Browsing by Subject "restortion"

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    Climate-informed restoration of white pine: Impacts of seed source, planting site, and earthworms
    (2016-11) Mead, Jordan
    Habitat suitability for forest species is expected to shift with changes in climate, resulting in new and altered species assemblages. These alterations will be most notable near species boundaries, where feedbacks between disturbance, regeneration and recruitment are especially sensitive to temperature. How forest ecosystems respond will depend on the rate of climate change, dominant disturbance regime, the arrival of suitable propagules and the ability of those propagules to survive local climate, herbivory, invasive species and interspecific competition. Local adaptation of tree populations has been well documented in common garden experiments and may have a significant impact on the regeneration and recruitment in disturbed forests. In Northern Minnesota, USA, forest-climate models predict large-scale shifts in forest cover, and climate-driven changes in forest regeneration have already been documented at ecotone boundaries. Local populations of white pine (Pinus strobus) that are expected to increase may not be able to survive and reproduce successfully due to population bottlenecks, slow migration rates, habitat fragmentation, and intense herbivory. This is coupled with reduced reproduction of other temperate species, such as maples (Acer spp.), by herbivory and introduced detritivores. Given the rate of climate change, the migration and evolution of locally adapted populations and species are expected to lag behind optimal climate. My work documents restoration of white pine to assess the effects of seed source climate and site attributes, such as light environment and earthworm abundance, on survival, growth and phenology of planted seedlings. I also investigate the impacts and abundance of non-native earthworms in disturbed areas, as well as the surrounding intact forest to look for interactions between these invaders and disturbance. This data could be further used to improve models and inform management that will help sustain forest health and productivity.