Arne Mooers’s research while affiliated with Simon Fraser University and other places

Retaining sufficient genetic variation for both short and long-term sustainability is a chief aim of ex situ programs for threatened species. Conservation breeding and reintroduction programs exist but oftentimes little is known about the genetic variation of in situ or ex situ populations. We collected genetic samples from both wild and zoo populations of Canada’s most endangered anuran, the Oregon Spotted Frog (Rana pretiosa) to compare genetic diversity (observed and expected heterozygosity), inbreeding coefficients (FIS), effective population sizes (Ne) and population structure using single-nucleotide polymorphisms (SNPs). We found low diversity in situ and lower diversity ex situ, with positive inbreeding coefficients indicating assortative mating in both wild and zoo populations. Ex situ breeding programs that allowed free mate choice retained more genetic variation compared to those where breeding groups were pre-determined. Mixed source zoo populations were less differentiated from their wild source populations than the latter were among themselves, indicating sufficient representation of wild populations in zoo populations. The patterns we uncover support continued collaboration of ex situ and in situ endeavours as supplementation will likely be required for the long-term viability of the very wild populations the zoos rely on for genetic sustainability.

Diversity plays an important role in various domains, including conservation, whether it describes diversity within a population or diversity over a set of species. While various strategies for measuring among-species diversity have emerged (e.g. Phylogenetic Diversity (PD), Split System Diversity (SSD) and entropy-based methods), extensions to populations are rare. An understudied problem is how to assess the diversity of a collection of populations where each has its own internal diversity. Relying solely on measures that treat each population as a monomorphic lineage (like a species) can be misleading. To address this problem, we present four population-level diversity assessment approaches: Pooling, Averaging, Pairwise Differencing, and Fixing. These approaches can be used to extend any diversity measure that is primarily defined for a group of individuals to a collection of populations. We then apply the approaches to two measures of diversity that have been used in conservation—Heterozygosity (Het) and Split System Diversity (SSD)—across a dataset comprising SNP data for 50 anadromous Atlantic salmon populations. We investigate agreement and disagreement between these measures of diversity when used to identify optimal sets of populations for conservation, on both the observed data, and randomized and simulated datasets. The similarity and differences of the maximum-diversity sets as well as the pairwise correlations among our proposed measures emphasize the need to clearly define what aspects of biodiversity we aim to both measure and optimize, to ensure meaningful and effective conservation decisions.

We unified the recent literature with the goal to contribute to the discussion on how genetic diversity might best be conserved. We argue that this decision will be guided by how genomic variation is distributed among manageable populations (i.e., its spatial structure), the degree to which adaptive potential is best predicted by variation across the entire genome or the subset of that variation that is identified as putatively adaptive (i.e., its genomic structure), and whether we are managing species as single entities or as collections of diversifying lineages. The distribution of genetic variation and our ultimate goal will have practical implications for on-the-ground management. If adaptive variation is largely polygenic or responsive to change, its spatial structure might be broadly governed by the forces determining genome-wide variation (linked selection, drift, and gene flow), making measurement and prioritization straightforward. If we are managing species as single entities, then population-level prioritization schemes are possible so as to maximize future pooled genetic variation. We outline one such scheme based on the popular Shapley value from cooperative game theory that considers the relative genetic contribution of a population to an unknown future collection of populations.

Previous studies have documented very little net change in average quadrat-level species richness and phylogenetic diversity. However, although the average remains centered around 0, there is much variation around this mean and many outliers. The relative contribution of anthropogenic drivers (such as climate change or land use change) to these outliers remains unclear. Traits may dictate species responses to these changes, and if relatedness is correlated with trait similarity, then the impacts of anthropogenic change may be clustered on the phylogeny. We build the first regional phylogeny of all Canadian butterfly species in order to examine change in community phylogenetic structure in response to two main documented drivers of change -- climate change and land use change -- across 265 species, 75 years and 96 well-sampled quadrats. We find no evidence that, on average, communities are becoming more or less clustered than one would expect. However, there is much variation depending on the magnitude and type of anthropogenic change occurring within a quadrat. We find that climate change as well as agricultural development is reducing species richness within a quadrat, and these species that are lost tend to be scattered across the phylogeny. However, agricultural abandonment is having the opposite effect: we find increasing species richness in the years immediately following it and decreasing distance between species in quadrats with the highest rates of abandonment, such that the species that colonize these plots tend to be close relatives of those already present and thus contribute little novel phylogenetic diversity to an assemblage. Consistent with previous work, small changes in local species richness may conceal simultaneous change in other facets of biodiversity.

Aim Recent studies have found that local‐scale plots measured through time exhibit marked variation in the change in species richness. However, the overall effect often reveals no net change. Most studies to date have been agnostic about the identities of the species lost/gained and about the processes that might lead to these changes. Generalist traits might be crucial in allowing species to colonize new plots or remain resilient in situ, whereas environmental filtering might remove specialists. We test whether plots are changing in species richness, whether they are becoming more similar (i.e., becoming homogenized) through time and whether several generalist traits can predict gains or losses from local plots. Location Canada. Time period 1945–2015. Major taxa studied Two hundred and sixty‐five species of butterflies. Methods We measured change in species richness and pairwise beta diversity across 96 well‐sampled 10 km × 10 km plots across Canada between two time periods: 1945–1975 and 1985–2015. We looked at the effects of wing span, mobility, dietary breadth and range size on the number of grid cells each species gained and lost between time periods. Results We observed a slight increase in plot‐level species richness, and that these communities are becoming homogenized through time. We note that most butterfly species in Canada have large North American ranges. The species with the widest ranges are better able to colonize new plots than species with narrower ranges, but also experience higher frequencies of local extinctions. In sum, the median range size of species within a plot increased through time. Main conclusions We highlight that, even when local species richness exhibits very little change, other potentially important changes in biodiversity can occur, such as geographical homogenization attributable to the colonization dynamics of species that are already widely distributed. Such patterns can reconcile observed global losses of species with the simultaneous lack of change in local diversity.

The Monarch butterfly eastern population (Danaus plexippus) is in decline primarily due to habitat loss. Current habitat restoration programs focus on re-establishing milkweed, the primary food resource for Monarch caterpillars, in the central United States of America. However, individual components of the Monarch life cycle function as part of an integrated whole. Here we develop the MOBU-SDyM, a migration-wide systems dynamics model of the Monarch butterfly migratory cycle to explore alternative management strategies’ impacts. Our model offers several advances over previous efforts, considering complex variables such as dynamic temperature-dependent developmental times, dynamic habitat availability, and weather-related mortality across the entire range. We first explored whether the predominant focus of milkweed restoration in the mid-range of the Monarch’s migration could be overestimating the Monarch’s actual habitat requirements. Second, we examined the robustness of using the recommended 1.2–1.6 billion milkweed stems as a policy objective when accounting for factors such as droughts, changes in temperature, and the stems’ effective usability by the Monarchs. Third, we used the model to estimate the number and distribution of stems across the northern, central, and southern regions of the breeding range needed to reach a self-sustainable long-term Monarch population of six overwintering hectares. Our analysis revealed that concentrating milkweed growth in the central region increases the size of the overwintering colonies more so than equivalent growth in the south region, with growth in the northern region having a negligible effect. However, even though simulating an increase in milkweed stems in the south did not play a key role in increasing the size of the overwintering colonies, it plays a paramount role in keeping the population above a critically small size. Abiotic factors considerably influenced the actual number of stems needed, but, in general, our estimates of required stems were 43–91% larger than the number of stems currently set as a restoration target: our optimal allocation efforts were 7.35, 92, and 0.15% to the south, central, and northern regions, respectively. Systems dynamics’ analytical and computational strengths provided us with new avenues to investigate the Monarch’s migration as a complex biological system and to contribute to more robust restoration policies for this unique species.

Bumble bees are globally important pollinators, especially in temperate regions, and evidence suggests that many species are declining. One recent high profile study by Soroye et al. (2020) applied occupancy models to dated historical collection data to quantify declines across North America and Europe. The authors modelled 66 species across a set of sites spanning both North America and Europe, rather than confining species to sites where they might be expected to occur. In addition, they inferred non-detections for time intervals where there is no evidence that the site was visited (by forcing every site to have exactly 3 visits in each era). We use simulated data to (i) investigate the validity of methods used in that study and (ii) test whether a multi-species framework that incorporates species' ranges and site visitation histories produces better estimates. We show that the method used by Soroye et al. (2020) yields biased estimates of declines, whereas our framework does not. We use such a model to provide revised and appreciably lower estimates for bumble bee community declines, with species-specific trends more closely matching classifications from IUCN. The species level trends we provide can help inform future species-at-risk assessments. Well-parameterized occupancy models may be a powerful tool for assessing species-wide trends using curated historical collection data.