There is a critical need in conservation, and in ecology in general, to accurately predict the adaptive potential and subsequent demographic outcomes for species facing environmental changes. The ability of a species to adapt to change depends, essentially, on two factors: the rate of environmental changes and the genetic mechanisms that control any traits under selection. However, our ability to inform demographic forecasts using genetic data has not yet been well validated. Here, we use simulations to show that existing genetic methodologies for demographic forecasting do not perform well, and instead propose a novel method of genetic architecture estimation (True Genomic Architecture Computation, or TGAC), which estimates the underlying genetic architecture of a trait without directly attempting to identify causal loci. We show that this method can be used to generate far more accurate demographic forecasts than existing alternatives.Monarch Butterflies (Danaus plexippus) are one such species of particular conservation concern. Due in part to long-term environmental and land use changes, migratory populations of the monarchs have dramatic declines over the last several decades, prompting concern that the migratory life history of the species may go “quasi-extinct” over the coming years as selective factors begin to favor residency over migration. However, one relatively new non-native monarch population in Australia rapidly re-acquired a migratory life history following hundreds of generations of residency and successive bottlenecks. We here show that reproductive diapause, a key migratory trait, is strongly associated with a novel genetic mechanism in the population. This may imply that the species might be able to rapidly re-evolve migration in other places as well should conditions change in the future to favor it.

In this dissertation, genomic tools were applied to investigate populations of two endangered native species of California for conservation purposes. The first species is the McCloud River Redband Trout (MRRT; Oncorhynchus mykiss stonei), a unique subspecies of rainbow trout that inhabits the isolated Upper McCloud River of Northern California. A major threat to MRRT is introgressive hybridization with non-native rainbow trout from historical stocking and contemporary unauthorized introductions. To help address this concern, I collected RAD-sequencing data on 308 total individuals from MRRT and other California O. mykiss populations and examined population structure using Principal Component and admixture analyses. I found that populations of MRRT in Sheepheaven, Swamp, Edson, and Moosehead creeks are nonintrogressed. Additionally, I saw no evidence of introgression in Dry Creek, and suggest further investigation to determine if it can be considered a core MRRT conservation population. Sheepheaven Creek was previously thought to be the sole historical lineage of MRRT, but our analysis identified three: Sheepheaven, Edson, and Dry creeks, all of which should be preserved. Finally, I discovered diagnostic and polymorphic SNP markers for monitoring introgression and genetic diversity in MRRT. The results provide a valuable resource for the conservation and management of MRRT.The second species is the endangered delta smelt (Hypomesus transpacificus). A refuge population of delta smelt has been maintained in a conservation hatchery system at the Fish Conservation and Culture Lab at UC Davis (FCCL). The FCCL uses a pedigree-based breeding system to keep the hatchery fish genetically close to the wild population. Despite intense genetic management at the FCCL, evidence of fitness differences between wild and cultured fish was reported. To investigate domestication selection, I used RAD-sequencing and Whole Genome Bisulfite Sequencing to collect genomic and epigenomic data on archived FCCL fin clip samples. For the genomic experiment, I grouped 240 individuals based on their level of hatchery ancestry (Domestication Index = DI) to low, medium, and high DI groups plus wild group. Selection signatures were examined using two FST comparisons: early (wild/low ID) vs. late (medium/high DI) groups, and wild vs. hatchery (low/medium/high DI) groups. I identified one candidate region on chromosome 22 as being putatively under domestication selection and discovered four genes located in this region through its annotation. Other candidate regions identified in this study need to be investigated further. My results also suggest domestication selection happens quickly (i.e., in early generations). For the epigenomic experiment, I investigated the methylation change between the wild and hatchery environments, and the inheritance patterns of the methylation changes after three generations in captivity. To do this, I collected 104 males and females from wild and hatchery delta smelt. I chose families with individuals grouped based on their generation number: G0, G1, G2, and G3. The most informative differentially methylated regions (DMRs) between the two environments were discovered by comparing methylation differences of individuals between G0 (n=12) and G3 (n=10) groups. A total of 201 significant DMRs (p-value < 0.05) were discovered across 26 chromosomes. The ratio of hypermethylated DMRs was 2.4 times more than hypomethylated DMRs in the hatchery group versus the wild group (71% to 29%). Genes associated with the DMRs in our study were predominantly involved in swimming and transmembrane activity. Methylation status of those DMRs in all the individuals at the group level, revealed possible evidence of methylation inheritance across generations but further examination at the level of individual family did not illustrate a clear inheritance pattern. Collectively, our findings may ultimately help the FCCL to adjust their protocol to minimize the rate of hatchery adaptation, and thus improve the likelihood of success for future supplementation.

Individuals should strategically shift decision criteria when there are disproportionate likelihoods or consequences for falsely identifying versus missing target items. Despite being explicitly aware of the advantages for criterion shifting, people on average do not shift extremely, leading many theories to conclude that people are generally suboptimal at placing decision criteria. However, assessments of individual differences reveal that some people do shift criteria quite well while others fail to shift entirely. These individual differences are remarkably consistent across time, tasks, and decision domains, yet cannot be adequately explained by other cognitive or personality measures—the degree to which people shift a criterion is a stable, uniquely individualistic cognitive trait. Individuals who inadequately shift criteria are capable of shifting to greater extents but appear unwilling to do so. Understanding criterion shifting tendencies at the individual level is vital since assessments of group averages fail to capture the true nature of this behavior. These individual differences carry important implications for investigating the neural mechanisms that underly the placement of a decision criterion.The role of the decision criterion is often neglected in neuroimaging studies. For instance, widespread frontoparietal activity is consistently observed in recognition memory tests that compare studied (“target”) versus unstudied (“nontarget”) responses. However, there are conflicting accounts that ascribe various aspects of frontoparietal activity to mnemonic evidence versus decisional processes. According to Signal Detection Theory, recognition judgments require individuals to decide whether the memory strength of an item exceeds a decision criterion for reporting previously studied items. Yet, most fMRI studies fail to manipulate both memory strength and decision criteria, making it difficult to appropriately identify frontoparietal activity associated with each process. Systematic manipulations of criteria and discriminability revealed that maintaining a conservative versus liberal decision criterion drastically affects frontoparietal activity in target versus nontarget response contrasts, whereas changes in discriminability showed virtually no differences. Findings from dense-sampling fMRI data revealed multiple frontoparietal networks associated with inhibiting prepotent responses whereas the default mode network is relatively more engaged when participants provide a prepotent response. This supports a response bias account of recognition memory indicating that widespread frontoparietal activity observed during recognition memory tests is largely attributable to decisional processes. Attempts to modulate decision criteria using neurostimulation have unfortunately failed to provide a causal link between frontoparietal activity and criterion placement, despite the robust fMRI correlates suggesting that such a relationship should exist.

Studies on multiple patient groups suggest that reasoning has a hemispheric asymmetry component. Previously, we proposed that neural networks in the left hemisphere are driven toward increasing and maintaining certainty, while right frontal networks prioritize congruence between beliefs and evidence. We tested the predictions of this framework with two high definition transcranial direct current stimulation (HD-tDCS) experiments and one functional magnetic resonance imaging (fMRI) experiment. In both HD-tDCS studies, we aimed to induce (or amplify) hemispheric asymmetry in healthy participants as they completed novel reasoning tasks. Each participant completed three tDCS sessions: a LH-bias session, in which the anode was placed over the left inferior frontal gyrus (IFG; BA45) and the cathode over the right IFG; a RH-bias session, in which the anode was placed over the right IFG and the cathode over the left IFG; and a sham session, which served as a control.

In the first HD-tDCS experiment, participants (N=26) completed a probabilistic inference task that required the integration of evidence and one’s prior background knowledge. Consistent with predictions, we found that the intensity of RH-bias stimulation was associated with 1) collecting more evidence, 2) adopting a higher threshold for stopping evidence collection, and 3) making less certain guesses than an ideal Bayesian updater during the evidence presentation. Contrary to predictions, we found that greater LH-bias intensity was associated with more evidence collection, and LH-bias stimulation was associated with greater belief backtracks after encountering conflicting evidence than RH-bias or sham stimulation.

The second HD-tDCS experiment followed a similar stimulation protocol but used reasoning problems that were more deeply embedded in real-world contexts in order to create more salient belief-evidence conflicts. During each stimulation session, 24 participants 1) judged whether a criminal suspect was guilty or not guilty based on crime scene evidence, 2) judged whether or not to pass a law based on arguments in favor and in opposition to it, and 3) judged whether a news headline was real or fake. We found that RH-bias stimulation reduced belief polarization after conflict, which was consistent with our predictions. Similarly, when evidence conflicted participants’ strong beliefs, they backtracked on their beliefs more under RH-bias stimulation compared to sham stimulation and, albeit to a lesser extent, compared to LH-bias stimulation. Under RH-bias stimulation, participants were less likely to judge real news headlines as being real, which resulted in poorer discrimination of real vs. fake headlines compared to sham and LH-bias stimulation.

Finally, in the fMRI experiment, we examined lateralization in frontal anatomical regions for contrasts that we predicted to be more left-lateralized or more right-lateralized. Participants (N=36) completed a modified version of the state guessing task that was used in the first tDCS experiment. Consistent with predictions, contrasts involving uncertainty and belief advances were generally more left-lateralized and contrasts involving conflicting evidence and belief backtracks were more right-lateralized.

We show that HD-tDCS can alter belief updating in healthy individuals in a way that is consistent with the patient literature, but additional experiments are necessary to disentangle the causal relationships between different reasoning biases and neural activity in left and right frontal neural networks.

Functional imaging studies have revealed the default mode network (DMN) activates when people are at rest. However, generally only minimal instructions were provided among those studies. Our goal in this study was to demonstrate how resting state activity varies with the knowledge of being watched. In this study, we used two distinct manipulations to address this question: first, we described two separate scans as being either anatomical or functional (with little additional detail), when in fact both were functional; and second, in a putatively separate experiment, we informed participants we were able to observe their thoughts, and after a more thorough description, carried out three more functional scans, one of which was again described as anatomical. Our results demonstrate there are systematic differences across several networks as a function of instructional differences. Most strikingly, there was a significant increase in the orbitofrontal cortex (OFC) when comparing the first functional scan to the first sham anatomical scan, and a substantial increase in functional connectivity within the DMN when comparing the second sham anatomical scan to the second and third functional scans. These results suggest the mere awareness that one is being watched causes significant changes in the patterns of activity across functional networks, including the DMN. They also suggest the importance of using precise instructions in resting-state studies, because even slight variations in instruction can have substantial impacts on the brain's activity at rest.

Intraspecific diversity is a crucial part of conservation genetics because it buffers populations from decline after catastrophic events. There is incredible intraspecific life history diversity within the species Oncorhynchus mykiss, commonly known and rainbow trout and steelhead. The life history of a freshwater residing rainbow trout differs greatly from that of a steelhead, who’s life history mirrors a salmon. There are many gaps in understanding of the life history variation in O. mykiss that can aid in its’ conservation and management. Here we apply genetics to better understand the ecology of steelhead throughout their range. We used a genetic marker in the North Umpqua River in Oregon to identify where early migrating steelhead are spawning. We also ran genetic associations with the half-pounder life history and early migration steelhead in northern latitudes. We found that some streams have variable use by early migrating steelhead depending on the spawning year. Additionally, the half-pounder life history is not likely to be genetically controlled, even though this variant occurs in two locations at the extreme ends of the species’ range: Kamchatka, Russia and California, USA. We also found the genetic region that controls migration time in the Situk River, Alaska, which is different, but close in position to the GREB1L/ROCK1 genes that control migration time in souther latitude populations. These results show unique differences in life-history diversity O. mykiss that are population specific. Ultimately, discoveries in conservation genetics in salmonids should not be extrapolated, but should be tested due to the incredible intraspecific diversity.