<scp>cdpop</scp>: A spatially explicit cost distance population genetics program

Landguth, Erin L.; Cushman, Samuel A.

doi:10.1111/j.1755-0998.2009.02719.x

Cited by 214 publications

(180 citation statements)

References 15 publications

(28 reference statements)

Supporting

Mentioning

177

Contrasting

Unclassified

Order By: Relevance

“…Recent software development in this field has increased processing speed thousands of times (Allen and Dytham 2009). Developments in this area were highlighted in Balkenhol et al (2009a), who noted in particular CDPOP (Landguth and Cushman 2010), and BIOMAPPER (in the EcoGenetics suite http://www2.unil.ch/ biomapper/ecogenetics/index.html, accessed 13 September 2010). These interface extremely well with the kinds of data and approaches that are used in field-based and molecular population biology research on organisms in landscapes affected by human activity.…”

Section: Demographic Projections In Real Landscapes Experiencing Envimentioning

confidence: 99%

“…Circuitscape is becoming a common tool for production of cost-distance matrices which can be used as part of the input for demographic and population genetic modelling. For example, it is accepted by CDPOP, an individually based, spatially explicit, population genetic simulator that incorporates a very flexible and detailed demographic model, and can be used to investigate relationships between landscape resistance surfaces, gene flow and population genetic patterns in a computationally efficient manner (Landguth and Cushman 2010).…”

Section: Landscape Genetics: Relating Spatial Genetic Patterns To Lanmentioning

confidence: 99%

See 1 more Smart Citation

Towards modelling persistence of woodland birds: the role of genetics

Sunnucks

2011

Emu - Austral Ornithology

View full text Add to dashboard Cite

Abstract. Assessing how environmental change affects the probability of persistence of organisms requires an understanding of dispersal through, and occupation of, landscapes, and the associated demographic outcomes. Projections of differences in persistence probability can then be made under different scenarios of land-use and global environmental change. Rates and distances of dispersal, and demographic change and trajectories, are difficult to measure accurately, but genetic approaches can make major contributions. For two decades the field of molecular ecology has been providing useful life-history information relevant to population management, including key ecological attributes such as disease-resistance and thermal biology, mobility, dispersal and gene flow, habitat connectivity, the spatial and temporal scales of population processes, and demography. Genetic estimators of these factors could be employed to a much greater extent than they are currently. To facilitate this increased use, genetic estimates of functional connectivity (mobility and gene flow of organisms) and demography need to be integrated directly into decision-making processes. Population genetics is well suited to Bayesian approaches, with associated benefits including the ability to consider many factors, and estimation of error and parameter sensitivities. Genetic estimators based on the mobility and reproductive success of individual organisms and their key ecological traits can make unique contributions alongside other types of data into agent-based, spatially explicit modelling approaches of real landscape scenarios at the range of scales needed by managers. Virtually all the tools to do this exist. It is imperative that genetic samples be collected for contemporary and future analyses.

show abstract

Section: Demographic Projections In Real Landscapes Experiencing Envimentioning

confidence: 99%

Section: Landscape Genetics: Relating Spatial Genetic Patterns To Lanmentioning

confidence: 99%

Towards modelling persistence of woodland birds: the role of genetics

Sunnucks

2011

Emu - Austral Ornithology

View full text Add to dashboard Cite

show abstract

“…To assess type I errors within sPCA, partial RDA and spatially lagged regression models, we simulated 100 populations where only geographic distance influenced gene flow in the program CDPOP v. 1.4 (Landguth and Cushman, 2009). CDPOP allows manipulation of both landscape resistance to gene flow and assignment of demographic characteristics.…”

Section: Type I Error Assessmentmentioning

confidence: 99%

Fine-scale landscape genetics of the American badger (Taxidea taxus): disentangling landscape effects and sampling artifacts in a poorly understood species

Kierepka

Latch

2015

Heredity

View full text Add to dashboard Cite

Landscape genetics is a powerful tool for conservation because it identifies landscape features that are important for maintaining genetic connectivity between populations within heterogeneous landscapes. However, using landscape genetics in poorly understood species presents a number of challenges, namely, limited life history information for the focal population and spatially biased sampling. Both obstacles can reduce power in statistics, particularly in individual-based studies. In this study, we genotyped 233 American badgers in Wisconsin at 12 microsatellite loci to identify alternative statistical approaches that can be applied to poorly understood species in an individual-based framework. Badgers are protected in Wisconsin owing to an overall lack in life history information, so our study utilized partial redundancy analysis (RDA) and spatially lagged regressions to quantify how three landscape factors (Wisconsin River, Ecoregions and land cover) impacted gene flow. We also performed simulations to quantify errors created by spatially biased sampling. Statistical analyses first found that geographic distance was an important influence on gene flow, mainly driven by fine-scale positive spatial autocorrelations. After controlling for geographic distance, both RDA and regressions found that Wisconsin River and Agriculture were correlated with genetic differentiation. However, only Agriculture had an acceptable type I error rate (3-5%) to be considered biologically relevant. Collectively, this study highlights the benefits of combining robust statistics and error assessment via simulations and provides a method for hypothesis testing in individual-based landscape genetics.

show abstract

“…figure 1c). We simulated genotypes in CDPOP 1.2.21 [44], which incorporates landscape-resistance surfaces from CIR-CUITSCAPE and allows resistance to change during the simulation.…”

Section: (G) Simulation Experimentsmentioning

confidence: 99%

Dispersal responses override density effects on genetic diversity during post-disturbance succession

et al. 2016

Self Cite

View full text Add to dashboard Cite

Dispersal fundamentally influences spatial population dynamics but little is known about dispersal variation in landscapes where spatial heterogeneity is generated predominantly by disturbance and succession. We tested the hypothesis that habitat succession following fire inhibits dispersal, leading to declines over time in genetic diversity in the early successional gecko Nephrurus stellatus. We combined a landscape genetics field study with a spatially explicit simulation experiment to determine whether successional patterns in genetic diversity were driven by habitat-mediated dispersal or demographic effects (declines in population density leading to genetic drift). Initial increases in genetic structure following fire were likely driven by direct mortality and rapid population expansion. Subsequent habitat succession increased resistance to gene flow and decreased dispersal and genetic diversity in N. stellatus. Simulated changes in population density alone did not reproduce these results. Habitat-mediated reductions in dispersal, combined with changes in population density, were essential to drive the field-observed patterns. Our study provides a framework for combining demographic, movement and genetic data with simulations to discover the relative influence of demography and dispersal on patterns of landscape genetic structure. Our results suggest that succession can inhibit connectivity among individuals, opening new avenues for understanding how disturbance regimes influence spatial population dynamics.

show abstract

cdpop: A spatially explicit cost distance population genetics program

Cited by 214 publications

References 15 publications

Towards modelling persistence of woodland birds: the role of genetics

Towards modelling persistence of woodland birds: the role of genetics

Fine-scale landscape genetics of the American badger (Taxidea taxus): disentangling landscape effects and sampling artifacts in a poorly understood species

Dispersal responses override density effects on genetic diversity during post-disturbance succession

Contact Info

Product

Resources

About