Reconciling empirical interactions and species coexistence

Coexistence in ecological communities is governed largely by the nature and intensity of species interactions. Countless studies have proposed methods to infer these interactions from empirical data, yet models parameterised using such data often fail to recover observed coexistence patterns. Here, we propose a method to reconcile empirical parameterisations of community dynamics with species‐abundance data, ensuring that the predicted equilibrium is consistent with the observed abundance distribution. To illustrate the approach, we explore two case studies: an experimental freshwater algal community and a long‐term time series of displacement in an intertidal community. We demonstrate how our method helps recover observed coexistence patterns, capture the core dynamics of the system, and, in the latter case, predict the impacts of experimental extinctions. Collectively, these results demonstrate an intuitive approach for reconciling observed and empirical data, improving our ability to explore the links between species interactions and coexistence in natural systems.     

Trophic interaction modifications: an empirical and theoretical framework

Consumer–resource interactions are often influenced by other species in the community. At present these ‘trophic interaction modifications’ are rarely included in ecological models despite demonstrations that they can drive system dynamics. Here, we advocate and extend an approach that has the potential to unite and represent this key group of non‐trophic interactions by emphasising the change to trophic interactions induced by modifying species. We highlight the opportunities this approach brings in comparison to frameworks that coerce trophic interaction modifications into pairwise relationships. To establish common frames of reference and explore the value of the approach, we set out a range of metrics for the ‘strength’ of an interaction modification which incorporate increasing levels of contextual information about the system. Through demonstrations in three‐species model systems, we establish that these metrics capture complimentary aspects of interaction modifications. We show how the approach can be used in a range of empirical contexts; we identify as specific gaps in current understanding experiments with multiple levels of modifier species and the distributions of modifications in networks. The trophic interaction modification approach we propose can motivate and unite empirical and theoretical studies of system dynamics, providing a route to confront ecological complexity.     

Dissecting genetic networks underlying complex phenotypes: the theoretical framework

Great progress has been made in genetic dissection of quantitative trait variation during the past two decades, but many studies still reveal only a small fraction of quantitative trait loci (QTLs), and epistasis remains elusive. We integrate contemporary knowledge of signal transduction pathways with principles of quantitative and population genetics to characterize genetic networks underlying complex traits, using a model founded upon one-way functional dependency of downstream genes on upstream regulators (the principle of hierarchy) and mutual functional dependency among related genes (functional genetic units, FGU). Both simulated and real data suggest that complementary epistasis contributes greatly to quantitative trait variation, and obscures the phenotypic effects of many 'downstream' loci in pathways. The mathematical relationships between the main effects and epistatic effects of genes acting at different levels of signaling pathways were established using the quantitative and population genetic parameters. Both loss of function and "co-adapted" gene complexes formed by multiple alleles with differentiated functions (effects) are predicted to be frequent types of allelic diversity at loci that contribute to the genetic variation of complex traits in populations. Downstream FGUs appear to be more vulnerable to loss of function than their upstream regulators, but this vulnerability is apparently compensated by different FGUs of similar functions. Other predictions from the model may account for puzzling results regarding responses to selection, genotype by environment interaction, and the genetic basis of heterosis.     

A conceptual framework for studying the strength of plant–animal mutualistic interactions

The strength of species interactions influences strongly the structure and dynamics of ecological systems. Thus, quantifying such strength is crucial to understand how species interactions shape communities and ecosystems. Although the concepts and measurement of interaction strength in food webs have received much attention, there has been comparatively little progress in the context of mutualism. We propose a conceptual scheme for studying the strength of plant–animal mutualistic interactions. We first review the interaction strength concepts developed for food webs, and explore how these concepts have been applied to mutualistic interactions. We then outline and explain a conceptual framework for defining ecological effects in plant–animal mutualisms. We give recommendations for measuring interaction strength from data collected in field studies based on a proposed approach for the assessment of interaction strength in plant–animal mutualisms. This approach is conceptually integrative and methodologically feasible, as it focuses on two key variables usually measured in field studies: the frequency of interactions and the fitness components influenced by the interactions.     

Using the quantitative genetic threshold model for inferences between and within species

Sewall Wright's threshold model has been used in modelling discrete traits that may have a continuous trait underlying them, but it has proven difficult to make efficient statistical inferences with it. The availability of Markov chain Monte Carlo (MCMC) methods makes possible likelihood and Bayesian inference using this model. This paper discusses prospects for the use of the threshold model in morphological systematics to model the evolution of discrete all-or-none traits. There the threshold model has the advantage over 0/1 Markov process models in that it not only accommodates polymorphism within species, but can also allow for correlated evolution of traits with far fewer parameters that need to be inferred. The MCMC importance sampling methods needed to evaluate likelihood ratios for the threshold model are introduced and described in some detail.     

Comparison of RFLP and RAPD markers to estimating genetic relationships within and among cruciferous species

Restriction fragment length polymorphism (RFLP) and random amplified polymorphic DNA (RAPD) markers are being used widely for evaluating genetic relationships of crop germplasm. Differences in the properties of these two markers could result in different estimates of genetic relationships among some accessions. Nuclear RFLP markers detected by genomic DNA and cDNA clones and RAPD markers were compared for evaluating genetic relationships among 18 accessions from six cultivated Brassica species and one accession from Raphanus sativus. Based on comparisons of genetic-similarity matrices and cophenetic values, RAPD markers were very similar to RFLP markers for estimating intraspecific genetic relationships; however, the two marker types gave different results for interspecific genetic relationships. The presence of amplified mitochondrial and chloroplast DNA fragments in the RAPD data set did not appear to account for differences in RAPD- and RFLP-based dendrograms. However, hybridization tests of RAPD fragments with similar molecular weights demonstrated that some fragments, scored as identical, were not homologous. In all these cases, the differences occurred at the interspecific level. Our results suggest that RAPD data may be less reliable than RFLP data when estimating genetic relationships of accessions from more than one species.     

Protein-protein interactions more conserved within species than across species

Experimental high-throughput studies of protein-protein interactions are beginning to provide enough data for comprehensive computational studies. Today, about ten large data sets, each with thousands of interacting pairs, coarsely sample the interactions in fly, human, worm, and yeast. Another about 55,000 pairs of interacting proteins have been identified by more careful, detailed biochemical experiments. Most interactions are experimentally observed in prokaryotes and simple eukaryotes; very few interactions are observed in higher eukaryotes such as mammals. It is commonly assumed that pathways in mammals can be inferred through homology to model organisms, e.g. the experimental observation that two yeast proteins interact is transferred to infer that the two corresponding proteins in human also interact. Two pairs for which the interaction is conserved are often described as interologs. The goal of this investigation was a large-scale comprehensive analysis of such inferences, i.e. of the evolutionary conservation of interologs. Here, we introduced a novel score for measuring the overlap between protein-protein interaction data sets. This measure appeared to reflect the overall quality of the data and was the basis for our two surprising results from our large-scale analysis. Firstly, homology-based inferences of physical protein-protein interactions appeared far less successful than expected. In fact, such inferences were accurate only for extremely high levels of sequence similarity. Secondly, and most surprisingly, the identification of interacting partners through sequence similarity was significantly more reliable for protein pairs within the same organism than for pairs between species. Our analysis underlined that the discrepancies between different datasets are large, even when using the same type of experiment on the same organism. This reality considerably constrains the power of homology-based transfer of interactions. In particular, the experimental probing of interactions in distant model organisms has to be undertaken with some caution. More comprehensive images of protein-protein networks will require the combination of many high-throughput methods, including in silico inferences and predictions. http://www.rostlab.org/results/2006/ppi_homology/     

The species pool concept as a framework for studying patterns of plant diversity

Co‐existence theories fail to adequately explain observed community patterns (diversity and composition) because they mainly address local extinctions. For a more complete understanding, the regional processes responsible for species formation and geographic dispersal should also be considered. The species pool concept holds that local variation in community patterns is dependent primarily on the availability of species, which is driven by historical diversification and dispersal at continental and landscape scales. However, empirical evidence of historical effects is limited. This slow progress can be attributed to methodological difficulties in determining the characteristics of historical species pools and how they contributed to diversity patterns in contemporary landscapes. A role of landscape‐scale dispersal limitation in determining local community patterns has been demonstrated by numerous seed addition experiments. However, disentangling general patterns of dispersal limitation in communities still requires attention. Distinguishing habitat‐specific species pools can help to meet both applied and theoretical challenges. In conservation biology, the use of absolute richness may be uninformative because the size of species pools varies between habitats. For characterizing the dynamic state of individual communities, biodiversity relative to species pools provides a balanced way of assessing communities in different habitats. Information about species pools may also be useful when studying community assembly rules, because it enables a possible mechanism of trait convergence (habitat filtering) to be explicitly assessed. Empirical study of the role of historic effects and dispersal on local community patterns has often been restricted due to methodological difficulties in determining habitat‐specific species pools. However, accumulating distributional, ecological and phylogenetic information, as well as use of appropriate model systems (e.g. archipelagos with known biogeographic histories) will allow the species pool concept to be applied effectively in future research.     

Comparison of crossability, RAPD, SDS-PAGE and morphological markers for revealing genetic relationships within and among Lens species

The phylogenetic relationships among (sub)-species in the genus Lens have been reviewed based on recent published reports. There was both a substantial level of agreement and disagreement between reports based on different analytical procedures and different plant germ plasms. Lens culinaris ssp. orientalis appeared as the wild progenitor of the cultivated lentils. A gene flow from L. odemensis and L. ervoides during lentil crop evolution was suggested. Morphological characters (quantitative and qualitative) showed a different taxonomic pattern in the genus Lens. The use of nuclear and biochemical markers (RFLPs, RAPDs, seed-protein electrophoresis) appeared to be the most consistent and reliable methods for determining genetic relationships. It is suggested that these techniques be used in combination for taxonomic analysis of the genus Lens.     

EST-SSR development from 5 Lactuca species and their use in studying genetic diversity among L. serriola biotypes

Prickly lettuce (Lactuca serriola L.) is a problematic weed of Pacific Northwest and recently developed resistance to the auxinic herbicide 2,4-D. There are no publically available simple sequence repeat (SSR) markers to tag 2,4-D resistance genes in L. serriola. Therefore, a study was conducted to develop SSR markers from expressed sequence tags (ESTs) of 5 Lactuca species. A total of 15,970 SSRs were identified among 57,126 EST assemblies belonging to 5 Lactuca species. SSR-containing ESTs (SSR-ESTs) ranged from 6.23% to 7.87%, and SSR densities ranged from 1.28 to 2.51 kb(-1) among the ESTs of 5 Lactuca species. Trinucleotide repeats were the most abundant SSRs detected during the study. As a representative sample, 45 ESTs carrying class I SSRs (≥ 20 nucleotides) were selected for designing primers and were also searched against the dbEST entries for L. sativa and Helianthus annuus (≤ 10(-50); score ≥ 100). In silico analysis of 45 SSR-ESTs showed 82% conservation across species and 68% conservation across genera. Primer pairs synthesized for the above 45 EST-SSRs were used to study genetic diversity among a collection of 22 L. serriola biotypes. Comparison of the resultant dendrogram to that developed using phenotypic evaluation of the same subset of lines showed limited correspondence. Taken together, this study reported a collection of useful SSR markers for L. serriola, confirmed transferability of these markers within and across genera, and demonstrated their usefulness in studying genetic diversity.     

Planning for optimal conservation of geographical genetic variability within species

Systematic Conservation Planning (SCP) involves a series of steps that should be accomplished to determine the most cost-effective way to invest in conservation action. Although SCP has been usually applied at the species level (or hierarchically higher), it is possible to use alleles from molecular analyses at the population level as basic units for analyses. Here we demonstrate how SCP procedures can be used to establish optimum strategies for in situ and ex situ conservation of a single species, using Dipteryx alata (a Fabaceae tree species widely distributed and endemics to Brazilian Cerrado) as a case study. Data for the analyses consisted in 52 alleles from eight microsatellite loci coded for a total of 644 individual trees sampled in 25 local populations throughout species’ geographic range. We found optimal solutions in which seven local populations are the smallest set of local populations of D. alata that should be conserved to represent the known genetic diversity. Combining these several solutions allowed estimating the relative importance of the local populations for conserving all known alleles, taking into account the current land-use patterns in the region. A germplasm collection for this species already exists, so we also used SCP approach to identify the smallest number of populations that should be further collected in the field to complement the existing collection, showing that only four local populations should be sampled for optimizing the species ex situ representation. The initial application of the SCP methods to genetic data showed here can be a useful starting point for methodological and conceptual improvements and may be a first important step towards a comprehensive and balanced quantitative definition of conservation goals, shedding light to new possibilities for in situ and ex situ designs within species.     

Effect of balancing selection on spatial genetic structure within populations: theoretical investigations on the self-incompatibility locus and empirical studies in Arabidopsis halleri

The effect of selection on patterns of genetic structure within and between populations may be studied by contrasting observed patterns at the genes targeted by selection with those of unlinked neutral marker loci. Local directional selection on target genes will produce stronger population genetic structure than at neutral loci, whereas the reverse is expected for balancing selection. However, theoretical predictions on the intensity of this signal under precise models of balancing selection are still lacking. Using negative frequency-dependent selection acting on self-incompatibility systems in plants as a model of balancing selection, we investigated the effect of such selection on patterns of spatial genetic structure within a continuous population. Using numerical simulations, we tested the effect of the type of self-incompatibility system, the number of alleles at the self-incompatibility locus and the dominance interactions among them, the extent of gene dispersal, and the immigration rate on spatial genetic structure at the selected locus and at unlinked neutral loci. We confirm that frequency-dependent selection is expected to reduce the extent of spatial genetic structure as compared to neutral loci, particularly in situations with low number of alleles at the self-incompatibility locus, high frequency of codominant interactions among alleles, restricted gene dispersal and restricted immigration from outside populations. Hence the signature of selection on spatial genetic structure is expected to vary across species and populations, and we show that empirical data from the literature as well as data reported here on three natural populations of the herb Arabidopsis halleri confirm these theoretical results.     

Patterns of genetic variation within and between Gibbon species

Gibbons are small, arboreal, highly endangered apes that are understudied compared with other hominoids. At present, there are four recognized genera and approximately 17 species, all likely to have diverged from each other within the last 5-6 My. Although the gibbon phylogeny has been investigated using various approaches (i.e., vocalization, morphology, mitochondrial DNA, karyotype, etc.), the precise taxonomic relationships are still highly debated. Here, we present the first survey of nuclear sequence variation within and between gibbon species with the goal of estimating basic population genetic parameters. We gathered ~60 kb of sequence data from a panel of 19 gibbons representing nine species and all four genera. We observe high levels of nucleotide diversity within species, indicative of large historical population sizes. In addition, we find low levels of genetic differentiation between species within a genus comparable to what has been estimated for human populations. This is likely due to ongoing or episodic gene flow between species, and we estimate a migration rate between Nomascus leucogenys and N. gabriellae of roughly one migrant every two generations. Together, our findings suggest that gibbons have had a complex demographic history involving hybridization or mixing between diverged populations.     

Population mixing and the adaptive divergence of quantitative traits in discrete populations: a theoretical framework for empirical tests

Empirical tests for the importance of population mixing in constraining adaptive divergence have not been well grounded in theory for quantitative traits in spatially discrete populations. We develop quantitative-genetic models to examine the equilibrium difference between two populations that are experiencing different selective regimes and exchanging individuals. These models demonstrate that adaptive divergence is negatively correlated with the rate of population mixing (m, most strongly so when m is low), positively correlated with the difference in phenotypic optima between populations, and positively correlated with the amount of additive genetic variance (G, most strongly so when G is low). The approach to equilibrium is quite rapid (fewer than 50 generations for two populations to evolve 90% of the distance to equilibrium) when either heritability or mixing are not too low (h2 > 0.2 or m > 0.05). The theory can be used to aid empirical tests that: (1) compare observed divergence to that predicted using estimates of population mixing, additive genetic variance/covariance, and selection; (2) test for a negative correlation between population mixing and adaptive divergence across multiple independent population pairs; and (3) experimentally manipulate the rate of mixing. Application of the first two of these approaches to data from two well-studied natural systems suggests that population mixing has constrained adaptive divergence for color patterns in Lake Erie water snakes (Nerodia sipedon), but not for trophic traits in sympatric pairs of benthic and limnetic stickleback (Gasterosteus aculeatus). The theoretical framework we outline should provide an improved basis for future empirical tests of the role of population mixing in adaptive divergence.     

Comparison of gene flow among species that occur within the same geographic locations versus gene flow among populations within species reveals introgression among several Elymus species

One of the challenges in evolutionary biology is to understand the evolution of speciation with incomplete reproductive isolation as many taxa have continued gene flow both during and after speciation. Comparison of population structure between sympatric and allopatric populations can reveal specific introgression and determine if introgression occurs in a unidirectional or bidirectional manner. Simple sequence repeat markers were used to characterize sympatric and allopatric population structure of plant species, Elymus alaskanus (Scribn. and Merr.) Löve, E. caninus L., E. fibrosus (Schrenk) Tzvel., and E. mutabilis (Drobov) Tzvelev. Our results showed that genetic diversity (H_E) at species level is E. caninus (0.5355) > E. alaskanus (0.4511) > E. fibrosus (0.3924) > E. mutabilis (0.3764), suggesting that E. caninus and E. alaskanus are more variable than E. fibrosus and E. mutabilis. Gene flow between species that occurs within the same geographic locations versus gene flow between populations within species was compared to provide evidence of introgression. Our results indicated that gene flow between species that occur within the same geographic location is higher than that between populations within species, suggesting that gene flow resulting from introgressive hybridization might have occurred among the sympatric populations of these species, and may play an important role in partitioning of genetic diversity among and within populations. The migration rate from E. fibrosus to E. mutabilis is highest (0.2631) among the four species studied. Asymmetrical rates of gene flow among four species were also observed. The findings highlight the complex evolution of these four Elymus species.     

On the length distribution of external branches in coalescence trees: genetic diversity within species

Let Z(n) denote the length of an external branch, chosen at random from a Kingman n-coalescent. Based on a recursion for the distribution of Z(n), we show that nZ(n) converges in distribution, as n tends to infinity, to a non-negative random variable Z with density x--> 8/(2+x)(3), x>or=0. This result facilitates the study of the time to the most recent common ancestor of a randomly chosen individual and its closest relative in a given population. This time span also reflects the maximum relatedness between a single individual and the rest of the population. Therefore, it measures the uniqueness of a random individual, a central characteristic of the genetic diversity of a population.