Been working on a lexicographic analysis of ‘Sustainability’ as published by the journals PNAS and Sustainability. Here are the stemmed word forms for 366 published articles represented as a hierarchical clustering. The wordclouds represent the top 10 word stems per group.
For a scientific discipline to be interdisciplinary it must satisfy two conditions; it must consist of contributions from at least two existing disciplines and it must be able to provide insights, through this interaction, that neither progenitor discipline could address. In this paper, I examine the complete body of peer-reviewed literature self-identified as landscape genetics using the statistical approaches of text mining and natural language processing. The goal here is to quantify the kinds of questions being addressed in landscape genetic studies, the ways in which questions are evaluated mechanistically, and how they are differentiated from the progenitor disciplines of landscape ecology and population genetics. I then circumscribe the main factions within published landscape genetic papers examining the extent to which emergent questions are being addressed and highlighting a deep bifurcation between existing individual- and population-based approaches. I close by providing some suggestions on where theoretical and analytical work is needed if landscape genetics is to serve as a real bridge connecting evolution and ecology sensu lato.
Pollen-mediated gene flow is a major driver of spatial genetic structure in plant populations. Both individual plant characteristics and site-specific features of the landscape can modify the perceived attractiveness of plants to their pollinators and thus play an important role in shaping spatial genetic variation. Most studies of landscape-level genetic connectivity in plants have focused on the effects of interindividual distance using spatial and increasingly ecological separation, yet have not incorporated individual plant characteristics or other at-site ecological variables. Using spatially explicit simulations, we first tested the extent to which the inclusion of at-site variables influencing local pollination success improved the statistical characterization of genetic connectivity based upon examination of pollen pool genetic structure. The addition of at-site characteristics provided better models than those that only considered interindividual spatial distance (e.g. IBD). Models parameterized using conditional genetic covariance (e.g. population graphs) also outperformed those assuming panmixia. In a natural population of Cornus florida L. (Cornaceae), we showed that the addition of at-site characteristics (clumping of primary canopy opening above each maternal tree and maternal tree floral output) provided significantly better models describing gene flow than models including only between-site spatial (IBD) and ecological (isolation by resistance) variables. Overall, our results show that including interindividual and local ecological variation greatly aids in characterizing landscape-level measures of contemporary gene flow.
The Forest ecosystem genomics Research: supporTing Transatlantic Cooperation project (FoResTTraC) sponsored a workshop in August 2010 to evaluate the potential for using a landscape genomics approach for studying plant adaptation to the environment and the potential of local populations for coping with changing climate. This paper summarizes our discussions and articulates a vision of how we believe forest trees offer an unparalleled opportunity to address fundamental biological questions, as well as the application of landscape genomic methods complement traditional forest genetic approaches to provide critical information needed for natural resource management. In this paper, we will cover four topics. First, we begin by defining landscape genomics and briefly reviewing the unique situation for tree species in the application of this approach toward understanding plant adaptation to the environment. Second, we review traditional approaches in forest genetics for studying local adaptation and identifying loci underlying locally adapted phenotypes. Third, we present existing and emerging methods available for landscape genomic analyses. Finally, we briefly touch on how these approaches can aid in understanding practical topics such as management of tree populations facing climate change.
Ecologically interacting species may have phylogeographic histories that are shaped both by features of their abiotic landscape, and by biotic constraints imposed by their co-association. The Baja California peninsula provides an excellent opportunity to examine the influence of abiotic vs. biotic factors on patterns of diversity in plant-insect species. This is because past climatic and geological changes impacted the genetic structure of plants quite differently to that of co-distributed free-living animals (e.g., herpetofauna and small mammals). Thus, ‘plant-like’ patterns should be discernible in host-specific insect herbivores. Here we investigate the population history of a monophagous bark beetle, Araptus attenuatus, and consider drivers of phylogeographic patterns in light of previous work on its host plant, Euphorbia lomelii. Based on mitochondrial and nuclear markers, we found that the evolutionary history of A. attenuatus exhibits similarities to host plant that are attributable to both biotic and abiotic processes. Southward range expansion and recent colonization of continental Sonora peninsula appear to be unique to this taxon pair, and likely reflect influences of the host plant. On the other hand, abiotic factors with landscape-level influences on suites of co-distributed taxa, such as Plio- and Pleistocene-aged marine incursions in the region, also left genetic signatures in beetle populations. Superimposed on these similarities, bark beetle-specific patterns and processes were also evident. Taken together, this work illustrates that the evolutionary history of species-specific insect herbivores may represent a mosaic of influences, including, but not limited to, those imposed by the host plant.
Whether they are used to describe fitness, genome architecture or the spatial distribution of environmental variables, the concept of a landscape has figured prominently in our collective reasoning. The tradition of landscapes in evolutionary biology is one of fitness mapped onto axes defined by phenotypes or molecular sequence states. The characteristics of these landscapes depend on natural selection, which is structured across both genomic and environmental landscapes, and thus, the bridge among differing uses of the landscape concept (i.e. metaphorically or literally) is that of an adaptive phenotype and its distribution across geographical landscapes in relation to selective pressures. One of the ultimate goals of evolutionary biology should thus be to construct fitness landscapes in geographical space. Natural plant populations are ideal systems with which to explore the feasibility of attaining this goal, because much is known about the quantitative genetic architecture of complex traits for many different plant species. What is less known are the molecular components of this architecture. In this issue of Molecular Ecology, Parchman et al. (2012) pioneer one of the first truly genome-wide association studies in a tree that moves us closer to this form of mechanistic understanding for an adaptive phenotype in natural populations of lodgepole pine (Pinus contorta Dougl. ex Loud.).
The manner by which pollinators move across a landscape and their resulting preferences and/or avoidances of travel through particular habitat types can have a significant impact on plant population genetic structure and population-level connectivity. We examined the spatial genetic structure of the understory tree Cornus florida (Cornaceae) adults (NAdults = 452) and offspring (NOffspring = 736) across two mating events to determine the extent to which pollen pool genetic covariance is influenced by intervening forest architecture. Resident adults showed no spatial partitioning but genotypes were positively autocorrelated up to a distance of 35 m suggesting a pattern of restricted seed dispersal. In the offspring, selfing rates were small (sm = 0.035) whereas both biparental inbreeding (sb;open canopy = 0.16, sb;closed canopy = 0.11) and correlated paternity (rp;open canopy = 0.21, rp;closed canopy = 0.07) were significantly influenced by primary canopy opening above individual mothers. The spatial distribution of genetic covariance in pollen pool composition was quantified for each reproductive event using Pollination Graphs, a network method based upon multivariate conditional genetic covariance. The georeferenced graph topology revealed a significant positive relationship between genetic covariance and pollinator movement through C. florida canopies, a negative relationship with open primary canopy (e.g., roads under open canopies and fields with no primary canopy), and no relationship with either conifer or mixed hardwood canopy species cover. These results suggest that both resident genetic structure within stands and genetic connectivity between sites in C. florida populations are influenced by spatial heterogeneity of mating individuals and quality of intervening canopy cover.
Habitat fragmentation and landscape topology may influence the genetic structure and connectivity between natural populations. Six microsatellite loci were used to infer the population structure of 35 populations (N = 788) of the alpine Arabian burnet moth Reissita simonyi (Lepidoptera, Zygaenidae) in Yemen and Oman. Due to the patchy distribution of larval food plants, R. simonyi is not continuously distributed throughout the studied area and the two recognized subspecies of this endemic species (Reissita s. simonyi/R. s. yemenicola) are apparently discretely distributed. All microsatellites showed prevalence of null alleles and therefore a thorough investigation of the impact of null alleles on different population genetic parameters (FST, inbreeding coefficients, and Population Graph topologies) is given. In general, null alleles reduced genetic covariance and independence of allele frequencies resulting in a more connected genetic topology in Population Graphs and an overestimation of pairwise FST values and inbreeding coefficients. Despite the presence of null alleles, Population Graphs also showed a much higher genetic connectivity within subspecies (and lower genetic differentiation, via FST) than between; supporting existing taxonomic distinction. Partial Mantel tests showed that both geo- graphical distance and altitude were highly correlated with the observed distribution of genetic structure within R. simonyi. In conclusion, we identified geographical and altitudinal distances in R. simonyi as well as an intervening desert area to be the main factors for spatial genetic structure in this species and show that the taxonomic division into two subspecies is confirmed by genetic analysis.
Patterns of spatial genetic structure produced following the expansion of an invasive species into novel habitats reflect demographic processes that have shaped the genetic structure we see today. We examined 359 individuals from 23 populations over 370 km within the James River Basin of Virginia, USA as well as four populations outside of the basin. Population diversity levels and genetic structure was quantified using several analyses. Within the James River Basin there was evidence for three separate introductions and a zone of secondary contact between two distinct lineages suggesting a relatively recent expansion within the basin. Microstegium vimineum possesses a mixed-mating system advantageous to invasion and populations with low diversity were found suggesting a recent founder event and self-fertilization. However, surprisingly high levels of diversity were found in some populations suggesting that out-crossing does occur. Understanding how invasive species spread and the genetic consequences following expansion may provide insights into the cause of invasiveness and can ultimately lead to better management strategies for control and eradication.
Landscape genetics is a burgeoning field of interest that focuses on how site-specific factors influence the distribution of genetic variation and the genetic connectivity of individuals and populations. In this manuscript, we focus on two methodological extensions for landscape genetic analyses: the use of conditional genetic distance (cGD) derived from population networks and the utility of extracting potentially confounding effects caused by correlations between phylogeographic history and contemporary ecological factors. Individual-based simulations show that when describing the spatial distribution of genetic variation, cGD consistently outperforms the traditional genetic distance measure of linearized FST under both 1- and 2-dimensional stepping stone models and Cavalli-Sforza and Edward’s chord distance Dc in 1-dimensional landscapes. To show how to identify and extract the effects of phylogeographic history prior to embarking on landscape genetic analyses, we use nuclear genotypic data from the Sonoran desert succulent Euphorbia lomelii (Euphrobiaceae), for which a detailed phylogeographic history has previously been determined. For E. lomelii, removing the effect of phylogeographic history significantly influences our ability to infer both the identity and the relative importance of spatial and bio-climatic variables in subsequent landscape genetic analyses. We close by discussing the utility of cGD in landscape genetic analyses.
Background: A widely-used approach for screening nuclear DNA markers is to obtain sequence data and use bioinformatic algorithms to estimate which two alleles are present in heterozygous individuals. It is common practice to omit unresolved genotypes from downstream analyses, but the implications of this have not been investigated. We evaluated the haplotype reconstruction method implemented by PHASE in the context of phylogeographic applications. Empirical sequence datasets from five non-coding nuclear loci with gametic phase ascribed by molecular approaches were coupled with simulated datasets to investigate three key issues: (1) haplotype reconstruction error rates and the nature of inference errors, (2) dataset features and genotypic configurations that drive haplotype reconstruction uncertainty, and (3) impacts of omitting unresolved genotypes on levels of observed phylogenetic diversity and the accuracy of downstream phylogeographic analyses.
Results: We found that PHASE usually had very low false-positives (i.e., a low rate of confidently inferring haplotype pairs that were incorrect). The majority of genotypes that could not be resolved with high confidence included an allele occurring only once in a dataset, and genotypic configurations involving two low-frequency alleles were disproportionately represented in the pool of unresolved genotypes. The standard practice of omitting unresolved genotypes from downstream analyses can lead to considerable reductions in overall phylogenetic diversity that is skewed towards the loss of alleles with larger-than-average pairwise sequence divergences, and in turn, this causes systematic bias in estimates of important population genetic parameters.
Conclusions: A combination of experimental and computational approaches for resolving phase of segregating sites in phylogeographic applications is essential. We outline practical approaches to mitigating potential impacts of computational haplotype reconstruction on phylogeographic inferences. With targeted application of laboratory procedures that enable unambiguous phase determination via physical isolation of alleles from diploid PCR products, relatively little investment of time and effort is needed to overcome the observed biases.
Background: Despite constant progress, cancer remains the second leading cause of death in the United States. The ability of tumors to metastasize is central to this dilemma, as many studies demonstrate successful treatment correlating to diagnosis prior to cancer spread. Hence a better understanding of cancer invasiveness and metastasis could provide critical insight.
Presentation of the hypothesis: We hypothesize that a systems biology-based comparison of cancer invasiveness and suburban sprawl will reveal similarities that are instructive.
Testing the hypothesis: We compare the structure and behavior of invasive cancer to suburban sprawl development. While these two systems differ vastly in dimension, they appear to adhere to scale-invariant laws consistent with invasive behavior in general. We demonstrate that cancer and sprawl have striking similarities in their natural history, initiating factors, patterns of invasion, vessel distribution and even methods of causing death.
Implications of the hypothesis: We propose that metastatic cancer and suburban sprawl provide striking analogs in invasive behavior, to the extent that conclusions from one system could be predictive of behavior in the other. We suggest ways in which this model could be used to advance our understanding of cancer biology and treatment.
The distribution of genetic variation within species is the result of both historical and ongoing demographic and evolutionary processes. Here we examine how genetic variation in Euphorbia lomelii (Euphorbaceae) among populations in Baja Mexico to understand how region-wide historical processes may have influenced this species. Specifically, we examined how the formation of the Sea of Cortéz, separating mainland and peninsular populations, and range expansion caused by Post Pleistocene climate change have influenced genetic variation. Samples were obtained from 37 sites in Baja California and mainland Sonora with a total of 324 individuals genotyped using six nuclear DNA markers. Analysis of genetic structure showed that while there was considerable differentiation among sites (ΦST=0.19) there was no significant difference between mainland and peninsular populations. The genetic structure of E. lomelii also has a gradual change with a northward reduction in heterozygosity, most likely caused by the relatively rapid range expansion during the current interglacial period. This research is important in understanding how genetic structure is influenced by historical processes that have operated on species in this region.
To examine the generality of population-level impacts of ancient vicariance identified for numerous arid-adapted animal taxa along the Baja peninsula, we tested phylogeographical hypotheses in a similarly distributed desert plant, Euphorbia lomelii (Euphorbiaceae). In light of fossil data indicating marked changes in the distributions of Baja floristic assemblages throughout the Holocene and earlier, we also examined evidence for range expansion over more recent temporal scales. Two classes of complementary analytical approaches — hypothesis-testing and hypothesis-generating — were used to exploit phylogeographical signal from chloroplast DNA sequence data and genotypic data from six codominant nuclear intron markers. Sequence data are consistent with a scenario of mid-peninsular vicariance originating c. 1 million years ago (Ma). Alternative vicariance scenarios representing earlier splitting events inferred for some animals (e.g. Isthmus of La Paz inundation, c. 3 Ma; Sea of Cortez formation, c. 5 Ma) were rejected. Nested clade phylo- geographical analysis corroborated coalescent simulation-based inferences. Nuclear markers broadened the temporal spectrum over which phylogeographical scenarios could be addressed, and provided strong evidence for recent range expansions along the north– south axis of the Baja peninsula. In contrast to previous plant studies in this region, however, the expansions do not appear to have been in a strictly northward direction. These findings contribute to a growing appreciation of the complexity of organismal responses to past climatic and geological changes — even when taxa have evolved in the same landscape context.
We report eight new co-dominant nuclear markers for population genetics of the bark beetle Araptus attenuatus Wood. Several loci include introns from low- copy genes, and four cross-amplify in one or more related genera. The markers show moderate levels of polymorphism (2–19 alleles per locus), and no loci showed significant deviations from Hardy–Weinberg or linkage equilibrium across both of the two populations examined, consistent with Mendelian inheritance patterns.
The analysis of genetic marker data is increasingly being conducted in the context of the spatial arrangement of strata (e.g. populations) necessitating a more flexible set of analysis tools. GeneticStudio consists of four interacting programs: (i) Geno a spreadsheet-like interface for the analysis of spatially explicit marker-based genetic variation; (ii) Graph software for the analysis of Population Graph and network topologies, (iii) Manteller, a general purpose for matrix analysis program; and (iv) SNPFinder, a program for identifying single nucleotide polymorphisms. The GeneticStudio suite is available as source code as well as binaries for OSX and Windows and is distributed under the GNU General Public License.
A recent commentary in Molecular Ecology by Petit (2008) paints a rather grim picture of the utility of nested clade phylogeographical analysis (NCPA) for inferring population history. Drawing on simulation studies based on single locus data sets, including the recent work by Panchal & Beaumont (2007), the potential fallibility of NCPA was characterized as being so dire that the method should be abandoned until further evidence in support of its legitimacy emerges. Here, we reconsider the arguments presented by Petit in light of practical approaches for validating or strengthening inferences drawn from NCPA. As with any method that attempts to distinguish processes and events that shaped spatial-genetic structuring throughout complex evolutionary histories of natural populations, we propose that treatment of NCPA inferences should be set in the context of corroborating evidence (or lack thereof) that support those inferences. Indeed, results from computer simulation, studies lend no support to the idea that NCPA should not be employed for generating plausible hypotheses (i.e. consistent with species biology and landscape history) that can be further tested using other methods. Moreover, cross-validation of NCPA inferences via assessment of multiple independent loci, complementary analyses, and/or prior expectations, should at least partly — perhaps considerably — counter high false-positive rates reported for some inferences. NCPA uniquely offers the ability to explore patterns relating to complex, historical scenarios: an over-reaction to Panchal & Beaumont (2007) should not precipitate throwing out an approach currently with no computationally feasible substitute.
We developed seven nuclear intron markers for Euphorbia lomelii. New exon-primed intron-crossing (EPIC) oligonucleotides were used for initial amplification and sequencing, then locus-specific primers and restriction fragment length polymorphism genotyping assays were designed. Loci showed no significant deviation from Hardy–Weinberg and linkage equilibrium, and they cross-amplify in at least three congeneric species.