Hierarchical population structure in greater sage-grouse provides insight into management boundary delineation

Cross, Todd B.; Naugle, David E.; Carlson, John C.; Schwartz, Michael K.

doi:10.1007/s10592-016-0872-z

Cited by 13 publications

(22 citation statements)

References 78 publications

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“…Similarly, there was a correlation between conditional genetic distance and geographic distance. These results support prior findings of isolation by distance across the species’ range (Bush et al., ; Cross et al., ; Davis, Reese, Gardner, & Bird, ; Fedy, Row, & Oyler‐McCance, ; Oyler‐McCance, Taylor, & Quinn, ; Schulwitz, Bedrosian, & Johnson, ). However, nodes with greater centrality, important to both local and network‐wide genetic exchange, are located across the species’ range.…”

Section: Discussionsupporting

confidence: 89%

“…We amplified 15 variable microsatellite loci (BG6, SGMS064, SGMS066, SGMS068, MSP11, MSP18, SG28, SG29, SG36, SG39, SGCA5, SGCA11, SGCTAT1, TUT3, and TUT4) and one sex‐diagnostic locus [CHD gene, using the primers 1237L and 1272H (Kahn, St. John, & Quinn, )]. Primer design, PCR conditions, and electrophoresis used at USFS and USGS are detailed in Cross, Naugle, Carlson, and Schwartz (); Cross et al. () and Row et al.…”

Section: Methodsmentioning

confidence: 99%

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The genetic network of greater sage‐grouse: Range‐wide identification of keystone hubs of connectivity

Cross

Schwartz

Naugle

et al. 2018

Ecology and Evolution

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Genetic networks can characterize complex genetic relationships among groups of individuals, which can be used to rank nodes most important to the overall connectivity of the system. Ranking allows scarce resources to be guided toward nodes integral to connectivity. The greater sage‐grouse (Centrocercus urophasianus) is a species of conservation concern that breeds on spatially discrete leks that must remain connected by genetic exchange for population persistence. We genotyped 5,950 individuals from 1,200 greater sage‐grouse leks distributed across the entire species’ geographic range. We found a small‐world network composed of 458 nodes connected by 14,481 edges. This network was composed of hubs—that is, nodes facilitating gene flow across the network—and spokes—that is, nodes where connectivity is served by hubs. It is within these hubs that the greatest genetic diversity was housed. Using indices of network centrality, we identified hub nodes of greatest conservation importance. We also identified keystone nodes with elevated centrality despite low local population size. Hub and keystone nodes were found across the entire species’ contiguous range, although nodes with elevated importance to network‐wide connectivity were found more central: especially in northeastern, central, and southwestern Wyoming and eastern Idaho. Nodes among which genes are most readily exchanged were mostly located in Montana and northern Wyoming, as well as Utah and eastern Nevada. The loss of hub or keystone nodes could lead to the disintegration of the network into smaller, isolated subnetworks. Protecting both hub nodes and keystone nodes will conserve genetic diversity and should maintain network connections to ensure a resilient and viable population over time. Our analysis shows that network models can be used to model gene flow, offering insights into its pattern and process, with application to prioritizing landscapes for conservation.

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Section: Discussionsupporting

confidence: 89%

Section: Methodsmentioning

confidence: 99%

The genetic network of greater sage‐grouse: Range‐wide identification of keystone hubs of connectivity

Cross

Schwartz

Naugle

et al. 2018

Ecology and Evolution

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“…DNA was extracted from feather and blood using previously described methods (Cross, Naugle, Carlson, & Schwartz, 2016; Row et al., 2015). Both FORT and NGC amplified 15 microsatellite loci in eight multiplex polymerase chain reactions (PCR) and genotypes were determined using electrophoresis (Cross et al., 2016; Row et al., 2015). Full genetic methods can also be found in Appendix S1.…”

Section: Methodsmentioning

confidence: 99%

“…Genetic analysis was conducted at two molecular biological labo- tracted from feather and blood using previously described methods (Cross, Naugle, Carlson, & Schwartz, 2016;Row et al, 2015). Both…”

Section: Derivation Of Microsatellite Genotypes For Unique Individualsmentioning

confidence: 99%

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Quantifying functional connectivity: The role of breeding habitat, abundance, and landscape features on range‐wide gene flow in sage‐grouse

Row

Doherty

Cross

et al. 2018

Evolutionary Applications

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Functional connectivity, quantified using landscape genetics, can inform conservation through the identification of factors linking genetic structure to landscape mechanisms. We used breeding habitat metrics, landscape attributes, and indices of grouse abundance, to compare fit between structural connectivity and genetic differentiation within five long‐established Sage‐Grouse Management Zones (MZ) I‐V using microsatellite genotypes from 6,844 greater sage‐grouse (Centrocercus urophasianus) collected across their 10.7 million‐km2 range. We estimated structural connectivity using a circuit theory‐based approach where we built resistance surfaces using thresholds dividing the landscape into “habitat” and “nonhabitat” and nodes were clusters of sage‐grouse leks (where feather samples were collected using noninvasive techniques). As hypothesized, MZ‐specific habitat metrics were the best predictors of differentiation. To our surprise, inclusion of grouse abundance‐corrected indices did not greatly improve model fit in most MZs. Functional connectivity of breeding habitat was reduced when probability of lek occurrence dropped below 0.25 (MZs I, IV) and 0.5 (II), thresholds lower than those previously identified as required for the formation of breeding leks, which suggests that individuals are willing to travel through undesirable habitat. The individual MZ landscape results suggested terrain roughness and steepness shaped functional connectivity across all MZs. Across respective MZs, sagebrush availability (<10%–30%; II, IV, V), tree canopy cover (>10%; I, II, IV), and cultivation (>25%; I, II, IV, V) each reduced movement beyond their respective thresholds. Model validations confirmed variation in predictive ability across MZs with top resistance surfaces better predicting gene flow than geographic distance alone, especially in cases of low and high differentiation among lek groups. The resultant resistance maps we produced spatially depict the strength and redundancy of range‐wide gene flow and can help direct conservation actions to maintain and restore functional connectivity for sage‐grouse.

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A genetic warning system for a hierarchically structured wildlife monitoring framework

Zimmerman

Aldridge

O’Donnell

et al. 2023

Ecological Applications

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Genetic variation is a well-known indicator of population fitness yet is not typically included in monitoring programs for sensitive species. Additionally, most programs monitor populations at one scale, which can lead to potential mismatches with ecological processes critical to species' conservation. Recently developed methods generating hierarchically nested population units (i.e., clusters of varying scales) for greater sage-grouse (Centrocercus urophasianus) have identified population trend declines across spatiotemporal scales to help managers target areas for conservation. The same clusters used as a proxy for spatial scale can alert managers to local units (i.e., neighborhoodscale) with low genetic diversity, further facilitating identification of management targets. We developed a genetic warning system utilizing previously developed hierarchical population units to identify management-relevant areas with low genetic diversity within the greater sage-grouse range. Within this warning system we characterized conservation concern thresholds based on values of genetic diversity and developed a statistical model for microsatellite data to robustly estimate these values for hierarchically nested populations.We found that 41 of 224 neighborhood-scale clusters had low genetic diversity, 23 of which were coupled with documented local population trend decline. We also found evidence of cross-scale low genetic diversity in the small and isolated Washington population, unlikely to be reversed through typical local management actions alone. The combination of low genetic diversity and a declining population suggests relatively high conservation concern.Our findings could further facilitate conservation action prioritization in combination with population trend assessments and (or) local information, and act as a base-line of genetic diversity for future comparison. Importantly, the approach we used is broadly applicable across taxa.

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Hierarchical population structure in greater sage-grouse provides insight into management boundary delineation

Cited by 13 publications

References 78 publications

The genetic network of greater sage‐grouse: Range‐wide identification of keystone hubs of connectivity

The genetic network of greater sage‐grouse: Range‐wide identification of keystone hubs of connectivity

Quantifying functional connectivity: The role of breeding habitat, abundance, and landscape features on range‐wide gene flow in sage‐grouse

A genetic warning system for a hierarchically structured wildlife monitoring framework

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