Incorporating evolutionary processes into population viability models

We examined how ecological and evolutionary (eco‐evo) processes in population dynamics could be better integrated into population viability analysis (PVA). Complementary advances in computation and population genomics can be combined into an eco‐evo PVA to offer powerful new approaches to understand the influence of evolutionary processes on population persistence. We developed the mechanistic basis of an eco‐evo PVA using individual‐based models with individual‐level genotype tracking and dynamic genotype–phenotype mapping to model emergent population‐level effects, such as local adaptation and genetic rescue. We then outline how genomics can allow or improve parameter estimation for PVA models by providing genotypic information at large numbers of loci for neutral and functional genome regions. As climate change and other threatening processes increase in rate and scale, eco‐evo PVAs will become essential research tools to evaluate the effects of adaptive potential, evolutionary rescue, and locally adapted traits on persistence.     

Joint Effects of Inbreeding and Local Adaptation on the Evolution of Genetic Load after Fragmentation

Abstract: Disruption of gene flow among demes after landscape fragmentation can facilitate local adaptation but increase the effect of genetic drift and inbreeding. The joint effects of these conflicting forces on the mean fitness of individuals in a population are unknown. Through simulations, we explored the effect of increased isolation on the evolution of genetic load over the short and long term when fitness depends in part on local adaptation. We ignored genetic effects on demography. We modeled complex genomes, where a subset of the loci were under divergent selection in different localities. When a fraction of the loci were under heterogeneous selection, isolation increased mean fitness in larger demes made up of hundreds of individuals because of improved local adaptation. In smaller demes of tens of individuals, increased isolation improved local adaptation very little and reduced overall fitness. Short‐term improvement of mean fitness after fragmentation may not be indicative of the long‐term evolution of fitness. Whatever the deme size and potential for local adaptation, migration of one or two individuals per generation minimized the genetic load in general. The slow dynamics of mean fitness following fragmentation suggests that conservation measures should be implemented before the consequences of isolation on the genetic load become of concern.     

Predicting the Probability of Outbreeding Depression

Abstract: Fragmentation of animal and plant populations typically leads to genetic erosion and increased probability of extirpation. Although these effects can usually be reversed by re‐establishing gene flow between population fragments, managers sometimes fail to do so due to fears of outbreeding depression (OD). Rapid development of OD is due primarily to adaptive differentiation from selection or fixation of chromosomal variants. Fixed chromosomal variants can be detected empirically. We used an extended form of the breeders’ equation to predict the probability of OD due to adaptive differentiation between recently isolated population fragments as a function of intensity of selection, genetic diversity, effective population sizes, and generations of isolation. Empirical data indicated that populations in similar environments had not developed OD even after thousands of generations of isolation. To predict the probability of OD, we developed a decision tree that was based on the four variables from the breeders’ equation, taxonomic status, and gene flow within the last 500 years. The predicted probability of OD in crosses between two populations is elevated when the populations have at least one of the following characteristics: are distinct species, have fixed chromosomal differences, exchanged no genes in the last 500 years, or inhabit different environments. Conversely, the predicted probability of OD in crosses between two populations of the same species is low for populations with the same karyotype, isolated for <500 years, and that occupy similar environments. In the former case, we recommend crossing be avoided or tried on a limited, experimental basis. In the latter case, crossing can be carried out with low probability of OD. We used crosses with known results to test the decision tree and found that it correctly identified cases where OD occurred. Current concerns about OD in recently fragmented populations are almost certainly excessive.     

Conservation practitioners’ understanding of how to manage evolutionary processes

Both academics and practitioners consider a lack of knowledge about evolutionary theory to be a general barrier to effectively managing genetic diversity. However, it is challenging to judge practitioners’ level of understanding and how this influences their management decisions. Knowledge built through experience may be difficult for practitioners to articulate, but could nonetheless result in appropriate management strategies. To date, researchers have assessed only the explicit (formal) knowledge practitioners have of evolutionary concepts. To explore practitioners’ understanding of evolutionary concepts, it is necessary to consider how they might apply explicit and implicit knowledge to their management decisions. Using an online survey, we asked Australian practitioners to respond to 2 common management scenarios in which there is strong evidence that managing genetic diversity can improve outcomes: managing small, isolated populations and sourcing seeds for restoration projects. In describing their approach to these scenarios, practitioners demonstrated a stronger understanding of the effective management of genetic diversity than the definitions of the relevant concepts. However, their management of genetic diversity within small populations was closer to best practice than for restoration projects. Moreover, the risks practitioners described in implementing best practice management were more likely to affect their approach to restoration than translocation projects. These findings provide evidence that strategies to build the capacity of practitioners to manage genetic diversity should focus on realistic management scenarios. Given that practitioners recognize the importance of adapting their practices and the strong evidence for the benefits of actively managing genetic diversity, there is hope that better engagement by evolutionary biologists with practitioners could facilitate significant shifts toward evolutionarily enlightened management.     

Evaluating the outcomes of genetic rescue attempts

Augmenting gene flow is a powerful tool for the conservation of small, isolated populations. However, genetic rescue attempts have largely been limited to populations at the brink of extinction, in part due to concerns over negative outcomes (e.g., outbreeding depression). Increasing habitat fragmentation may necessitate more proactive genetic management. Broader application of augmented gene flow will, in turn, require rigorous evaluation to increase confidence and identify pitfalls in this approach. To date, there has been no assessment of best monitoring practices for genetic rescue attempts. We used genomically explicit, individual-based simulations to examine the effectiveness of common approaches (i.e., tests for increases in fitness, migrant ancestry, heterozygosity, and abundance) for determining whether genetic rescue or outbreeding depression occurred. Statistical power to detect the effects of gene flow on fitness was high (≥0.8) when effect sizes were large, a finding consistent with those from previous studies on severely inbred populations. However, smaller effects of gene flow on fitness can appreciably affect persistence probability but current evaluation approaches fail to provide results from which reliable inferences can be drawn. The power of the metrics we examined to evaluate genetic rescue attempts depended on the time since gene flow and whether gene flow was beneficial or deleterious. Encouragingly, the use of multiple metrics provided nonredundant information and improved inference reliability, highlighting the importance of intensive monitoring efforts. Further development of best practices for evaluating genetic rescue attempts will be crucial for a responsible transition to increased use of translocations to decrease extinction risk.     

The immediate costs and long-term benefits of assisted gene flow in large populations

With the genetic health of many plant and animal populations deteriorating due to climate change outpacing adaptation, interventions, such as assisted gene flow (AGF), may provide genetic variation necessary for populations to adapt to climate change. We ran genetic simulations to mimic different AGF scenarios in large populations and measured their outcomes on population-level fitness to determine circumstances in which it is worthwhile to perform AGF. In the absence of inbreeding depression, AGF was beneficial within a few generations only when introduced genotypes had much higher fitness than local individuals and traits affecting fitness were controlled by a few genes of large effect. AGF was harmful over short periods (e.g., first ∼10–20 generations) if there was strong outbreeding depression or introduced deleterious genetic variation. When the adaptive trait was controlled by many loci of small effect, the benefits of AGF took over 10 generations to realize—potentially too long for most climate-related management scenarios. The genomic integrity of the recipient population typically remained intact following AGF; the amount of genetic material from the donor population usually constituted no more of the recipient population's genome than the fraction of the population introduced. Significant genomic turnover (e.g., >50% replacement) only occurred when the selective advantage of the adaptive trait and translocation fraction were extremely high. Our results will be useful when adaptive management is used to maintain the genetic health and productivity of large populations under climate change.     

Guidelines for genetic monitoring of translocated plant populations

Plant translocation is a useful tool for implementing assisted gene flow in recovery plans of critically endangered plant species. Although it helps to restore genetically viable populations, it is not devoid of genetic risks, such as poor adaptation of transplants and outbreeding depression in the hybrid progeny, which may have negative consequences in terms of demographic growth and plant fitness. Hence, a follow-up genetic monitoring should evaluate whether the translocated populations are genetically viable and self-sustaining in the short and long term. The causes of failure to adjust management responses also need to be identified. Molecular markers and fitness-related quantitative traits can be used to determine whether a plant translocation enhanced genetic diversity, increased fitness, and improved the probability of long-term survival. We devised guidelines and illustrated them with studies from the literature to help practitioners determine the appropriate genetic survey methods so that management practices can better integrate evolutionary processes. These guidelines include methods for sampling and for assessing changes in genetic diversity and differentiation, contemporary gene flow, mode of local recruitment, admixture level, the effects of genetic rescue, inbreeding or outbreeding depression and local adaptation on plant fitness, and long-term genetic changes.