Landscape genetics annotated bibliography

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					Antolin, M.F., Savage, L.T., & Eisen, R.J. (2006) Landscape features influence genetic structure
       of black-tailed prairie dogs (Cynomys ludovicianus). Landscape Ecology, 21, 867-875.
Cited by 24 (As of 9/10/10)
Impact factor of Landscape Ecology: 3.293

This paper is a review of landscape genetics studies of the Black tailed prairie dog. They
conclude based on their genetic data and previous work describing the structure of prairie dog
populations that both the ecology and genetic sturcture of prairie dogs are influenced by habitat

Balkenhol, N., Waits, L.P., & Dezzani, R.J. (2009) Statistical approaches in landscape genetics:
       an evaluation of methods for linking landscape and genetic data. Ecography, 32, 818-830.
Cited by 14 (As of 9/2/10)
Impact factor of Ecography: 4.385

The authors simulated data for 5 common landscape genetics scenarios which they then
evaluated using 11 different statistical methods. The methods which performed best were
multivariate, non linear methods like MRDM, partial CCA and BIMR. Further, these methods
produce the most accurate results when they are used in combination.

Coulon, A., Guillot, G., Cosson, J.F., Angibault, J.M.A., Aulagnier, S., Cargnelutti, B., Galan,
       M., & Hewison, A.J.M. (2006) Genetic structure is influenced by landscape features:
       empirical evidence from a roe deer population. Molecular Ecology, 15, 1669-1679.
Cited by 84 (As of 9/8/10)
Impact factor of Molecular Ecology: 5.960
Data: Microsatellites (nuclear)

Uses GENELAND to look at structuring of roe deer populations. None of the landscape features
they considered could explain the genetic structuring seen by themselves but rather, landscape
features acting in concert as limits to gene flow could explain the genetic differentiation.

Funk, W.C. & Murphy, M.A. (2010) Testing evolutionary hypotheses for phenotypic divergence
       using landscape genetics. Molecular Ecology, 19, 427-430.
Cited by 0 (As of 9/8/10)
Impact factor of Molecular Ecology: 5.960

Describes and explains Wang and Summers (2010) and provides perspective on testing
evolutionary hypotheses within the context of landscape genetics.

Guillot, G., Estoup, A., Mortier, F., & Cosson, J.F. (2005) A spatial statistical model for
        landscape genetics. Genetics, 170, 1261-1280.
Cited by 155 (As of 8/27/10)
Impact factor of Genetics: 3.889
Data: Microsatellites (nuclear)

This paper establishes a new spatial statistical method for locating genetic discontinuities in a
landscape. It is a form of Bayesian modeling in a Markov Chain Monte Carlo scheme. The
method doesn't use a priori designations and performs well on standard simulated data sets with
both low and high levels of genetic differentiation between populations. The authors then test
their model on microsatellite data from wolverines

Hirao, A.S. & Kudo, G. (2004) Landscape genetics of alpine-snowbed plants: comparisons along
       geographic and snowmelt gradients. Heredity, 93, 290-298.
Cited by 26 (As of 9/2/10)
Impact factor of Heredity: 4.122
Data: Allozymes

Used a matrix of plots in different geographic areas with different timing of snowmelt to
investigate genetic structuring in three species of snowbed-herbs. Found a significant correlation
between geographic and genetic distance in one species and a correlation between phelogic
distance and genetic distance in the other two.

Holderegger, R., Kamm, U., & Gugerli, F. (2006) Adaptive vs. neutral genetic diversity:
       implications for landscape genetics. Landscape Ecology, 21, 797-807.
Cited by 43 (As of 9/2/10)
Impact factor of Landscape Ecology: 3.293

This paper discusses the two types of genetic marker data that can be used in population genetics
studies: adaptive and neutral markers. They emphasize the fact that these two types of data have
different applications because they tell the researcher different things about the genetic
differentiation of the study organism. The authors suggest that neutral markers are most useful
for considering questions of what is driving landscape level differentiation while adaptive
markers are most useful when questions focus more on evolution.

Holderegger, R. & Wagner, H.H. (2006) A brief guide to landscape genetics. Landscape
       Ecology, 21, 793-796.
Cited by 53 (As of 9/2/10)
Impact factor of Landscape Ecology: 3.293

The authors of this paper are not completely satisfied with the definition of landscape ecology
provided in Manel et al. (2003) so they endeavor to provide a more accurate description,
specifically on the landscape, spatial side of things. It includes two tables of advice, one for
ecologists planning to use genetic data and one for geneticists planning to use landscape ecology

Holderegger, R. & Wagner, H.H. (2008) Landscape genetics. Bioscience, 58, 199-207.
Cited by 54 (As of 9/2/10)
Impact factor of BioScience: 4.064

This paper is a review of the techniques and questions used in both l andscape ecology and
population genetics. The authors discuss the combined applications of these two fields to
conservation. They further discuss the limitations of using neutral markers and suggest that
genomic methods will help researchers in the future when they need to consider the effects of
both rapid land use changes and slower climate changes.

Keyghobadi, N., Roland, J., & Strobeck, C. (1999) Influence of landscape on the population
       genetic structure of the alpine butterfly Parnassius smintheus (Papilionidae). Molecular
       Ecology, 8, 1481-1495.
Cited by 126 (As of 9/2/10)
Impact factor of Molecular Ecology: 5.960
Data: Microsatellites (nuclear)

Looks at population structure, distance and several environmental factors in the alpine butterfly.
Found that there was evidence of isolation by distance in the populations and further that the
forest was acting as a barrier to gene flow.

Manel, S., Schwartz, M.K., Luikart, G., & Taberlet, P. (2003) Landscape genetics: combining
       landscape ecology and population genetics. Trends in Ecology & Evolution, 18, 189-197.
Cited by 546 (As of 8/27/10)
Impact factor of Trends in Ecology and Evolution: 11.564

Provides definitions of terms used in landscape genetics and landscape genetics itself. Describes
methods of statistical analysis and visualization used in the field.

Murphy, M.A., Evans, J.S., & Storfer, A. (2010) Quantifying Bufo boreas connectivity in
       Yellowstone National Park with landscape genetics. Ecology, 91, 252-261.
Cited by 13 (As of 9/8/10)
Impact factor of Ecology: 4.411
Data: Microsatellites (nuclear)

Uses Random Forest models to look at the influence of several landscape and ecological factors
on genetic diversity in Bufo boreas on different scales. Measures of habitat permeability were
found to be important at small scales, measures of topographic morphology at broad scales and
measures of the temperature/moisture regime were found to be influential on genetic distance
across scales. The authors stress that using an algorithmic approach to analyzing landscape
genetic data can provide a greater explanation of the factors influencing genetic diversity.

Petren, K., Grant, P.R., Grant, B.R., & Keller, L.F. (2005) Comparative landscape genetics and
        the adaptive radiation of Darwin's finches: the role of peripheral isolation. Molecular
        Ecology, 14, 2943-2957.
Cited by 42 (As of 9/2/10)
Impact factor of Molecular Ecology: 5.960

Evaluates possible causes of genetic differentiation in three groups of Darwin's finches. Warbler
finches seemed ot show low genetic diversity due to drift while cactus and sharp-beaked ground
finches showed evidence of isolation by distance.

Savage, W.K., Fremier, A.K., & Shaffer, H.B. (2010) Landscape genetics of alpine Sierra
       Nevada salamanders reveal extreme population subdivision in space and time. Molecular
       Ecology, 19, 3301-3314.
Cited by 0 (As of 8/27/10)
Impact factor of Molecular Ecology: 5.960
Data: Microsatellites (nuclear)

Created a friction matrix to observe landscape effects on genetic differentiation in southern long-
toed salamanders. Evaluated several models and sampled both spatially and temporally. Found
highly divergent populations based mostly on distance in the Lake Tahoe region and a less clear
picture of what is structuring populations in the Eldorado region.

Schwartz, M.K. & McKelvey, K.S. (2009) Why sampling scheme matters: the effect of sampling
       scheme on landscape genetic results. Conservation Genetics, 10, 441-452.
Cited by 44 (As of 9/10/10)
Impact factor of Conservation Genetics: 3.899
Data: Simulated

The authors wanted to determine whether the current trend in sampling to sample evenly across a
landscape provided accurate results in STRUCTURE. The authors found that STRUCTURE was
able to correctly identify a single population when it was being sampled but when genetic
structuring existed, STRUCTURE did not always perform as well, depending on how the data
was sampled. The authors recommend that STRUCTURE not be used without some a priori
knowledge of the number of populations or clusters that exist within the data because to do
otherwise could result in an incorrect interpretation of your results.

Segelbacher, G., Cushman, S.A., Epperson, B.K., Fortin, M.J., Francois, O., Hardy, O.J.,
       Holderegger, R., Taberlet, P., Waits, L.P., & Manel, S. (2010) Applications of landscape
       genetics in conservation biology: concepts and challenges. Conservation Genetics, 11,
Cited by 5 (As of 9/7/10)
Impact factor of Conservation Genetics: 3.899

This paper discusses the limitations and applications of landscape genetics studies to the field of
conservation. They point out that often the design of landscape genetics studies and the
questions they aim to answer don't give enough insight into the processes at work for proper
application in conservation. They provide reviews of several common statistical and modeling
techniques used in landscape genetics. They conclude that the techniques used in landscape
genetics do provie powerful tools for better studying genetics at the landscape level and that the
field will be helpful to conservation.

Sork, V.L. & Smouse, P.E. (2006) Genetic analysis of landscape connectivity in tree populations.
       Landscape Ecology, 21, 821-836.
Cited by 70 (As of 9/2/10)
Impact factor of Landscape Ecology

This paper reviews the methods for considering the movement of both pollen and seeds in tree
populations and reviews studies that have considered the movement of pollen in the landscape
and those that have considered the movement of seeds. The authors conclude that for a complete
study of tree genetic connectivity it is imperative to take into account the movement of both
pollen and seeds.

Spear, S.F., Peterson, C.R., Matocq, M.D., & Storfer, A. (2005) Landscape genetics of the
       blotched tiger salamander (Ambystoma tigrinum melanostictum). Molecular Ecology, 14,
Cited by 96 (As of 9/2/10)
Impact factor of Molecular Ecology: 5.960
Data: Microsatellites (nuclear)

First, the authors tested whether isolation by distance led to population structure in blotched tiger
salamanders. Then they used GIS to incorporate landscape variables and found it significantly
improved model fit. Distance and elevation were found to be important in higher levels of

Storfer, A., Murphy, M.A., Evans, J.S., Goldberg, C.S., Robinson, S., Spear, S.F., Dezzani, R.,
        Delmelle, E., Vierling, L., & Waits, L.P. (2007) Putting the 'landscape' in landscape
        genetics. Heredity, 98, 128-142.
Cited by 179 (As of 9/2/10)
Impact factor of Heredity: 4.122

Provides a definition of landscape genetics and a table including recent works in the field which
also provides the design, analyses, data and conclusions in those studies. The review discusses
questions, design and analyses of landscape genetics and talks about the future directions of the

Wang, I.J. (2009) Fine-scale population structure in a desert amphibian: landscape genetics of
       the black toad (Bufo exsul). Molecular Ecology, 18, 3847-3856.
Cited by 2 (As of 9/2/10)
Impact factor of Molecular Ecology: 5.960
Data: Microsatellites (nuclear)
The black toad is restricted to four springs in a desert basin. All but the two closest spring
populations show significant population structure and the authors found that structure was
correlated with distance influenced by topography and the presence of a lake barrier.

Wang, I.J. & Summers, K. (2010) Genetic structure is correlated with phenotypic divergence
       rather than geographic isolation in the highly polymorphic strawberry poison-dart frog.
       Molecular Ecology, 19, 447-458.
Cited by 2 (As of 9/8/10)
Impact factor of Molecular Ecology: 5.960
Data: Microsatellites (nuclear)

This paper used microsatellite data and partial mantel tests to test 12 causal hypotheses for
genetic structuring seen in strawberry poison dart frogs. The authors found support only for the
phenotypic divergence hypothesis.

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