Postglacial phylogeography, admixture, and evolution of red spruce (Picea rubens Sarg.) in Eastern North America.

Climate change is a major evolutionary force that can affect the structure of forest ecosystems worldwide. Red spruce (Picea rubens Sarg.) has recently faced a considerable decline in the Southern Appalachians due to rapid environmental change, which includes historical land use, and atmospheric pollution. In the northern part of its range, red spruce is sympatric with closely related black spruce (Picea mariana (Mill.) B.S.P.), where introgressive hybridization commonly occurs. We investigated range-wide population genetic diversity and structure and inferred postglacial migration patterns and evolution of red spruce using nuclear microsatellites. Moderate genetic diversity and differentiation were observed in red spruce. Genetic distance, maximum likelihood and Bayesian analyses identified two distinct population clusters: southern glacial populations, and the evolutionarily younger northern populations. Approximate Bayesian computation suggests that patterns of admixture are the result of divergence of red spruce and black spruce from a common ancestor and then introgressive hybridization during post-glacial migration. Genetic diversity, effective population size (Ne) and genetic differentiation were higher in the northern than in the southern populations. Our results along with previously available fossil data suggest that Picea rubens and Picea mariana occupied separate southern refugia during the last glaciation. After initial expansion in the early Holocene, these two species faced a period of recession and formed a secondary coastal refugium, where introgressive hybridization occurred, and then both species migrated northward. As a result, various levels of black spruce alleles are present in the sympatric red spruce populations. Allopatric populations of P. rubens and P. mariana have many species-specific alleles and much fewer alleles from common ancestry. The pure southern red spruce populations may become critically endangered under projected climate change conditions as their ecological niche may disappear.

Global genetic diversity status and trends: towards a suite of Essential Biodiversity Variables (EBVs) for genetic composition.

Biodiversity underlies ecosystem resilience, ecosystem function, sustainable economies, and human well-being. Understanding how biodiversity sustains ecosystems under anthropogenic stressors and global environmental change will require new ways of deriving and applying biodiversity data. A major challenge is that biodiversity data and knowledge are scattered, biased, collected with numerous methods, and stored in inconsistent ways. The Group on Earth Observations Biodiversity Observation Network (GEO BON) has developed the Essential Biodiversity Variables (EBVs) as fundamental metrics to help aggregate, harmonize, and interpret biodiversity observation data from diverse sources. Mapping and analyzing EBVs can help to evaluate how aspects of biodiversity are distributed geographically and how they change over time. EBVs are also intended to serve as inputs and validation to forecast the status and trends of biodiversity, and to support policy and decision making. Here, we assess the feasibility of implementing Genetic Composition EBVs (Genetic EBVs), which are metrics of within-species genetic variation. We review and bring together numerous areas of the field of genetics and evaluate how each contributes to global and regional genetic biodiversity monitoring with respect to theory, sampling logistics, metadata, archiving, data aggregation, modeling, and technological advances. We propose four Genetic EBVs: (i) Genetic Diversity; (ii) Genetic Differentiation; (iii) Inbreeding; and (iv) Effective Population Size (Ne ). We rank Genetic EBVs according to their relevance, sensitivity to change, generalizability, scalability, feasibility and data availability. We outline the workflow for generating genetic data underlying the Genetic EBVs, and review advances and needs in archiving genetic composition data and metadata. We discuss how Genetic EBVs can be operationalized by visualizing EBVs in space and time across species and by forecasting Genetic EBVs beyond current observations using various modeling approaches. Our review then explores challenges of aggregation, standardization, and costs of operationalizing the Genetic EBVs, as well as future directions and opportunities to maximize their uptake globally in research and policy. The collection, annotation, and availability of genetic data has made major advances in the past decade, each of which contributes to the practical and standardized framework for large-scale genetic observation reporting. Rapid advances in DNA sequencing technology present new opportunities, but also challenges for operationalizing Genetic EBVs for biodiversity monitoring regionally and globally. With these advances, genetic composition monitoring is starting to be integrated into global conservation policy, which can help support the foundation of all biodiversity and species' long-term persistence in the face of environmental change. We conclude with a summary of concrete steps for researchers and policy makers for advancing operationalization of Genetic EBVs. The technical and analytical foundations of Genetic EBVs are well developed, and conservation practitioners should anticipate their increasing application as efforts emerge to scale up genetic biodiversity monitoring regionally and globally.

Comparative Association Mapping Reveals Conservation of Major Gene Resistance to White Pine Blister Rust in Southwestern White Pine (Pinus strobiformis) and Limber Pine (P. flexilis).

All native North American white pines are highly susceptible to white pine blister rust (WPBR) caused by Cronartium ribicola. Understanding genomic diversity and molecular mechanisms underlying genetic resistance to WPBR remains one of the great challenges in improvement of white pines. To compare major gene resistance (MGR) present in two species, southwestern white pine (Pinus strobiformis) Cr3 and limber pine (P. flexilis) Cr4, we performed association analyses of Cr3-controlled resistant traits using single nucleotide polymorphism (SNP) assays designed with Cr4-linked polymorphic genes. We found that ∼70% of P. flexilis SNPs were transferable to P. strobiformis. Furthermore, several Cr4-linked SNPs were significantly associated with the Cr3-controlled traits in P. strobiformis families. The most significantly associated SNP (M326511_1126R) almost colocalized with Cr4 on the Pinus consensus linkage group 8, suggesting that Cr3 and Cr4 might be the same R locus, or have localizations very close to each other in the syntenic region of the P. strobiformis and P. flexilis genomes. M326511_1126R was identified as a nonsynonymous SNP, causing amino acid change (Val376Ile) in a putative pectin acetylesterase, with coding sequences identical between the two species. Moreover, top Cr3-associated SNPs were further developed as TaqMan genotyping assays, suggesting their usefulness as marker-assisted selection (MAS) tools to distinguish genotypes between quantitative resistance and MGR. This work demonstrates the successful transferability of SNP markers between two closely related white pine species in the hybrid zone, and the possibility for deployment of MAS tools to facilitate long-term WPBR management in P. strobiformis breeding and conservation.

Advancing an interdisciplinary framework to study seed dispersal ecology.

Although dispersal is generally viewed as a crucial determinant for the fitness of any organism, our understanding of its role in the persistence and spread of plant populations remains incomplete. Generalizing and predicting dispersal processes are challenging due to context dependence of seed dispersal, environmental heterogeneity and interdependent processes occurring over multiple spatial and temporal scales. Current population models often use simple phenomenological descriptions of dispersal processes, limiting their ability to examine the role of population persistence and spread, especially under global change. To move seed dispersal ecology forward, we need to evaluate the impact of any single seed dispersal event within the full spatial and temporal context of a plant's life history and environmental variability that ultimately influences a population's ability to persist and spread. In this perspective, we provide guidance on integrating empirical and theoretical approaches that account for the context dependency of seed dispersal to improve our ability to generalize and predict the consequences of dispersal, and its anthropogenic alteration, across systems. We synthesize suitable theoretical frameworks for this work and discuss concepts, approaches and available data from diverse subdisciplines to help operationalize concepts, highlight recent breakthroughs across research areas and discuss ongoing challenges and open questions. We address knowledge gaps in the movement ecology of seeds and the integration of dispersal and demography that could benefit from such a synthesis. With an interdisciplinary perspective, we will be able to better understand how global change will impact seed dispersal processes, and potential cascading effects on plant population persistence, spread and biodiversity.

The total dispersal kernel: a review and future directions.

The distribution and abundance of plants across the world depends in part on their ability to move, which is commonly characterized by a dispersal kernel. For seeds, the total dispersal kernel (TDK) describes the combined influence of all primary, secondary and higher-order dispersal vectors on the overall dispersal kernel for a plant individual, population, species or community. Understanding the role of each vector within the TDK, and their combined influence on the TDK, is critically important for being able to predict plant responses to a changing biotic or abiotic environment. In addition, fully characterizing the TDK by including all vectors may affect predictions of population spread. Here, we review existing research on the TDK and discuss advances in empirical, conceptual modelling and statistical approaches that will facilitate broader application. The concept is simple, but few examples of well-characterized TDKs exist. We find that significant empirical challenges exist, as many studies do not account for all dispersal vectors (e.g. gravity, higher-order dispersal vectors), inadequately measure or estimate long-distance dispersal resulting from multiple vectors and/or neglect spatial heterogeneity and context dependence. Existing mathematical and conceptual modelling approaches and statistical methods allow fitting individual dispersal kernels and combining them to form a TDK; these will perform best if robust prior information is available. We recommend a modelling cycle to parameterize TDKs, where empirical data inform models, which in turn inform additional data collection. Finally, we recommend that the TDK concept be extended to account for not only where seeds land, but also how that location affects the likelihood of establishing and producing a reproductive adult, i.e. the total effective dispersal kernel.

Rapid changes in seed dispersal traits may modify plant responses to global change.

When climatic or environmental conditions change, plant populations must either adapt to these new conditions, or track their niche via seed dispersal. Adaptation of plants to different abiotic environments has mostly been discussed with respect to physiological and demographic parameters that allow local persistence. However, rapid modifications in response to changing environmental conditions can also affect seed dispersal, both via plant traits and via their dispersal agents. Studying such changes empirically is challenging, due to the high variability in dispersal success, resulting from environmental heterogeneity, and substantial phenotypic variability of dispersal-related traits of seeds and their dispersers. The exact mechanisms that drive rapid changes are often not well understood, but the ecological implications of these processes are essential determinants of dispersal success, and deserve more attention from ecologists, especially in the context of adaptation to global change. We outline the evidence for rapid changes in seed dispersal traits by discussing variability due to plasticity or genetics broadly, and describe the specific traits and biological systems in which variability in dispersal is being studied, before discussing some of the potential underlying mechanisms. We then address future research needs and propose a simulation model that incorporates phenotypic plasticity in seed dispersal. We close with a call to action and encourage ecologists and biologist to embrace the challenge of better understanding rapid changes in seed dispersal and their consequences for the reaction of plant populations to global change.

Landscape genomic insights into the historic migration of mountain hemlock in response to Holocene climate change.

PREMISE OF THE STUDY: Untangling alternative historic dispersal pathways in long-lived tree species is critical to better understand how temperate tree species may respond to climatic change. However, disentangling these alternative pathways is often difficult. Emerging genomic technologies and landscape genetics techniques improve our ability to assess these pathways in natural systems. We address the question to what degree have microrefugial patches and long-distance dispersal been responsible for the colonization of mountain hemlock (Tsuga mertensiana) on the Alaskan Kenai Peninsula. METHODS: We used double-digest restriction-associated DNA sequencing (ddRADseq) to identify genetic variants across eight mountain hemlock sample sites on the Kenai Peninsula, Alaska. We assessed genetic diversity and linkage disequilibrium using landscape and population genetics approaches. Alternative historic dispersal pathways were assessed using discriminant analysis of principle components and electrical circuit theory. KEY RESULTS: A combination of decreasing diversity, high gene flow, and landscape connectivity indicates that mountain hemlock colonization on the Kenai Peninsula is the result of long-distance dispersal. We found that contemporary climate best explained gene flow patterns and that isolation by resistance was a better model explaining genetic variation than isolation by distance. CONCLUSIONS: Our findings support the conclusion that mountain hemlock colonization is the result of several long-distance dispersal events following Pleistocene glaciation. The high dispersal capability suggests that mountain hemlock may be able to respond to future climate change and expand its range as new habitat opens along its northern distribution.