Donal Mullan

Ecology of testate amoebae in an Amazonian peatland and development of a transfer function for palaeohydrological reconstruction.

Tropical peatlands represent globally important carbon sinks with a unique biodiversity and are currently threatened by climate change and human activities. It is now imperative that proxy methods are developed to understand the ecohydrological dynamics of these systems and for testing peatland development models. Testate amoebae have been used as environmental indicators in ecological and palaeoecological studies of peatlands, primarily in ombrotrophic Sphagnum-dominated peatlands in the mid- and high-latitudes. We present the first ecological analysis of testate amoebae in a tropical peatland, a nutrient-poor domed bog in western (Peruvian) Amazonia. Litter samples were collected from different hydrological microforms (hummock to pool) along a transect from the edge to the interior of the peatland. We recorded 47 taxa from 21 genera. The most common taxa are Cryptodifflugia oviformis, Euglypha rotunda type, Phryganella acropodia, Pseudodifflugia fulva type and Trinema lineare. One species found only in the southern hemisphere, Argynnia spicata, is present. Arcella spp., Centropyxis aculeata and Lesqueresia spiralis are indicators of pools containing standing water. Canonical correspondence analysis and non-metric multidimensional scaling illustrate that water table depth is a significant control on the distribution of testate amoebae, similar to the results from mid- and high-latitude peatlands. A transfer function model for water table based on weighted averaging partial least-squares (WAPLS) regression is presented and performs well under cross-validation (rapparent2=0.76,RMSE=4.29;rjack2=0.68,RMSEP=5.18

The long-term fate of permafrost peatlands under rapid climate warming.

^{2}_{apparent} \,=\, 0.76, \text {RMSE} \,=\, 4.29; \mathrm {r}^{2}_{jack} \,=\, 0.68, \text {RMSEP} \,=\, 5.18

Validation of non‑stationary precipitation series for site‑specific impact assessment: comparison of two statistical downscaling techniques

). The transfer function was applied to a 1-m peat core, and sample-specific reconstruction errors were generated using bootstrapping. The reconstruction generally suggests near-surface water tables over the last 3,000 years, with a shift to drier conditions at c. cal. 1218-1273 AD.

Modelling the impacts of climate change on future rates of soil erosion: Addressing key limitations

Permafrost peatlands contain globally important amounts of soil organic carbon, owing to cold conditions which suppress anaerobic decomposition. However, climate warming and permafrost thaw threaten the stability of this carbon store. The ultimate fate of permafrost peatlands and their carbon stores is unclear because of complex feedbacks between peat accumulation, hydrology and vegetation. Field monitoring campaigns only span the last few decades and therefore provide an incomplete picture of permafrost peatland response to recent rapid warming. Here we use a high-resolution palaeoecological approach to understand the longer-term response of peatlands in contrasting states of permafrost degradation to recent rapid warming. At all sites we identify a drying trend until the late-twentieth century; however, two sites subsequently experienced a rapid shift to wetter conditions as permafrost thawed in response to climatic warming, culminating in collapse of the peat domes. Commonalities between study sites lead us to propose a five-phase model for permafrost peatland response to climatic warming. This model suggests a shared ecohydrological trajectory towards a common end point: inundated Arctic fen. Although carbon accumulation is rapid in such sites, saturated soil conditions are likely to cause elevated methane emissions that have implications for climate-feedback mechanisms.

Soil erosion on agricultural land in the north of Ireland: past, present and future potential

Statistical downscaling (SD) methods have become a popular, low-cost and accessible means of bridging the gap between the coarse spatial resolution at which climate models output climate scenarios and the finer spatial scale at which impact modellers require these scenarios, with various different SD techniques used for a wide range of applications across the world. This paper compares the Generator for Point Climate Change (GPCC) model and the Statistical DownScaling Model (SDSM)—two contrasting SD methods—in terms of their ability to generate precipitation series under non-stationary conditions across ten contrasting global climates. The mean, maximum and a selection of distribution statistics as well as the cumulative frequencies of dry and wet spells for four different temporal resolutions were compared between the models and the observed series for a validation period. Results indicate that both methods can generate daily precipitation series that generally closely mirror observed series for a wide range of non-stationary climates. However, GPCC tends to overestimate higher precipitation amounts, whilst SDSM tends to underestimate these. This infers that GPCC is more likely to overestimate the effects of precipitation on a given impact sector, whilst SDSM is likely to underestimate the effects. GPCC performs better than SDSM in reproducing wet and dry day frequency, which is a key advantage for many impact sectors. Overall, the mixed performance of the two methods illustrates the importance of users performing a thorough validation in order to determine the influence of simulated precipitation on their chosen impact sector.

Addressing key limitations associated with modelling soil erosion under the impacts of future climate change

Future climate change is expected to impact the extent, frequency, and magnitude of soil erosion in a variety of ways. The most direct of these impacts is the projected increase in the erosive power of rainfall owing to an increase in the moisture-holding capacity of the atmosphere, but other more indirect impacts include changes in plant biomass and shifts in land use to accommodate the new climatic regime. Given the potential for climate change to increase soil erosion and its associated adverse impacts, modelling future rates of erosion is a crucial step in its assessment as a potential future environmental problem, and as a basis to help advise future conservation strategies. In this study, the Water Erosion Prediction Project (WEPP) model is used to simulate the impacts of climate change on future rates of soil erosion for a case study hillslope in Northern Ireland for three future time periods centered on the 2020s, 2050s and 2080s. Despite the wide range of previous modelling studies, in the majority of cases a number of limitations are apparent with respect to their treatment of the direct impacts (changed climate data), and their failure to factor in the indirect impacts (changing land use and management). In addressing the need for site-specific climate change impacts, for example, many previous studies have attempted to downscale future climate change output from general circulation models (GCMs). The most popular downscaling approach in future soil erosion studies is the change factor method, yet this approach possesses severe limitations with respect to modelling future erosion rates since it incorporates only changes in the mean climate and fails to account for climate variability. In order to address this limitation, statistical downscaling methods are used in this study to downscale future climate change projections using three GCMs and two emissions scenarios, providing daily site-specific climate inputs to WEPP in a manner that incorporates both changes in the mean climate and its variability. The temporal scale of climate change projections is also a key limitation with respect to modelling future erosion rates. The most severe soil losses often occur in high intensity rainfall events that occur over very short time intervals, yet input to soil erosion models tends to be at a daily resolution. Given the decreasing confidence of future climate change projections at a sub-daily temporal resolution, a sensitivity analysis approach is used in this study to perturb the sub-daily rainfall intensity parameter in WEPP. In addition, most previous studies fail to account for the indirect impacts of climate change on soil erosion, with no change in land use and management often assumed. Here, a scenarios-based approach is employed to examine the impacts of changing crop cover and management on future rates of soil erosion. Results indicate a mix of soil erosion increases and decreases, depending on which scenarios are considered. Downscaled climate change projections in isolation generally result in erosion decreases, whereas large increases are projected when land use is changed from the current cover of grass to a row crop which requires annual tillage, and/or where large changes in sub-daily rainfall intensity are applied. The overall findings illustrate the potential for increased soil erosion under future climate change, and illuminate the need to address key limitations in previous studies with respect to the treatment of future climate change projections, and crucially, the factoring in of future land use and management.

Soil erosion under the impacts of future climate change: Assessing the statistical significance of future changes and the potential on-site and off-site problems

Soil erosion in Ireland is a considerable environmental problem with respect to the ‘off-site’ transport of sediment and pollutants out of fields and into nearby water courses and the neighbouring environment. This paper examines this important issue by presenting evidence for past and present-day soil erosion in Ireland through the use of secondary documentary and primary observational evidence. An original modelling-based study is also conducted at six locations across the north of Ireland in order to project future soil erosion rates for Ireland under a changing environment. Results reveal that numerous incidences of soil erosion occur across Ireland in the present day, and that past erosion was more widespread due to increased cultivation to support a growing pre-famine population. Projected rates of soil erosion under the impacts of future climate change reveal the potential for increased erosion and indicate that off-site impacts associated with declining water quality and ‘muddy flooding’ of infrastructure and property may become more widespread in the future. This illuminates the need to begin monitoring the problem in the present day in order to better manage a problem projected to escalate in the coming decades.