked targeted (non-random) sampling had the poorest performing predictive models, the other targeted sampling scenarios resulted in models with similar predictive performance to that of the random sampling scenarios. Our results suggest that although potential biases in datasets from some forms of targeted sampling may limit predictive performance, compiling existing spatially-extensive datasets can result in models with good predictive performance that may inform a wide range of science questions and policy goals related to global change.

Ecological Applications↗