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  • The impact of boreal wildfires on carbon and nitrogen dynamics: the interplay between biotic and abiotic processes

    Purpose and aims

    Wildfires are a natural phenomenon but human activities are altering both the driving factors (climate) and the vulnerability (land-use factors) of ecosystems, increasing both frequency and severity of fire impacts. This is an issue of concern given that wildfires play a major role in the global carbon cycle by affecting carbon and nitrogen storage in ecosystems. Yet, our knowledge of early post-fire carbon (C) and nitrogen (N) (hereafter abbreviated as CN) dynamics has been severely limited by the lack of cross-scale (from soil to plant to ecosystem) and cross-landscape (wetlands to uplands, managed and unmanaged land) studies. Understanding the mechanisms causing variability in CN dynamics (e.g., CN accumulation) , in heterogeneous landscapes, is critical for predicting changes in C and N storage with more frequent disturbance. Given this immediate research need, I propose an ambitious research program to investigate the impact of wildfires on the C and N cycle in the boreal landscape, capitalizing on a recent stand-replacing wildfire in Sweden. With an array of paired pre- and post-fire data, which is rare in wildfire ecosystem research, I aim to address whether pre-disturbance and initial post-disturbance conditions can be used to formulate predictions of post-disturbance ecosystem development. I will employ a novel multidiciplinary framework, which integrates ecological process, like plant community development, into the biogeochemical processes. This much needed integration makes it possible to improve and add new mechanisms to current ecosystem models and to answer under what conditions is the system is most vulnerable to change under frequent and severe wildfires. Three question-based work packages are described below as the basis of this wildfire research program:

    1. CN losses. CN losses. Where in the landscape do the largest C and N losses occur, and what factors control losses? How large are CN combustion losses relative to C transformed into charcoal and hydrologically-exported CN following fire?

    2. CN pool development. What is the relative importance of abiotic (e.g. soil moisture, temperature) and biotic (e.g. plant traits) factors in generating variation in post-fire recovery rate of C and N pools at different spatial scales?

    3. Vegetation development. What controls species and trait assembly post-fire? What is the role of niche-based processes (abiotic effects: environmental filtering, and biotic effects: legacy effects, regeneration traits) in contrast to neutral processes (stochasticity, priority effects)?

    Survey of the field

    Boreal systems and the role of wildfire

    Wildfires have a large impact on the boreal carbon and nitrogen cycle (Bond-Lamberty 2007, Smithwick 2005). Large CO2 emission to the atmosphere from more frequent and larger wildfires can have a positive climate change feedback if the C is not swiftly re-sequestered. Furthermore, the boreal forests are N limited (Tamm 1991) and fire induced N losses may provide a strong control on post-fire productivity, and consequently long-term C storage (soil, standing biomass). Land-use practice, like drainage and forestry, may further increasing the vulnerability of the ecosystem to lose CN during and after fires, possibly leading to regime shifts (Kettridge 2015). Thus, there is a pressing need for ecosystem models to accurately capture C and N losses due to wildfire, and C and N build-up during the post-fire succession.

    Despite recent efforts to study wildfire effects on biogeochemistry and vegetation, few studies have attempted to connect biotic and abiotic processes and their contribution to the landscape complexity that emerges after fire (Hollingsworth 2013). To understand these processes, and how they affect resilience and stability of the ecosystem, cross-scale and cross-landscape are need to capture the “functional mosaic” of the landscape (Turner 2010, Holling 1973). However, most studies on post-fire ecosystem development have relied on chronosequence designs (space for time substitution), which are unable to resolve fine-scale processes and underlying mechanisms (Kashian 2013). Studies have suggested that burn severity (i.e. CN loss) largely regulates fine-scale processes (Schimmel 1996, Johnstone 2010), however, linking CN loss following fire, with plant assembly processes and ecosystem functions like CN dynamics, remains an unexplored line of research.

    The need for an integrative research approach is particularly true for soil processes and soil organic C, which accounts for a striking 85% of the total boreal C stock (Deluca 2012). Furthermore, despite the majority of C being stored in peatlands, cross-landscape studies covering both peatlands and uplands are surprisingly rare. Current process-based ecosystem models (e.g., Terrestrial Ecosystem Model, TEM)) are still lacking or fail to include these important abiotic-biotic interactions (Yi 2009). As a result, there can be estimation errors of the initial post-fire C stock and unaccounted differences in the early recovery phase, which can incorporate large biases in long-term C balance predictions generated by modelling (Kelly 2016). The present research program will address these knowledge gaps and in addition, advance fire-related ecosystem research by linking processes over various scales.

    C and N loss following fire

    The majority (up to 85%) of fire-emitted C in boreal upland forests originates from the organic soil layer and mosses/lichens (Turetsky 2011). Recent research shows that C-loss from moss dominated peatlands can be substantial, often in par with uplands, but few studies have included peatlands in their C-loss estimates after fire, or assumed an average C loss value (Turetsky 2011). Ignoring peatlands in C emission calculations can give large errors, particularly in areas with drained peatlands. My research suggests that drained peatlands are vulnerable to deep burns; yet, field data on C-losses from drained peatlands in Scandinavia and Russia (which contain >95% of the worlds drained boreal peatlands) is still lacking. In addition to combustion, C can be lost through run-off water. These lateral losses are of vital importance to the net ecosystem C balance, but to my knowledge, post-fire C-losses through waterways (e.g. DOC) have not been empirically compared to losses through combustion at a catchment scale. It has been hypothesized that DOC export can increase immediately after fire, but there is little evidence supporting this claim (Evans sub).

    Unlike C-emissions following fire, few studies have quantified fire-related N losses.In boreal systems, deep soil N-pools are less important for N dynamics compared to the top layer organic soil, which supplies plants with the majority of N (Tamm 1991). Hence, if a fire consumes the organic layer, it can influence ecosystem productivity by reducing plant available N. Fire can also transform organic N to inorganic forms that are available to plants, but with poorly developed post-fire plant communities, this N can be easily exported to streams and lakes (Smith 2011)(Granath et al. In prep). The different forms of N-losses (combustion and exportation) have not been previously compared, and whether exported N-losses are relevant at a catchment scale or not, remains unknown.

    C and N accumulation

    Post-fire C dynamics have been extensively studied, but mostly at the landscape scale (Bond-Lamberty 2007, Kashian 2013). Boreal forests likely function as a C source immediately after fire (1-10 yrs, (Amiro 2010)), until tree growth and soil C accumulation start to dominate over decomposition (Kashian 2013). The strong soil C-sink can be attributed to mosses, which dominate Net Primary Productivity (NPP) in wetter environments (mainly peat mosses) (Turetsky 2010). However, post-fire plant production has seldom been measured in peatlands, as well as post-fire N-accumulation patterns which remain largely unknown. Recovery of the N-pool has also received little attention in uplands, but it has been hypothesised that post-fire plants, if establish quickly, can retain the N before it is lost (Smithwick 2009). To what extent this is true, or at what temporal scale this process is important, is still to be resolved.

    Increased mineralization rates post-fire could occur through the release “locked in” nutrients (e.g., N) by charcoal. This nutrient release mechanisms has been shown to be particularly important in phenol-rich litter, produced by ericaceous dwarf shrubs or peat mosses (Wardle 1998, Freeman 2001). It is therefore suggested that the amount of charcoal is a good predictor of plant biomass recovery after fire (Wardle 1998). However, charcoal is rarely measured after fire and this prediction remains to be tested.

    Mechanisms controlling plant production and organic soil accumulation can be divided into abiotic and biotic, and their relative importance in regulating ecosystem properties is a long-standing research interest. Biotic factors are examined through the concept of functional traits, that is, variation in so-called “effect traits” (e.g., NPP, litter quality) determines variation in ecosystem functions (Lavorel 2002). Knowledge on the abiotic and biotic controls on NPP is extensive (Enquist 2007), yet the interplay of abiotic and biotic factors on soil decomposition is less known. Traditionally, abiotic factors, such as temperature and moisture, have been thought to regulate decomposition rates through their influence on decomposer organisms; while plant traits (i.e., litter quality) have been considered of less importance (Deluca 2012, Swift 1979). However, a recent synthesis suggests the opposite and in fact functional plant traits may play an even larger role than previously thought in controlling decomposition rates (Cornwell 2008). Plant effect traits can also interact directly with the abiotic factors and create negative feedbacks. For example, bryophytes can reduce the sub-surface temperature of soils by retaining water and shutting down evaporation when they dry out. Their negative effect on temperature and positive effect on moisture reduce decomposition rates, and thereby control nutrient availability for plants (Turetsky 2012). The interplay between abiotic and biotic factors is, however, poorly understood in this process (Turetsky 2012, Yi 2009). These unresolved issues of the relative importance of abiotic vs biotic factors, and frequent failure of litter incubation studies to explain mass losses, calls for more experimental work in this research field (Bradford 2016).

    Vegetation development

    CN accumulation processes (e.g. NPP, decomposition) are directly linked to plant traits, which in turn are the result of species assembly. Thus, to model CN accumulation processes in the landscape, a complete understanding of species assembly processes is required. Two main processes are involved in shaping species assembly: i) niche-based processes, driven by abiotic (e.g., environmental filtering - species that can establish and grow at a site), or biotic (e.g., species interactions, life history traits like regeneration strategies) factors, and ii) neutral processes (e.g., stochasticity - random colonization-extinction and priority effects where first arrivals can monopolize resources) (Weiher 2011).

    Post-fire species assembly has been shown to be controlled by burn severity (e.g., residual organic soil, living trees) which alters the relative importance of these assembly processes (Walker 1987, Schimmel 1996, Hollingsworth 2013). A lighter, milder burn has a large ecological inertia favoring re-sprouting plants over the seed and spore bank, and dispersers; thus, the pre-fire plant community is rapidly restored. In contrast, a severe burn exposes the mineral soil and dispersers will instead greatly affect species composition (Walker 1987, Schimmel 1996, Johnstone 2006, Shenoy 2011). Species assembly theory, and the link to functional traits (e.g., regeneration traits), provide an excellent framework to close the gap between biogeochemistry models and ecological models. However, so far this opportunity has been little explored.