Stochastic simulation software that simultaneously model genetic, population and environmental processes can inform many topics in molecular ecology. These include forecasting species and community ...response to environmental change, inferring dispersal ecology, revealing cryptic mating, quantifying past population dynamics, assessing in situ management options and monitoring neutral and adaptive biodiversity change. Advances in population demographic–genetic simulation software, especially with respect to individual life history, landscapes and genetic processes, are transforming and expanding the ways that molecular data can be used. The aim of this review is to explain the roles that such software can play in molecular ecology studies (whether as a principal component or a supporting function) so that researchers can decide whether, when and precisely how simulations can be incorporated into their work. First, I use seven case studies to demonstrate how simulations are employed, their specific advantage/necessity and what alternative or complementary (nonsimulation) approaches are available. I also explain how simulations can be integrated with existing spatial, environmental, historical and genetic data sets. I next describe simulation features that may be of interest to molecular ecologists, such as spatial and behavioural considerations and species' interactions, to provide guidance on how particular simulation capabilities can serve particular needs. Lastly, I discuss the prospect of simulation software in emerging challenges (climate change, biodiversity monitoring, population exploitation) and opportunities (genomics, ancient DNA), in order to emphasize that the scope of simulation‐based work is expanding. I also suggest practical considerations, priorities and elements of best practice. This should accelerate the uptake of simulation approaches and firmly embed them as a versatile tool in the molecular ecologist's toolbox.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
•Genetic diversity is vital for continued survival of species and ecosystems.•Disappearing diversity from populations is motivating conservation seed collections.•We test how the spatial arrangement ...of sampled populations affects collections.•We also test how the diversity in the pollen pool affects collections.•Our results offer new realistic guidelines for conservation seed collections.
As habitat loss accelerates, there is pressing need to preserve plant genetic diversity in ex situ conservation collections. Population structure (i.e. subdivision), which is common in plants, may be an important consideration when planning such collections because it results in locally restricted alleles or traits, which have high conservation, ecological, or economic value. Nonetheless, common protocols for ex situ collections do not consider population structure. To help inform collection decisions, we utilize computer simulations with different levels of realistic hierarchical population structure to evaluate the expected performance of an array of sample sizes and several spatial distributions of sampled populations. We quantify how population structure affects the expected probability of capturing alleles (especially rare alleles). We also test the effect of family-level structure due to pollen pool composition (e.g., sibling clusters). Our findings suggest that when range-wide population structure exists, the spatial distribution of sampled populations is crucial: sampling one population per region (dispersed sampling) captured up to 175% more alleles than sampling all populations in one region (constrained sampling), and nearly as much as sampling all existing populations. The spatial effect is strongest for poorly-connected (low gene flow) species. Under realistic population structure, moderate sampling (25–30 individuals per population) from few but widely-spaced populations performs optimally; this differs from previous recommended guidelines that do not consider structure. There is smaller effect of the pollen pool composition on collection performance. We conclude that seed collection plans should incorporate spatial considerations, especially for poorly-connected taxa. Our simulation approach can be extended to particular species and other spatial patterns. We use the butternut tree as a case study for collection planning.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Many species on endangered species lists such as the IUCN Red List (RL) are categorized using demographic factors such as numbers of mature individuals. Genetic factors are not currently used in the ...RL even though their explicit consideration, including effective population size (
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) and expected heterozygosity-loss (
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-loss), could improve the assessment of extinction risk. Here, we consider the estimation of
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and
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-loss in the context of RL species. First, we investigate the reporting of number of mature individuals for RL Endangered species, which is needed to estimate
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and
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-loss. We found 77% of species assessments studied here did not report methods used to estimate the number of mature adults, and that these assessments rarely report other important determinants of
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(e.g., sex ratio, variance in family size). We therefore applied common rules of thumb to estimate
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, and found that
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was likely < 50 for at least 25% of the 170 RL Endangered species studied here. We also estimated mean expected
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-loss for these species over the next 100 years, and found it to be 9–29%. These estimates of high
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-loss and low
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suggest that some species listed as Endangered likely warrant listing as Critically Endangered if genetic considerations were included. We recommend that RL and other assessment frameworks (i) report methods used for estimating the number of mature adults, (ii) include standardized information on species traits that influence
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to facilitate
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estimation, and (iii) consider using concepts like
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and heterozygosity-loss in risk assessments.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
After the last glacial cycle, temperate European trees migrated northward, experiencing genetic bottlenecks and founder effects, which left high haplotype endemism in southern populations and clines ...in genetic diversity northward. These patterns are thought to be ubiquitous across temperate forests, and are therefore used to anticipate the potential genetic consequences of future warming. We compared existing and new phylogeographic data sets (chloroplast DNA) from 14 woody taxa in Eastern North America (ENA) to data sets from 21 ecologically similar European species to test for common impacts of Quaternary climate swings on genetic diversity across diverse taxa and between continents. Unlike their European counterparts, ENA taxa do not share common southern centres of haplotype endemism and they generally maintain high genetic diversity even at their northern range limits. Differences between the genetic impacts of Quaternary climate cycles across continents suggest refined lessons for managing genetic diversity in today's warming world.
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Uncovering the genetic and evolutionary basis of local adaptation is a major focus of evolutionary biology. The recent development of cost-effective methods for obtaining high-quality genome-scale ...data makes it possible to identify some of the loci responsible for adaptive differences among populations. Two basic approaches for identifying putatively locally adaptive loci have been developed and are broadly used: one that identifies loci with unusually high genetic differentiation among populations (differentiation outlier methods) and one that searches for correlations between local population allele frequencies and local environments (genetic-environment association methods). Here, we review the promises and challenges of these genome scan methods, including correcting for the confounding influence of a species’ demographic history, biases caused by missing aspects of the genome, matching scales of environmental data with population structure, and other statistical considerations. In each case, we make suggestions for best practices for maximizing the accuracy and efficiency of genome scans to detect the underlying genetic basis of local adaptation. With attention to their current limitations, genome scan methods can be an important tool in finding the genetic basis of adaptive evolutionary change.
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BFBNIB, NMLJ, NUK, PNG, SAZU, UL, UM, UPUK
We compare the two main classes of measures of population structure in genetics: (i) fixation measures such as FST, GST, and θ and (ii) allelic differentiation measures such as Jost's D and entropy ...differentiation. These two groups of measures quantify complementary aspects of population structure, which have no necessary relationship with each other. We focus especially on empirical aspects of population structure relevant to conservation analyses. At the empirical level, the first set of measures quantify nearness to fixation, while the second set of measures quantify relative degree of allelic differentiation. The two sets of measures do not compete with each other. Fixation measures are often misinterpreted as measures of allelic differentiation in conservation applications; we give examples and theoretical explanations showing why this interpretation can mislead. This misinterpretation has led to the mistaken belief that the absolute number of migrants determines allelic differentiation between demes when mutation rate is low; we show that in the finite island model, the absolute number of migrants determines nearness to fixation, not allelic differentiation. We show that a different quantity, the factor that controls Jost's D, is a good predictor of the evolution of the actual genetic divergence between demes at equilibrium in this model. We also show that when conservation decisions require judgments about differences in genetic composition between demes, allelic differentiation measures should be used instead of fixation measures. Allelic differentiation of fast‐mutating markers can be used to rank pairs or sets of demes according to their differentiation, but the allelic differentiation at coding loci of interest should be directly measured in order to judge its actual magnitude at these loci.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
The International Union for Conservation of Nature (IUCN) Red List is an important and widely used tool for conservation assessment. The IUCN uses information about a species’ range, population size, ...habitat quality and fragmentation levels, and trends in abundance to assess extinction risk. Genetic diversity is not considered, although it affects extinction risk. Declining populations are more strongly affected by genetic drift and higher rates of inbreeding, which can reduce the efficiency of selection, lead to fitness declines, and hinder species’ capacities to adapt to environmental change. Given the importance of conserving genetic diversity, attempts have been made to find relationships between red‐list status and genetic diversity. Yet, there is still no consensus on whether genetic diversity is captured by the current IUCN Red List categories in a way that is informative for conservation. To assess the predictive power of correlations between genetic diversity and IUCN Red List status in vertebrates, we synthesized previous work and reanalyzed data sets based on 3 types of genetic data: mitochondrial DNA, microsatellites, and whole genomes. Consistent with previous work, species with higher extinction risk status tended to have lower genetic diversity for all marker types, but these relationships were weak and varied across taxa. Regardless of marker type, genetic diversity did not accurately identify threatened species for any taxonomic group. Our results indicate that red‐list status is not a useful metric for informing species‐specific decisions about the protection of genetic diversity and that genetic data cannot be used to identify threat status in the absence of demographic data. Thus, there is a need to develop and assess metrics specifically designed to assess genetic diversity and inform conservation policy, including policies recently adopted by the UN's Convention on Biological Diversity Kunming‐Montreal Global Biodiversity Framework.
La diversidad genética y los estados de la Lista Roja de la UICN
Resumen
La Lista Roja de la Unión Internacional para la Conservación de la Naturaleza (UICN) es una importante herramienta de uso extendido para evaluar la conservación. La UICN utiliza datos sobre la distribución y tamaño poblacional de una especie, la calidad y niveles de fragmentación de su hábitat y sus tendencias de abundancia para valorar su riesgo de extinción, A pesar de que la diversidad genética afecta al riesgo de extinción, la UICN no la considera. La deriva génica y las tasas altas de endogamia afectan con mayor fuerza a las poblaciones en declinación, lo que puede reducir la eficiencia de la selección, derivar en la disminución de la aptitud y dificultar la capacidad de una especie de adaptarse ante el cambio ambiental. Se ha intentado encontrar la relación entre la diversidad genética y el estado en las listas rojas ya que su conservación es muy importante. Aun con lo anterior, no hay un consenso actual sobre si la diversidad genética está capturada en las categorías vigentes de la Lista Roja de la UICN de manera que sea informativa para la conservación. Para poder evaluar el poder predictivo de la correlación entre la diversidad genética y el estado en la Lista Roja de los vertebrados, sintetizamos trabajos previos y analizamos de nuevo los conjuntos de datos con base en tres tipos de información genética: ADN mitocondrial, microsatélites y genomas completos. Las especies con un estado de riesgo de extinción más alto fueron propensas a una diversidad genética más baja para todos los tipos de marcadores, aunque estas relaciones fueron débiles y variaron entre los taxones, lo cual es coherente con trabajos anteriores. Sin importar el tipo de marcador, la diversidad genética no fue un identificador certero de las especies amenazadas en ninguno de los grupos taxonómicos. Nuestros resultados indican que el estado de lista roja no es una medida útil para guiar las decisiones específicas por especie en relación con la protección de la diversidad genética. También indican que los datos genéticos no pueden usarse para identificar el estado de amenaza si no se tienen los datos demográficos. Por lo tanto, es necesario desarrollar y evaluar las medidas diseñadas específicamente para valorar la diversidad genética e informar las políticas de conservación, incluidas las que adoptó recientemente la ONU en el Convenio del Marco Mundial Kunming‐Montreal de la Diversidad Biológica.
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A vital component of conservation is to sample germplasm from wild populations for safeguarding ex situ (e.g., in seed banks, though the concept also applies to animals via cryopreservation or zoos). ...For decades, conservationists have commonly heeded a logically sound, but perhaps suboptimal, minimum sampling guideline- to sample from 50 individuals per population. Here, I demonstrate how sampling can be improved based on two considerations that are neglected in this common, simple guideline, and have not previously been tested. First, I consider a fundamental aspect of population biology- sharing of genetic material among populations through migration. Second, I consider a fundamental aspect of ex situ collections maintenance- loss of plants through germination failure, disease, and active use (e.g., research, seed exchanges). I first simulate metapopulations with a wide range of migration rates, population sizes, numbers of populations and demographic (i.e., bottleneck) histories. Then I determine minimum sampling to preserve a sufficient number of allele copies to account for various degrees of collection attrition. My results show that sampling seed from approximately 200 to 300 individuals in total across a species' geographic range may suffice for a wide range of plant population systems, if all seeds germinate and produce plants that survive in perpetuity. However, to compensate for expected losses over time, sampling should be increased by a factor closely related to the expected loss rate, meaning that a robust minimum collection for ex situ gene conservation will often be 1000 individuals or more. More work is needed to establish final guidelines, but I do provide a summary table for practitioners. I conclude that seed collections planning must consider the plant's biology, collection maintenance, and desired characteristics of the collection such as the number of allele copies and the type of allele targeted. These results emphasize a need for thoughtful deliberation and decisions by the curator and collector, and renewed discussion of conservation targets for ex situ collections to remain viable over hundreds to thousands of years.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Detecting bottlenecks is a common task in molecular ecology. While several bottleneck detection methods exist, evaluations of their power have focused only on severe bottlenecks (e.g. to Ne ~10). As ...a component of a recent review, Peery et al. () analysed the power of two approaches, the M‐ratio and heterozygote excess tests, to detect moderate bottlenecks (e.g. to Ne ~100), which is realistic for many conservation situations. In this Comment, we address three important points relevant to but not considered in Peery et al. Under moderate bottleneck scenarios, we test the (i) relative advantage of sampling more markers vs. more individuals, (ii) potential power to detect the bottleneck when utilizing dozens of microsatellites (a realistic possibility for contemporary studies) and (iii) reduction in power when postbottleneck recovery has occurred. For the realistic situations examined, we show that (i) doubling the number of loci shows equal or better power than tripling the number of individuals, (ii) increasing the number of markers (up to 100) results in continued additive gains in power, and (iii) recovery after a moderate amount of time or gradual change in size reduces power, by up to one‐half. Our results provide a practical supplement to Peery et al. and encourage the continued use of bottleneck detection methods in the genomic age, but also emphasize that the power under different sampling schemes should be estimated, using simulation modelling, as a routine component of molecular ecology studies.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Abstract
Global conservation policy and action have largely neglected protecting and monitoring genetic diversity—one of the three main pillars of biodiversity. Genetic diversity (diversity within ...species) underlies species’ adaptation and survival, ecosystem resilience, and societal innovation. The low priority given to genetic diversity has largely been due to knowledge gaps in key areas, including the importance of genetic diversity and the trends in genetic diversity change; the perceived high expense and low availability and the scattered nature of genetic data; and complicated concepts and information that are inaccessible to policymakers. However, numerous recent advances in knowledge, technology, databases, practice, and capacity have now set the stage for better integration of genetic diversity in policy instruments and conservation efforts. We review these developments and explore how they can support improved consideration of genetic diversity in global conservation policy commitments and enable countries to monitor, report on, and take action to maintain or restore genetic diversity.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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