Erosion, vegetation and the evolution of hillslopes in upland landscapes

The geomorphic and geochemical characteristics of landscapes impose a physical template on the establishment and development of ecosystems. Conversely, vegetation is a key geomorphic agent, actively involved both soil production and sediment transport. The evolution of hillslopes and the ecosystems that populate them, are thus intimately coupled; their co-dependence potentially has a profound impact on the way in which landscapes respond to environmental change. This thesis explores how rates of erosion, integrated over millennia, impact on the structural characteristics of the mixed conifer forest that presently mantles this landscape, the development of the underlying soils and emergence of bedrock. The focus for this investigation is the Feather River Region in the northern Sierra Nevada in California, a landscape characterised by a striking geomorphic gradient accompanied by spatial variations in erosion rate spanning over an order of magnitude, from 20 mm ka-1 to over 250 mm ka-1. Using LiDAR data to quantify forest structure, I demonstrate that increasing rates of erosion drive a reduction in canopy height and aboveground biomass. Subsequently, I exploit a novel method to map rock exposure, based on a metric of topographic roughness, to show that as erosion rates increase and soil thickness consequently decreases, the degree of bedrock exposed on hillsides increases. Importantly, this soil-bedrock transition is gradual, with rapidly eroding hillslopes frequently possessing a mosaic of bedrock outcrop and intermittent soil mantle. Both the ecological and geomorphic trends are shown to be impacted by the underlying bedrock, which provides an additional source of heterogeneity in the evolution of the Feather River landscape. The negative correlation between AGB and erosion rate has potential implications for soil production. Using a simple hillslope model I show that if this decrease in AGB is associated with a drop in biotic soil production, then feedbacks between soil thickness and biotic soil production are capable of generating a complex response to geomorphic forcing, such that hillslopes possess multiple stable states: for intermediate rates of erosion, equilibrium hillslopes may be either soil mantled or bedrock. Hillslope evolution in these simulations is path dependent; once exposed at the surface, significant patches of bedrock exposure may persist over a wide range of incision rates

Parameter uncertainty dominates C-cycle forecast errors over most of Brazil for the 21st century

Identification of terrestrial carbon (C) sources and sinks is critical for understanding the Earth system as well as mitigating and adapting to climate change resulting from greenhouse gas emissions. Predicting whether a given location will act as a C source or sink using terrestrial ecosystem models (TEMs) is challenging due to net flux being the difference between far larger, spatially and temporally variable fluxes with large uncertainties. Uncertainty in projections of future dynamics, critical for policy evaluation, has been determined using multi-TEM intercomparisons, for various emissions scenarios. This approach quantifies structural and forcing errors. However, the role of parameter error within models has not been determined. TEMs typically have defined parameters for specific plant functional types generated from the literature. To ascertain the importance of parameter error in forecasts, we present a Bayesian analysis that uses data on historical and current C cycling for Brazil to parameterise five TEMs of varied complexity with a retrieval of model error covariance at 1g spatial resolution. After evaluation against data from 2001-2017, the parameterised models are simulated to 2100 under four climate change scenarios spanning the likely range of climate projections. Using multiple models, each with per pixel parameter ensembles, we partition forecast uncertainties. Parameter uncertainty dominates across most of Brazil when simulating future stock changes in biomass C and dead organic matter (DOM). Uncertainty of simulated biomass change is most strongly correlated with net primary productivity allocation to wood (NPPwood) and mean residence time of wood (MRTwood). Uncertainty of simulated DOM change is most strongly correlated with MRTsoil and NPPwood. Due to the coupling between these variables and C stock dynamics being bi-directional, we argue that using repeat estimates of woody biomass will provide a valuable constraint needed to refine predictions of the future carbon cycle. Finally, evaluation of our multi-model analysis shows that wood litter contributes substantially to fire emissions, necessitating a greater understanding of wood litter C cycling than is typically considered in large-scale TEMs

Isolating the effects of forest regrowth and functional adjustments upon global change impacts on Yucatán's forest biomass

Tropical forests hold large stocks of carbon in biomass and face pressures from changing climate and anthropogenic disturbance. Understanding the impact of these pressures on biomass is vital for effective forest management and conservation over the next century. Forests' capacity to store biomass under future conditions and accumulate biomass during regrowth after clearance are major knowledge gaps. Here we use chronosequence data, satellite observations and a C-cycle process model to diagnose woody C dynamics in two major dry forest ecotypes (semi-deciduous and semi-evergreen) in Yucatán, Mexico. Woody biomass differences between mature semi-deciduous (90 MgC/ha) and semi-evergreen (175 MgC/ha) forest landscapes are mostly explained by differences in climate (c. 60%), particularly temperature, humidity and soil moisture effects on production. Functional variation in foliar phenology, woody allocation, and wood turnover rate explained c. 40% of biomass differences between ecotypes. Modelling experiments explored varied forest clearance and regrowth cycles, under a range of climate and CO2 change scenarios up to 2100. Climate scenario projections indicate that production and steady state biomass in both ecotypes were reduced by forecast warming and drying (mean biomass 2021-2100 reduced 16-19% compared to 2001-2020), but compensated by fertilisation from rising CO2. Functional analysis indicates that trait adjustments could amplify biomass losses by c. 70%. Experiments with disturbance and recovery across historically reported levels for the Yucatán indicate reductions to mean forest biomass stocks over 2021-2100 similar in magnitude to climate change impacts (10-19% reductions for disturbance with recovery). Forest disturbance without regrowth amplifies biomass loss by three- or four-fold. Our results identify the potential for functional adjustments, hypothesised to limit climate risks, to magnify biomass reductions over the coming century. However, the range of impacts of land use and land use change are as, or more, substantive than the totality of direct and indirect climate impacts. The dataset is related to the upcoming publication "Isolating the effects of regrowth and functional adjustments on climate and land use impacts on Yucatán's forest biomass in the twenty-first century" (in review)