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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, Jeffrey R; Doherty, Kevin E; Cross, Todd B; Schwartz, Michael K; Oyler-McCance, Sara J; Naugle, Dave E; Knick, Steven T; Fedy, Bradley C.
Afiliação
  • Row JR; School of Environment, Resources and Sustainability University of Waterloo Waterloo ON Canada.
  • Doherty KE; U.S. Fish and Wildlife Service Lakewood CO USA.
  • Cross TB; Rocky Mountain Research Station USDA Forest Service National Genomics Center for Wildlife and Fish Conservation Missoula MT USA.
  • Schwartz MK; College of Forestry and Conservation University of Montana Missoula MT USA.
  • Oyler-McCance SJ; Rocky Mountain Research Station USDA Forest Service National Genomics Center for Wildlife and Fish Conservation Missoula MT USA.
  • Naugle DE; Fort Collins Science Center U.S. Geological Survey Fort Collins CO USA.
  • Knick ST; College of Forestry and Conservation University of Montana Missoula MT USA.
  • Fedy BC; Forest and Rangeland Ecosystem Science Center U.S. Geological Survey Boise ID USA.
Evol Appl ; 11(8): 1305-1321, 2018 Sep.
Article em En | MEDLINE | ID: mdl-30151042
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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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2018 Tipo de documento: Article