| Abstract |
Arbutus menziesii is a coastal evergreen tree observed to be in decline over the last 50 years. The cause of its decline has been associated with climate change resulting in a reduction in its habitat and the increased presence of fungal pathogens, yet the relative importance, and temporal effects of these threats are unknown, and considered variable throughout the range of this species. By examining subpopulations across A. menziesii’s range for forecasted suitable habitat and Pacific Madrone Leaf Blight (PMLB) risk, I assessed the relative range-wide, temporal effects and potential contributions to decline. Subpopulation delineation is a challenge for species lacking range-wide genetic information, like A. menziesii. This thesis used a novel subpopulation clustering method integrating both isolation by distance and environment to establish coarse-scale subpopulations. Data for subpopulation clustering and forecasting were sourced from the Global Biodiversity Information Facility (GBIF) (n = ~ 18 000) offering range-wide representation of A. menziesii. Herbarium data also sourced from the GBIF (n = ~600) spanned the last 120 years, also offering range-wide representation of A. menziesii. Four subpopulation delineation methods were compared using geographic and environmental isolation clusters. The highest performing subpopulation model used both isolation by distance and isolation by environment and could better discriminate presence and background points at the local scale compared to the whole species model and other subpopulation delineation method models. The PMLB scored herbaria dataset was combined with ClimateNA climate variables from the historical and 13 GCM ensembled SSP3-7.0 future time series to model blight risk from 1901-2100 for whole species and subpopulations. Chelsa historical and future climate bioclimatic predictors from SSP3-7.0 were used to build an SDM and forecast suitable habitat for whole species and subpopulation models. Whole species and subpopulations differed in their blight risk and forecasted suitable habitat. Subpopulation models produced a more optimistic suitable habitat forecast, with a percent decrease compared to historical of 3%. Whole species models produced less optimistic suitable habitat forecasts, with a percent decrease compared to historical of 12%. Both models show southern range contraction and northern range expansion, though the subpopulation model predicts more north-central area. Whole species blight risk from historical herbaria data shows little change in blight prevalence from 1901-2023, however subpopulations had significantly different blight prevalence. Northern subpopulations had the highest blight prevalence and southern subpopulations had the lowest blight prevalence. Whole species forecasting found blight risk unchanged but was significantly different for subpopulations through time. Blight risk is predicted to decrease for northern subpopulations, increase for southern subpopulations and stay unchanged for central subpopulations. Comparing both the forecasted species distribution models and PMLB risk maps suggests that southern populations are likely to be under double the pressure of both climate change moving them out of their preferred habitat, and increased PMLB presence where they historically experienced a lower incidence. Given the predicted shift north of suitable habitat for species, safeguarding the southern population for translocation may be important if southern conditions transfer northward to reduce the decline of A. menziesii.
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