CoChat
Sign Up
Cited by 945

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Circuit theory predicts gene flow in plant and animal populations

McRae, Brad H., Beier, Paul·2007·Proceedings of the National Academy of Sciences
DOI 10.1073/pnas.0706568104
Open this paper in CoChat — free account

Abstract

Maintaining connectivity for broad-scale ecological processes like dispersal and gene flow is essential for conserving endangered species in fragmented landscapes. However, determining which habitats should be set aside to promote connectivity has been difficult because existing models cannot incorporate effects of multiple pathways linking populations. Here, we test an ecological connectivity model that overcomes this obstacle by borrowing from electrical circuit theory. The model vastly improves gene flow predictions because it simultaneously integrates all possible pathways connecting populations. When applied to data from threatened mammal and tree species, the model consistently outperformed conventional gene flow models, revealing that barriers were less important in structuring populations than previously thought. Circuit theory now provides the best-justified method to bridge landscape and genetic data, and holds much promise in ecology, evolution, and conservation planning.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1073/pnas.0706568104

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Across long time scales at which genetic mutations can be measured, resistance distance is strongly correlated to the differences between populations.

    “It has already been demonstrated that across long time scales at which genetic mutations can be measured, resistance distance is strongly correlated to the differences between populations [28], [29], [42].”

    From Applying circuit theory for corridor expansion and management at regional scales: tiling, pinch points, and omnidirectional connectivity (2014) · cites this paper as [29]

    The Results tables report strong correlations between resistance distance and genetic differentiation in mahogany and wolverine populations (R² = 0.68–0.85 across the listed measures). The paper discusses gene flow over many generations, but does not establish the claim’s specific time-scale qualifier—that these are long time scales at which genetic mutations can be measured. (LLM, conf=0.85)

    Experimental — accuracy not yet measured

  • McRae & Beier (2007) showed Circuitscape software to be relatively insensitive to cell size.

    “McRae & Beier (2007), however, showed Circuitscape software to be relatively insensitive to cell size.”

    From Landscape connectivity for wildlife: development and validation of multispecies linkage maps (2014) · cites this paper as McRae & Beier (2007)

  • McRae & Beier (2007) demonstrated that IBR explained genetic patterns of mammal (wolverine, Gulo gulo) and plant (bigleaf mahogany, Swetenia macrophylla) populations about 50-200% better than two conventional approaches, namely isolation by distance and least-cost paths.

    “The second foundational paper (McRae & Beier 2007) demonstrated that IBR explained genetic patterns of mammal (wolverine, Gulo gulo) and plant (bigleaf mahogany, Swetenia macrophylla) populations about 50–200% better than two conventional approaches, namely isolation by distance and least-cost paths.”

    From Circuit‐theory applications to connectivity science and conservation (2019) · cites this paper as McRae & Beier 2007

  • The species in McRae & Beier (2007) were undergoing rapid human-caused demographic changes, violating the IBR model assumption that all populations are in genetic equilibrium.

    “The findings were striking because the species were undergoing rapid human-caused demographic changes, violating the IBR model assumption that all populations are in genetic equilibrium (i.e., based on the response variable, FST).”

    From Circuit‐theory applications to connectivity science and conservation (2019) · cites this paper as McRae & Beier 2007

  • Multiple or wider swaths of suitable habitat are more likely conduits of animal movement than are narrow pathways.

    “Multiple or wider swaths of suitable habitat are more likely conduits of animal movement than are narrow pathways (McRae & Beier 2007).”

    From Landscape connectivity for wildlife: development and validation of multispecies linkage maps (2014) · cites this paper as McRae & Beier 2007

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Flagged first, then by citations

Research works printed but not linked: 34

  1. 10.2307/1313208 · DOI
  2. 10.1017/CBO9780511754821 · DOI
  3. 10.1017/CBO9780511754821.013 · DOI
  4. 10.1890/1540-9295(2004)002[0529:ACGTCM]2.0.CO;2 · DOI · Paper page
  5. 10.1016/S0169-5347(03)00008-9 · DOI · Paper page
  6. 10.1038/33136 · DOI
  7. 10.1126/science.3576198 · DOI
  8. 10.1073/pnas.091093098 · DOI
  9. 10.1111/j.1365-2664.2007.01325.x · DOI
  10. 10.1111/j.1365-294X.2005.02632.x · DOI
  11. 10.1073/pnas.0500057102 · DOI
  12. 10.1038/nature01942 · DOI
  13. 10.1016/S0169-2046(02)00242-6 · DOI · Paper page
  14. 10.1111/j.1365-294X.2004.02253.x · DOI
  15. 10.1111/j.1365-294X.2005.02568.x · DOI
  16. 10.1086/506976 · DOI · Paper page
  17. 10.1111/j.1558-5646.1993.tb01215.x · DOI
  18. 10.1007/BF01164627 · DOI
  19. 10.1093/genetics/145.4.1219 · DOI
  20. IUCN Red List of Threatened Species (World Conservation Union, Gland, Switzerland, 2006).
  21. 10.1046/j.1365-294X.2003.01951.x · DOI
  22. 10.1046/j.1365-294x.2001.01222.x · DOI
  23. N Mantel Cancer Res 27, 209–220 (1967).
  24. P Legendre, L Legendre Numerical Ecology (Elsevier, Amsterdam, 1998).
  25. FB Lamb Mahogany of Tropical America: Its Ecology and Management (Univ of Michigan Press, Ann Arbor, MI, 1966).
  26. J Calvo Evaluation of Mahogany (Swietenia macrophylla King) in Mesoamerica (PROARCA/CAPAS, Tropical Science Center, Costa Rica, 2000).
  27. 10.1111/j.1558-5646.1999.tb04571.x · DOI
  28. 10.1109/TCAD.2005.850863 · DOI
  29. 10.5948/UPO9781614440222 · DOI · Paper page
  30. DE Wilson Wild Mammals of North America, eds JA Chapman, GA Feldhamer (Johns Hopkins Univ Press, Baltimore), pp. 644–652 (1982).
  31. TD Pennington, BT Styles, DAH Taylor Flora Neotrop 28, 1–449 (1981).
  32. 10.1111/j.1471-8286.2004.00843.x · DOI
  33. 10.2307/2413122 · DOI
  34. P Legendre, A Vaudor The R Package: Multidimensional Analysis, Spatial Analysis (Département de Sciences Biologiques, Université de Montréal, Montréal, 1991).

Cited by

Sorted by citations

Metadata

Authors
McRae, B. H., & Beier, P.
Affiliations
  • *National Center for Ecological Analysis and Synthesis, 735 State Street, Suite 300, Santa Barbara, CA 93101; and
  • School of Forestry and Merriam–Powell Center for Environmental Research, Northern Arizona University, Flagstaff, AZ 86011
Venue
Proceedings of the National Academy of Sciences
Publisher
National Academy of Sciences
Published
2007-12-11
Volume
104
Issue
50
Pages
19885-19890
ISSN
  • 0027-8424
  • 1091-6490
DOI
10.1073/pnas.0706568104
Cited by
945
References
1
Language
en

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review