Role of recent climate change on carbon sequestration in peatland systems.

This paper provides information on the impact of recent climate change on carbon sequestration in peatland systems in South West England. This is important because peatlands have the potential to sequester and hold large quantities of anthropogenically released CO2. This paper investigates whether there has been a reduction in the strength of carbon sinks in a valley mire and blanket bog, which occur on the limits of the biogeographical envelop for peatlands in Britain. Past rates of carbon accumulation were calculated from peat depth and the sequential analysis of peat age, bulk density and carbon content from cores taken from valley mire and blanket bog. At the valley mire site contemporary net ecosystem carbon balance (NECB) was calculated by measuring inputs to the peat body, via net primary productivity (NPP), of Sphagna. Losses of C from the peat body were calculated by measuring CH4, and aquatic carbon, calculated from catchment export of particulate and dissolved organic carbon. The study found similar mean rates of carbon accumulation since 1850 of 11.26 t ± 0.68 t CO2e ha-1 yr-1 (307 g C m-2 yr-1) in valley mire and 11.77 t ± 0.88 t CO2e ha-1 yr-1 (321 g C m-2 yr-1) in blanket bog. The mean present-day CO2 sequestration rate for Sphagna on valley mire was calculated to be 9.13 t ± 0.98 t CO2e ha-1 yr-1 (249 g C m-2 yr-1). Both past and contemporary rates of CO2 sequestration were found to be at the maxima of those reported for temperate peatlands. NPP was found to vary according to microform with higher rates of carbon sequestration found in lawn and hummock microforms compared with pools. Our work suggests that recent changes in the climate appear to have had limited impact on the strength of peatland carbon sinks in South West England

Quantified moorland vegetation and assessment of the role of burning over the past five millennia

© 2017 International Association for Vegetation Science. Aims: To apply the Landscape Reconstruction Algorithm (LRA) to pollen count data from multiple sites to estimate local vegetation abundance and compare with charcoal-derived records of burning. Location: Exmoor, southwest England, UK. Methods: Pollen count data from 16 sites were transformed to estimates of distance-weighted vegetation abundance using the LRA (REVEALS and LOVE models), correcting for bias in pollen production and dispersal. Charcoal concentration data from six sites were normalized using Box-Cox transformation to produce z-scores. Moving-window correlation was undertaken to compare pollen percentage values for key taxa (Calluna, Poaceae) and localized burning. Estimates of distance-vegetation abundance (LRA output) and time-averaged charcoal z-scores were compared to assess the role of burning as a driver for upland vegetation cover. Results: Comparison of pollen percentage and normalized charcoal z-scores show little correlation between vegetation cover and burning. Estimates of distance-weighted vegetation abundance and normalized charcoal data show relationships between vegetation change and burning at four of the six sites. The relationships are site-specific: three sites suggest burning promoted grass-dominated vegetation, at one site burning promoted heather-dominated vegetation, and in two sites there is no apparent relationship. Conclusions: The patterning of vegetation within uplands is a crucial part of ecosystem service delivery, and contemporary and future management benefits from understanding of 'long-term' development, i.e. patterns over millennia. The correction of biases within pollen production and dispersal to produce local vegetation estimates has demonstrated spatial heterogeneity in vegetation cover on Exmoor that is not otherwise evident in the pollen percentage data (which retain a strong influence of the regional vegetation cover). The relationship between LRA-derived vegetation cover and burning is not apparent in comparisons between pollen percentage data and charcoal records. This implies that studies that use pollen proportional data alone can misrepresent the relationship between vegetation cover and fire. This study demonstrates that fire has been an important part of the development of this cultural landscape

Europe's lost forests: a pollen-based synthesis for the last 11,000 years

8000 years ago, prior to Neolithic agriculture, Europe was mostly a wooded continent. Since then, its forest cover has been progressively fragmented, so that today it covers less than half of Europe’s land area, in many cases having been cleared to make way for fields and pasture-land. Establishing the origin of Europe’s current, more open land-cover mosaic requires a long-term perspective, for which pollen analysis offers a key tool. In this study we utilise and compare three numerical approaches to transforming pollen data into past forest cover, drawing on >1000 14C-dated site records. All reconstructions highlight the different histories of the mixed temperate and the northern boreal forests, with the former declining progressively since ~6000 years ago, linked to forest clearance for agriculture in later prehistory (especially in northwest Europe) and early historic times (e.g. in north central Europe). In contrast, extensive human impact on the needle-leaf forests of northern Europe only becomes detectable in the last two millennia and has left a larger area of forest in place. Forest loss has been a dominant feature of Europe’s landscape ecology in the second half of the current interglacial, with consequences for carbon cycling, ecosystem functioning and biodiversity

Mapping upland peat depth using airborne radiometric and lidar survey data

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record.A method to estimate peat depth and extent is vital for accurate estimation of carbon stocks and to facilitate appropriate peatland management. Current methods for direct measurement (e.g. ground penetrating radar, probing) are labour intensive making them unfeasible for capturing spatial information at landscape extents. Attempts to model peat depths using remotely sensed data such as elevation and slope have shown promise but assume a functional relationship between current conditions and gradually accrued peat depth. Herein we combine LiDAR-derived metrics known to influence peat accumulation (elevation, slope, topographic wetness index (TWI)) with passive gamma-ray spectrometric survey data, shown to correlate with peat occurrence to develop a novel peat depth model for Dartmoor. Total air absorbed dose rates of Thorium, Uranium and Potassium were calculated, referred to as radiometric dose. Relationships between peat depth, radiometric dose, elevation, slope and TWI were trained using 1334 peat depth measurements, a further 445 measurements were used for testing. All variables showed significant relationships with peat depth. Linear stepwise regression of natural log-transformed variables indicated that a radiometric dose and slope model had an r2 = 0.72/0.73 and RMSE 0.31/0.31 m for training/testing respectively. This model estimated an area of 158 ±101 km2 of peaty soil >0.4 m deep across the study area. Much of this area (60 km2) is overlain by grassland and therefore may have been missed if vegetation cover was used to map peat extent. Using published bulk density and carbon content values we estimated 13.1 Mt C (8.1-21.9 Mt C) are stored in the peaty soils within the study area. This is an increase on previous estimates due to greater modelled peat depth. The combined use of airborne gamma-ray spectrometric survey and LiDAR data provide a novel, practical and repeatable means to estimate peat depth with no a priori knowledge, at an appropriate resolution (10 m) and extent (406 km2) to facilitate management of entire peatland complexes.The authors would like to thank the anonymous reviewers for the thorough reviews, their suggestions improved this paper. This work was supported by South West Water [SK06855], Dartmoor National Park Authority [SK07279] and the South West Partnership for Environmental and Economic Prosperity (SWEEP). SWEEP was funded by the Natural Environment Research Council (NE/P011217/1)

Nonlinear landscape and cultural response to sea-level rise

Rising sea levels have been associated with human migration and behavioral shifts throughout prehistory, often with an emphasis on landscape submergence and consequent societal collapse. However, the assumption that future sea-level rise will drive similar adaptive responses is overly simplistic. While the change from land to sea represents a dramatic and permanent shift for preexisting human populations, the process of change is driven by a complex set of physical and cultural processes with long transitional phases of landscape and socioeconomic change. Here, we use reconstructions of prehistoric sea-level rise, paleogeographies, terrestrial landscape change, and human population dynamics to show how the gradual inundation of an island archipelago resulted in decidedly nonlinear landscape and cultural responses to rising sea levels. Interpretation of past and future responses to sea-level change requires a better understanding of local physical and societal contexts to assess plausible human response patterns in the future

Diffusion of e-health innovations in 'post-conflict' settings: a qualitative study on the personal experiences of health workers.

BACKGROUND: Technological innovations have the potential to strengthen human resources for health and improve access and quality of care in challenging 'post-conflict' contexts. However, analyses on the adoption of technology for health (that is, 'e-health') and whether and how e-health can strengthen a health workforce in these settings have been limited so far. This study explores the personal experiences of health workers using e-health innovations in selected post-conflict situations. METHODS: This study had a cross-sectional qualitative design. Telephone interviews were conducted with 12 health workers, from a variety of cadres and stages in their careers, from four post-conflict settings (Liberia, West Bank and Gaza, Sierra Leone and Somaliland) in 2012. Everett Roger's diffusion of innovation-decision model (that is, knowledge, persuasion, decision, implementation, contemplation) guided the thematic analysis. RESULTS: All health workers interviewed held positive perceptions of e-health, related to their beliefs that e-health can help them to access information and communicate with other health workers. However, understanding of the scope of e-health was generally limited, and often based on innovations that health workers have been introduced through by their international partners. Health workers reported a range of engagement with e-health innovations, mostly for communication (for example, email) and educational purposes (for example, online learning platforms). Poor, unreliable and unaffordable Internet was a commonly mentioned barrier to e-health use. Scaling-up existing e-health partnerships and innovations were suggested starting points to increase e-health innovation dissemination. CONCLUSIONS: Results from this study showed ICT based e-health innovations can relieve information and communication needs of health workers in post-conflict settings. However, more efforts and investments, preferably driven by healthcare workers within the post-conflict context, are needed to make e-health more widespread and sustainable. Increased awareness is necessary among health professionals, even among current e-health users, and physical and financial access barriers need to be addressed. Future e-health initiatives are likely to increase their impact if based on perceived health information needs of intended users

Trajectories of change in Mediterranean Holocene vegetation through classification of pollen data

© 2017 Springer-Verlag GmbH Germany, part of Springer Nature Quantification of vegetation cover from pollen analysis has been a goal of palynologists since the advent of the method in 1916 by the great Lennart von Post. Pollen-based research projects are becoming increasingly ambitious in scale, and the emergence of spatially extensive open-access datasets, advanced methods and computer power has facilitated sub-continental analysis of Holocene pollen data. This paper presents results of one such study, focussing on the Mediterranean basin. Pollen data from 105 fossil sequences have been extracted from the European Pollen database, harmonised by both taxonomy and chronologies, and subjected to a hierarchical agglomerative clustering method to synthesise the dataset into 16 main groupings. A particular focus of analysis was to describe the common transitions from one group to another to understand pathways of Holocene vegetation change in the Mediterranean. Two pollen-based indices of human impact (OJC: Oleaceae, Juglans, Castanea; API: anthropogenic pollen indicators) have been used to infer the degree of human modification of vegetation within each pollen grouping. Pollen-inferred cluster groups that are interpreted as representing more natural vegetation states show a restricted number of pathways of change. A set of cluster groups were identified that closely resemble anthropogenically-disturbed vegetation, and might be considered anthromes (anthopogenic biomes). These clusters show a very wide set of potential pathways, implying that all potential vegetation communities identified through this analysis have been altered in response to land exploitation and transformation by human societies in combination with other factors, such as climatic change. Future work to explain these ecosystem pathways will require developing complementary datasets from the social sciences and humanities (archaeology and historical sources), along with synthesis of the climatic records from the region