Isomeric triazines exhibit unique profiles of bioorthogonal reactivity.

Expanding the scope of bioorthogonal reactivity requires access to new and mutually compatible reagents. We report here that 1,2,4-triazines can be tuned to exhibit unique reaction profiles with biocompatible strained alkenes and alkynes. Computational analyses were used to identify candidate orthogonal reactions, and the predictions were experimentally verified. Notably, 5-substituted triazines, unlike their 6-substituted counterparts, undergo rapid [4 + 2] cycloadditions with a sterically encumbered strained alkyne. This unique, sterically controlled reactivity was exploited for dual bioorthogonal labeling. Mutually orthogonal triazines and cycloaddition chemistries will enable new multi-component imaging applications

Distribution of priority grassland bird habitats in the Prairie Pothole Region of Canada

Grassland ecosystems and the species that rely on them are one of the most urgent habitat conservation concerns in North America. Fundamental to any landscape conservation efforts is the identification of priority habitats to help target management efforts. Many avian species associated with prairie ecosystems have experienced population declines along with continued loss of prairie habitats. Additionally, given the long history of research in avian systems and the close grassland associations of some species, birds are excellent candidate taxa for the identification of priority habitats and can provide an informed starting point for multispecies assessments. We used data from the North American Breeding Bird Survey (1997-2014) to develop species distribution models for 15 grassland bird species across the Prairie Pothole Region of Canada. Model performance varied widely across species. Ten species demonstrated good model performance (average Boyce Index > 0.64 across 5-fold cross validation). We used these 10 species to assess the influence of habitat covariates on the relative probability of occurrence, to compare the spatial scales of selection, and to generate multispecies habitat priority maps. Of the nine habitat covariates considered, most species predictably demonstrated positive associations with grassland habitats and avoidance of areas of high tree and shrub cover. Two covariates representing wetland abundance were also frequently included in the top models. The area covered by wetlands (w.area) was present in the top model for 5 of 10 species with a consistently estimated negative coefficient. However, a covariate, which represented the number of wetland basins (w.basins), was present in the top model for 8 of 10 species with an estimated positive coefficient for all but 1 species, representing a preference for more heterogeneous wetland landscapes. The larger spatial scales we considered tended to have greater explanatory power than smaller spatial scales and were thus more prevalent in the top models. The multispecies priority habitat maps that we produced can be used for future assessments of potential habitat management actions. Our work provides a critical foundation for the incorporation of grassland bird conservation goals into on-going landscape-planning initiatives in the Prairie Pothole Region of Canada

Developing approaches for linear mixed modeling in landscape genetics through landscape-directed dispersal simulations

Dispersal can impact population dynamics and geographic variation, and thus, genetic approaches that can establish which landscape factors influence population connectivity have ecological and evolutionary importance. Mixed models that account for the error structure of pairwise datasets are increasingly used to compare models relating genetic differentiation to pairwise measures of landscape resistance. A model selection framework based on information criteria metrics or explained variance may help disentangle the ecological and landscape factors influencing genetic structure, yet there are currently no consensus for the best protocols. Here, we develop landscape-directed simulations and test a series of replicates that emulate independent empirical datasets of two species with different life history characteristics (greater sage-grouse; eastern foxsnake). We determined that in our simulated scenarios, AIC and BIC were the best model selection indices and that marginal R-2 values were biased toward more complex models. The model coefficients for landscape variables generally reflected the underlying dispersal model with confidence intervals that did not overlap with zero across the entire model set. When we controlled for geographic distance, variables not in the underlying dispersal models (i.e., nontrue) typically overlapped zero. Our study helps establish methods for using linear mixed models to identify the features underlying patterns of dispersal across a variety of landscapes.Endangered Species Recovery Fund (WWF, Environment Canada, Ontario Ministry of Natural Resources)US Bureau of Land ManagementUS Geological SurveyWyoming Game and Fish Departmen

Landscape characteristics influencing the genetic structure of greater sage-grouse within the stronghold of their range: a holistic modeling approach

Given the significance of animal dispersal to population dynamics and geographic variability, understanding how dispersal is impacted by landscape patterns has major ecological and conservation importance. Speaking to the importance of dispersal, the use of linear mixed models to compare genetic differentiation with pairwise resistance derived from landscape resistance surfaces has presented new opportunities to disentangle the menagerie of factors behind effective dispersal across a given landscape. Here, we combine these approaches with novel resistance surface parameterization to determine how the distribution of high- and low-quality seasonal habitat and individual landscape components shape patterns of gene flow for the greater sage-grouse (Centrocercus urophasianus) across Wyoming. We found that pairwise resistance derived from the distribution of low-quality nesting and winter, but not summer, seasonal habitat had the strongest correlation with genetic differentiation. Although the patterns were not as strong as with habitat distribution, multivariate models with sagebrush cover and landscape ruggedness or forest cover and ruggedness similarly had a much stronger fit with genetic differentiation than an undifferentiated landscape. In most cases, landscape resistance surfaces transformed with 17.33-km-diameter moving windows were preferred, suggesting small-scale differences in habitat were unimportant at this large spatial extent. Despite the emergence of these overall patterns, there were differences in the selection of top models depending on the model selection criteria, suggesting research into the most appropriate criteria for landscape genetics is required. Overall, our results highlight the importance of differences in seasonal habitat preferences to patterns of gene flow and suggest the combination of habitat suitability modeling and linear mixed models with our resistance parameterization is a powerful approach to discerning the effects of landscape on gene flow.U.S. Bureau of Land ManagementU.S. Geological SurveyWyoming Game and Fish Departmen

Intercontinental dispersal of Typha angustifolia and T. latifolia between Europe and North America has implications for Typha invasions

The full effects of biological invasions may be underestimated in many areas because of cryptogenic species, which are those that can be identified as neither native nor introduced. In North America, the cattails Typha latifolia, T. angustifolia, and their hybrid T. × glauca are increasingly aggressive invaders of wetlands. There is a widespread belief that T. latifolia is native to North America and T. angustifolia was introduced from Europe, although there has so far been little empirical support for the latter claim. We used microsatellite data and chloroplast DNA sequences to compare T. latifolia and T. angustifolia genotypes from eastern North America and Europe. In both species, our data revealed a high level of genetic similarity between North American and European populations that is indicative of relatively recent intercontinental dispersal. More specifically, the most likely scenario suggested by Approximate Bayesian Computation was an introduction of T. angustifolia from Europe to North America. We discuss the potential importance of our findings in the context of hybridization, novel genomes, and increasingly invasive behaviour in North American Typha spp

Data from: The genetic underpinnings of population cyclicity: establishing expectations for the genetic anatomy of cycling populations

Despite extensive research into the mechanisms underlying population cyclicity, we have little understanding of the impacts of numerical fluctuations on the genetic variation of cycling populations. Thus, the potential implications of natural and anthropogenically-driven variation in population cycle dynamics on the diversity and evolutionary potential of cyclic populations is unclear. Here, we use Canada lynx Lynx canadensis matrix population models, set up in a linear stepping-stone, to generate demographic replicates of biologically realistic cycling populations. Overall, increasing cycle amplitude predictably reduced genetic diversity and increased genetic differentiation, with cyclic effects increased by population synchrony. Modest dispersal rates (1–3% of the population) between high and low amplitude cyclic populations did not diminish these effects suggesting that spatial variation in cyclic amplitude should be reflected in patterns of genetic diversity and differentiation at these rates. At high dispersal rates (6%) groups containing only high amplitude cyclic populations had higher diversity and lower differentiation than those mixed with low amplitude cyclic populations. Negative density-dependent dispersal did not impact genetic diversity, but did homogenize populations by reducing differentiation and patterns of isolation by distance. Surprisingly, temporal changes in diversity and differentiation throughout a cycle were not always consistent with population size. In particular, negative density-dependent dispersal simultaneously decreased differences in genetic diversity while increasing differences in genetic differentiation between numerical peaks and nadirs. Combined, our findings suggest demographic changes at fine temporal scales can impact genetic variation of interacting populations and provide testable predictions relating population cyclicty to genetic variation. Further, our results suggest that including realistic demographic and dispersal parameters in population genetic models and using information from temporal changes in genetic variation could help to discern complex demographic scenarios and illuminate population dynamics at fine temporal scales

Cycle amplitude genetic differences

This is genetic summary statistics from demographic simulations with different cycle amplitudes (High, Medium, Low). All summary statistic are averaged across the 10 simulated populations. In total there are 25 replicates for each cycle amplitude across 500 years

Mixed population genetic simulations

Genetic summary statistics for demographic simulations with high and low amplitude cyclic populations exchanging migrants in a linear stepping stone model. Low (1% dispersal), Medium (3% dispersal) and high (6 % dispersal) dispersal scenarios were simulated and genetic summary statistics are averaged across amplitude treatments in each year

Dispersal difference simulations.

Genetic summary statistics for demographic simulations with different dispersal scenarios (constant synchronous, constant non-synchronous, phase dependent dispersal). Summary statistics are averaged across 10 populations for all 500 generations