ADAPTForRes: Assessing Forest resilience and carbon dynamics in differing Irish forest types to promote more sustainable sinks

Climate change poses a significant threat to the carbon (C) sequestration capacity of Irish forests, exacerbated by heightened risks from pests, pathogens, and escalating climate extremes, including drought and intense rainfall. Building resilience in forest ecosystems is vital to protecting the ecosystem services they deliver and has therefore gained increased attention from both research and industry. ADAPTForRes is a project dedicated to assessing forest management options and identifying enhanced climate-smart mitigation strategies.

In this study, we utilise Eddy Covariance (EC), soil chamber and biometric methodologies to investigate the C stock and flux dynamics of three distinct forest types: commercial Sitka spruce coniferous forest on mineral soil, broadleaf-dominated native woodland on mineral soil, and a mixed species (Norway spruce and Birch) forest on peat soil. Initial results suggest that the Sitka spruce forest nearing the end of its first rotation assimilates the most C, while the native deciduous broadleaved forest shows near C neutrality due to the age/maturity of the stand and high quantities of decaying biomass on the forest floor. The C dynamics of the Norway spruce/Silver birch mixed forest were dominated by high levels of ecosystem respiration driven by the high organic content of the soil and low water table heights in summer.

Furthermore, advanced footprint analyses have been employed to address the heterogenous nature of the native Irish forest studied here – acknowledging challenges posed by dynamic forest management practices, diversity in vegetative distribution and complex terrain. This approach provides additional insight into the flux dynamics from the forest compartments and encompasses management practices (thinning, clearfelling, underplanting), phenology (budburst, leaf expansion, senescence), inventory (species, ages, height), NDVI and disease outbreak information. The additional parameters generated from this analysis enhances data richness, allowing for a greater understanding of ecosystem C dynamics. Additionally, biometric stocks of C and soil derived C flux measurements including auto- and heterotrophic partitioning experiments have been conducted to further explore the impacts of forest composition and management on fluxes from wider ecosystem carbon pools.

These data are also being used in combination with the QUINCY land surface model to assess the model’s performance in capturing the effects of management, soil, forest type and climate on the ecosystem C balance. The EC data provides a foundational basis for the development and parameterization of the model, whereby ground-truthing is increasing our predictive capacity for future C budgets under various management regimes and varying magnitudes of climate change. The EC, biometric and soil flux data in combination with QUINCY model outputs will inform future management options for greater adaptability, as well as policy targets around strategic land-use goals for multifunctional and resilient forests.