Biology subjects

Brush, M.

Publications and source records attributed to Brush, M..

8 recordsLinked to original sources

bioRxiv2024

Modeling Mountain Pine Beetle Abundance in Novel Hosts

The mountain pine beetle has recently expanded its range into northern and central Alberta, posing an immediate threat to the novel host, jack pine. To date, some experiments suggest that jack pine has limited defensive capabilities despite of the restrictions from the physical environment. In this work, we explore the susceptibility of jack pine compared to the primary host, lodgepole pine, evaluating the risk of potential range expansion into Canadas boreal forest. We employ a hierarchical model, incorporating environmental and ecological covariates, to examine mountain pine beetle dynamics in a pine forest with lodgepole, hybrid and jack pines. Our results show that pine species significantly influence the probability of being killed, with jack pine being less likely to be infested than lodgepole pine, all else being equal. The hierarchical model demonstrates that beetles perform poorer in jack pine, characterized by a reproduction rate 0.16 times that of non-jack pine. Although jack pine is a suitable host, our results indicate that the number of infestations in jack pine could be lower than in lodgepole pine, with a reduced probability of emerging beetles.

ecology↗

bioRxiv2024

Modeling Mountain Pine Beetle Abundance and Distribution in a Changing Climate

The range of mountain pine beetle (Dendroctonus ponderosae Hopkins) is primarily constrained by climate, with winter temperatures playing a crucial role. Climate change is likely to increase the number of warm days and decrease cold days compared to historical norms, making higher latitudes more suitable habitats. In this work, we explore the potential impacts of environmental covariates on outbreaks of mountain pine beetle under climate change in a selected lodgepole pine area in Alberta. We employ a hierarchical model to examine mountain pine beetle dynamics approaching the end of the century. Our analysis assesses the impact of various climatic covariates and estimates the probability and expected number of infestations across different climate change scenarios. Our results from the hierarchical model underscore the critical role of degree days and overwinter survival probability, displaying an overall trend towards a higher probability and a greater number of outbreaks with increasing temperature. Our results indicate that Alberta is likely to experience widespread infestations in the future.

ecology↗

bioRxiv2024

Characterizing the speed and severity of mountain pine beetle spread under climate change with a mechanistic model

In the last few decades, mountain pine beetle (MPB) have spread into Alberta, partially facilitated by climate change and warmer winters. Future effects of climate change on pine beetle spread are uncertain as warming is likely to affect both forest growth and beetle development. We here present a mechanistic model of pine beetle dynamics and characterize simulated outbreaks under climate change. This model includes key aspects of pine beetle biology, and we determine plausible ranges for each model parameter from available data. We then consider how forest growth, beetle brood size, and host resistance are likely to change in Alberta by the end of the century, and how this will relate to changes in model parameters. We simulate beetle outbreaks and quantify how the projected change in the distribution of the parameters will affect the period, speed, and severity of pine beetle spread. We find that simulated beetle outbreaks move more quickly than historically and are more severe.

ecology↗

bioRxiv2024

Eruptive insect outbreaks from endemic populations under climate change

Insects, especially forest pests, are frequently characterized by eruptive dynamics. These types of species can stay at low, endemic population densities for extended periods of time before erupting in large-scale outbreaks. We here present a mechanistic model of these dynamics for mountain pine beetle. This extends a recent model that describes key aspects of mountain pine beetle biology coupled with a forest growth model by additionally including a fraction of low-vigor trees. These low-vigor trees, which may represent hosts with weakened defenses from drought, disease, other bark beetles, or other stressors, give rise to an endemic equilibrium in biologically plausible parameter ranges. The mechanistic nature of the model allows us to study how each model parameter affects the existence and size of the endemic equilibrium. We then show that under certain parameter shifts that are more likely under climate change, the endemic equilibrium can disappear entirely, leading to an outbreak.

ecology↗

bioRxiv2024

Mountain pine beetle spread in forests with varying host resistance

In the last few decades, mountain pine beetle (MPB) have spread into novel regions in Canada. An important aspect seldom captured in models of MPB spread is host resistance. Lodgepole pine, the predominant host of MPB, varies in resistance across the landscape. There is evidence for a genetic component of resistance, as well as evidence that hosts in areas where MPB has not been present historically are at risk of increased susceptibility. In addition to the spatially varying resistance of the primary host species, the eastward spread of MPB has brought them into jack pine forests. Host resistance in jack pine remains uncertain, but experiments indicate jack pine could be a suitable host. We develop a model of pine beetle spread that links pine beetle population dynamics and forest structure and resistance. We find that beetle outbreaks in the model are characterized by large transient outbreaks that move through the forest. We show how the speed of these outbreaks changes with host resistance and find that biologically plausible values for host resistance are able to stop the wave from advancing. We also find that near the threshold of resistance where the wave is able to advance, small changes in host resistance dramatically decrease the severity of the outbreak. These results indicate that planting trees selected for higher MPB resistance on the landscape may be able to slow or even stop the local spread of MPB. In terms of further eastward spread, our results indicate future outbreaks may move more quickly and be more severe if novel lodgepole pine hosts are indeed more susceptible to beetle attacks, although more research is needed into the susceptibility of jack pine.

ecology↗

bioRxiv2023

Coupling mountain pine beetle and forest population dynamics predicts transient outbreaks that are likely to increase in number with climate change

Mountain pine beetle (MPB) in Canada have spread well beyond their historical range. Accurate modelling of the long-term dynamics of MPB is critical for assessing the risk of further expansion and informing management strategies, particularly in the context of climate change and variable forest resilience. Most previous models have focused on capturing a single outbreak without tree replacement. While these models are useful for understanding MPB biology and outbreak dynamics, they cannot accurately model long-term forest dynamics. Past models that incorporate forest growth tend to simplify beetle dynamics. We present a new model that couples forest growth to MPB population dynamics and accurately captures key aspects of MPB biology, including a threshold for the number of beetles needed to overcome tree defenses and beetle aggregation that facilitates mass attacks. These mechanisms lead to a demographic Allee effect, which is known to be important in beetle population dynamics. We show that as forest resilience decreases, a fold bifurcation emerges and there is a stable fixed point with a non-zero MPB population. We derive conditions for the existence of this equilibrium. We then simulate biologically relevant scenarios and show that the beetle population approaches this equilibrium with transient boom and bust cycles with period related to the time of forest recovery. As forest resilience decreases, the Allee threshold also decreases. Thus, if host resilience decreases under climate change, for example under increased stress from drought, then the lower Allee threshold makes transient outbreaks more likely to occur in the future. Statements and DeclarationsO_ST_ABSCompeting interestsC_ST_ABSThe authors declare no competing interests. Data availability statementData sharing is not applicable to this article as no datasets were generated or analysed during the current study. Code to produce the figures is available at github.com/micbru/MPBModel/.

ecology↗

bioRxiv2021

The GA4GH Variation Representation Specification (VRS): a Computational Framework for the Precise Representation and Federated Identification of Molecular Variation

Maximizing the personal, public, research, and clinical value of genomic information will require that clinicians, researchers, and testing laboratories exchange genetic variation data reliably. Developed by a partnership among national information resource providers, public initiatives, and diagnostic testing laboratories under the auspices of the Global Alliance for Genomics and Health (GA4GH), the Variation Representation Specification (VRS, pronounced "verse") is an extensible framework for the semantically precise and computable representation of variation that complements contemporary human-readable and flat file standards for variation representation. VRS objects are designed to be semantically precise representations of variation, and leverage this design to enable unique, federated identification of molecular variation. We describe the components of this framework, including the terminology and information model, schema, data sharing conventions, and a reference implementation, each of which is intended to be broadly useful and freely available for community use. The specification, documentation, examples, and community links are available at https://vrs.ga4gh.org/.

bioinformatics↗

bioRxiv2016

The Monarch Initiative: Insights across species reveal human disease mechanisms

The principles of genetics apply across the whole tree of life: on a cellular level, we share mechanisms with species from which we diverged millions or even billions of years ago. We can exploit this common ancestry at the level of sequences, but also in terms of observable outcomes (phenotypes), to learn more about health and disease for humans and all other species. Applying the range of available knowledge to solve challenging disease problems requires unified data relating genomics, phenotypes, and disease; it also requires computational tools that leverage these multimodal data to inform interpretations by geneticists and to suggest experiments. However, the distribution and heterogeneity of databases is a major impediment: databases tend to focus either on a single data type across species, or on single species across data types. Although each database provides rich, high-quality information, no single one provides unified data that is comprehensive across species, biological scales, and data types. Without a big-picture view of the data, many questions in genetics are difficult or impossible to answer. The Monarch Initiative (https://monarchinitiative.org) is an international consortium dedicated to providing computational tools that leverage a computational representation of phenotypic data for genotype-phenotype analysis, genomic diagnostics, and precision medicine on the basis of a large-scale platform of multimodal data that is deeply integrated across species and covering broad areas of disease.

evolutionary biology↗