Publications by year
In Press
Lenton T, Buxton J, Abrams J, Boulton C, Powell T, Cunliffe A (In Press). A resilience sensing system for the biosphere.
Philosophical Transactions of the Royal Society B: Biological SciencesAbstract:
A resilience sensing system for the biosphere
We are in a climate and ecological emergency, where climate change and direct anthropogenic interference with the biosphere are risking abrupt and/or irreversible changes that threaten our life-support systems. Efforts are underway to increase the resilience of some ecosystems that are under threat, yet collective awareness and action are modest at best. Here we highlight the potential for a biosphere resilience sensing system to make it easier to see where things are going wrong, and to see whether deliberate efforts to make things better are working. We focus on global resilience sensing of the terrestrial biosphere at high spatial and temporal resolution through satellite remote sensing, utilising the generic mathematical behaviour of complex systems – loss of resilience corresponds to slower recovery from perturbations, gain of resilience equates to faster recovery. We consider what subset of biosphere resilience remote sensing can monitor, critically reviewing existing studies. Then we present illustrative, global results for vegetation resilience and trends in resilience over the last 20 years, from both satellite data and model simulations. We close by discussing how resilience sensing nested across global, biome-ecoregion, and local ecosystem scales, could aid management and governance at these different scales, and identify priorities for further work.
Abstract.
Cunliffe A (In Press). Author responses to refaree feedback.
Cunliffe AM, Anderson K, Boschetti F, Brazier RE, Graham HA, Myers-Smith IH, Astor T, Boer MM, Calvo L, Clark PE, et al (In Press). Drone-derived canopy height predicts biomass across non-forest ecosystems globally.
Abstract:
Drone-derived canopy height predicts biomass across non-forest ecosystems globally
AbstractNon-forest ecosystems, dominated by shrubs, grasses and herbaceous plants, provide ecosystem services including carbon sequestration and forage for grazing, yet are highly sensitive to climatic changes. Yet these ecosystems are poorly represented in remotely-sensed biomass products and are undersampled by in-situ monitoring. Current global change threats emphasise the need for new tools to capture biomass change in non-forest ecosystems at appropriate scales. Here we assess whether canopy height inferred from drone photogrammetry allows the estimation of aboveground biomass (AGB) across low-stature plant species sampled through a global site network. We found mean canopy height is strongly predictive of AGB across species, demonstrating standardised photogrammetric approaches are generalisable across growth forms and environmental settings. Biomass per-unit-of-height was similar within, but different among, plant functional types. We find drone-based photogrammetry allows for monitoring of AGB across large spatial extents and can advance understanding of understudied and vulnerable non-forested ecosystems across the globe.
Abstract.
Cunliffe A, Anderson K (In Press). Measuring Above-ground Biomass with Drone Photogrammetry: Data Collection Protocol. Nature Protocol Exchange
2023
Zhu S, McCalmont J, Cardenas LM, Cunliffe AM, Olde L, Signori-Müller C, Litvak ME, Hill T (2023). Gap-filling carbon dioxide, water, energy, and methane fluxes in challenging ecosystems: Comparing between methods, drivers, and gap-lengths.
Agricultural and Forest Meteorology,
332Abstract:
Gap-filling carbon dioxide, water, energy, and methane fluxes in challenging ecosystems: Comparing between methods, drivers, and gap-lengths
Eddy covariance serves as one the most effective techniques for long-term monitoring of ecosystem fluxes, however long-term data integrations rely on complete timeseries, meaning that any gaps due to missing data must be reliably filled. To date, many gap-filling approaches have been proposed and extensively evaluated for mature and/or less actively managed ecosystems. Random forest regression (RFR) has been shown to be stable and perform better in these systems than alternative approaches, particularly when filling longer gaps. However, the performance of RFR gap filling remains less certain in more challenging ecosystems, e.g. actively managed agri-ecosystems and following recent land-use change due to management disturbances, ecosystems with relatively low fluxes due to low signal to noise ratios, or for trace gases other than carbon dioxide (e.g. methane). In an extension to earlier work on gap filling global carbon dioxide, water, and energy fluxes, we assess the RFR approach for gap filling methane fluxes globally. We then investigate a range of gap-filling methodologies for carbon dioxide, water, energy, and methane fluxes in challenging ecosystems, including European managed pastures, Southeast Asian converted peatlands, and North American drylands. Our findings indicate that RFR is a competent alternative to existing research standard gap-filling algorithms. The marginal distribution sampling (MDS) is still suggested for filling short (< 12 days) gaps in carbon dioxide fluxes, but RFR is better for filling longer (> 30 days) gaps in carbon dioxide fluxes and also for gap filling other fluxes (e.g. sensible heat, latent energy and methane). In addition, using RFR with globally available reanalysis environmental drivers is effective when measured drivers are unavailable. Crucially, RFR was able to reliably fill cumulative fluxes for gaps > 3 moths and, unlike other common approaches, key environment-flux responses were preserved in the gap-filled data.
Abstract.
2022
McIntire CD, Cunliffe AM, Boschetti F, Litvak ME (2022). Allometric Relationships for Predicting Aboveground Biomass, Sapwood, and Leaf Area of Two-Needle Piñon Pine ( Pinus edulis ) Amid Open-Grown Conditions in Central New Mexico. Forest Science, 68(2), 152-161.
Fawcett D, Cunliffe AM, Sitch S, O’Sullivan M, Anderson K, Brazier RE, Hill TC, Anthoni P, Arneth A, Arora VK, et al (2022). Assessing Model Predictions of Carbon Dynamics in Global Drylands.
Frontiers in Environmental Science,
10Abstract:
Assessing Model Predictions of Carbon Dynamics in Global Drylands
Drylands cover ca. 40% of the land surface and are hypothesised to play a major role in the global carbon cycle, controlling both long-term trends and interannual variation. These insights originate from land surface models (LSMs) that have not been extensively calibrated and evaluated for water-limited ecosystems. We need to learn more about dryland carbon dynamics, particularly as the transitory response and rapid turnover rates of semi-arid systems may limit their function as a carbon sink over multi-decadal scales. We quantified aboveground biomass carbon (AGC; inferred from SMOS L-band vegetation optical depth) and gross primary productivity (GPP; from PML-v2 inferred from MODIS observations) and tested their spatial and temporal correspondence with estimates from the TRENDY ensemble of LSMs. We found strong correspondence in GPP between LSMs and PML-v2 both in spatial patterns (Pearson’s r = 0.9 for TRENDY-mean) and in inter-annual variability, but not in trends. Conversely, for AGC we found lesser correspondence in space (Pearson’s r = 0.75 for TRENDY-mean, strong biases for individual models) and in the magnitude of inter-annual variability compared to satellite retrievals. These disagreements likely arise from limited representation of ecosystem responses to plant water availability, fire, and photodegradation that drive dryland carbon dynamics. We assessed inter-model agreement and drivers of long-term change in carbon stocks over centennial timescales. This analysis suggested that the simulated trend of increasing carbon stocks in drylands is in soils and primarily driven by increased productivity due to CO2 enrichment. However, there is limited empirical evidence of this 50-year sink in dryland soils. Our findings highlight important uncertainties in simulations of dryland ecosystems by current LSMs, suggesting a need for continued model refinements and for greater caution when interpreting LSM estimates with regards to current and future carbon dynamics in drylands and by extension the global carbon cycle.
Abstract.
Cunliffe AM, Anderson K, Boschetti F, Brazier RE, Graham HA, Myers-Smith IH, Astor T, Boer MM, Calvo LG, Clark PE, et al (2022). Global application of an unoccupied aerial vehicle photogrammetry protocol for predicting aboveground biomass in non-forest ecosystems.
REMOTE SENSING IN ECOLOGY AND CONSERVATION,
8(1), 57-71.
Author URL.
Gallois E, Myers-Smith IH, Daskalova GN, Kerby J, Thomas H, Cunliffe AM (2022). Litter decomposition is moderated by scale-dependent microenvironmental variation in tundra ecosystems.
Cunliffe AM, Boschetti F, Clement R, Sitch S, Anderson K, Duman T, Zhu S, Schlumpf M, Litvak ME, Brazier RE, et al (2022). Strong Correspondence in Evapotranspiration and Carbon Dioxide Fluxes Between Different Eddy Covariance Systems Enables Quantification of Landscape Heterogeneity in Dryland Fluxes. Journal of Geophysical Research Biogeosciences, 127(8).
2020
Cunliffe AM, J Assmann J, N Daskalova G, Kerby JT, Myers-Smith IH (2020). Aboveground biomass corresponds strongly with drone-derived canopy height but weakly with greenness (NDVI) in a shrub tundra landscape.
Environmental Research Letters,
15(12), 125004-125004.
Abstract:
Aboveground biomass corresponds strongly with drone-derived canopy height but weakly with greenness (NDVI) in a shrub tundra landscape
. Abstract
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. Arctic landscapes are changing rapidly in response to warming, but future predictions are hindered by difficulties in scaling ecological relationships from plots to biomes. Unmanned aerial systems (hereafter ‘drones’) are increasingly used to observe Arctic ecosystems over broader extents than can be measured using ground-based approaches and are facilitating the interpretation of coarse-grained remotely sensed data. However, more information is needed about how drone-acquired remote sensing observations correspond with ecosystem attributes such as aboveground biomass. Working across a willow shrub-dominated alluvial fan at a focal study site in the Canadian Arctic, we conducted peak growing season drone surveys with an RGB camera and a multispectral multi-camera array. We derived photogrammetric reconstructions of canopy height and normalised difference vegetation index (NDVI) maps along with in situ point-intercept measurements and aboveground vascular biomass harvests from 36, 0.25 m2 plots. We found high correspondence between canopy height measured using in situ point-intercept methods compared to drone-photogrammetry (concordance correlation coefficient = 0.808), although the photogrammetry heights were positively biased by 0.14 m relative to point-intercept heights. Canopy height was strongly and linearly related to aboveground biomass, with similar coefficients of determination for point-intercept (R
. 2 = 0.92) and drone-based methods (R
. 2 = 0.90). NDVI was positively related to aboveground biomass, phytomass and leaf biomass. However, NDVI only explained a small proportion of the variance in biomass (R
. 2 between 0.14 and 0.23 for logged total biomass) and we found moss cover influenced the NDVI-phytomass relationship. Vascular plant biomass is challenging to infer from drone-derived NDVI, particularly in ecosystems where bryophytes cover a large proportion of the land surface. Our findings suggest caution with broadly attributing change in fine-grained NDVI to biomass differences across biologically and topographically complex tundra landscapes. By comparing structural, spectral and on-the-ground ecological measurements, we can improve understanding of tundra vegetation change as inferred from remote sensing.
Abstract.
Cunliffe AM, McIntire CD, Boschetti F, Sauer KJ, Litvak M, Anderson K, Brazier RE (2020). Allometric Relationships for Predicting Aboveground Biomass and Sapwood Area of Oneseed Juniper (Juniperus monosperma) Trees.
Frontiers in Plant Science,
11Abstract:
Allometric Relationships for Predicting Aboveground Biomass and Sapwood Area of Oneseed Juniper (Juniperus monosperma) Trees
Across the semi-arid ecosystems of the southwestern USA, there has been widespread encroachment of woody shrubs and trees including Juniperus species into former grasslands. Quantifying vegetation biomass in such ecosystems is important because semi-arid ecosystems are thought to play an important role in the global land carbon (C) sink, and changes in plant biomass also have implications for primary consumers and potential bioenergy feedstock. Oneseed Juniper (J. monosperma) is common in desert grasslands and pinyon-juniper rangelands across the intermountain region of southwestern North America; however, there is limited information about the aboveground biomass (AGB) and sapwood area (SWA) for this species, causing uncertainties in estimates of C stock and transpiration fluxes. In this study, we report on canopy area, stem diameter, maximum height and biomass measurements from J. monosperma trees sampled from central New Mexico. Dry biomass ranged between 0.4 kg and 625 kg, and cross-sectional sapwood area was measured on n=200 stems using image analysis. We found a strong linear relationship between canopy area and AGB (r2 = 0.96), with a similar slope to that observed in other juniper species, suggesting that this readily measured attribute is well suited for upscaling studies. There was a 9% bias between different approaches to measuring canopy area, indicating care should be taken to account for these differences to avoid systematic biases. We found equivalent stem diameter (ESD) was a strong predictor of biomass, but that existing allometric models under-predicted biomass in larger trees. We found sapwood area could be predicted from individual stem diameter with a power relationship, and that tree-level SWA should be estimated by summing the SWA predictions from individual stems rather than ESD. Our improved allometric models for J. monosperma support more accurate and robust measurements of C storage and transpiration fluxes in Juniperus-dominated ecosystems.
Abstract.
Author URL.
Myers-Smith IH, Kerby JT, Phoenix GK, Bjerke JW, Epstein HE, Assmann JJ, John C, Andreu-Hayles L, Angers-Blondin S, Beck PSA, et al (2020). Complexity revealed in the greening of the Arctic.
Nature Climate Change,
10(2), 106-117.
Abstract:
Complexity revealed in the greening of the Arctic
As the Arctic warms, vegetation is responding, and satellite measures indicate widespread greening at high latitudes. This ‘greening of the Arctic’ is among the world’s most important large-scale ecological responses to global climate change. However, a consensus is emerging that the underlying causes and future dynamics of so-called Arctic greening and browning trends are more complex, variable and inherently scale-dependent than previously thought. Here we summarize the complexities of observing and interpreting high-latitude greening to identify priorities for future research. Incorporating satellite and proximal remote sensing with in-situ data, while accounting for uncertainties and scale issues, will advance the study of past, present and future Arctic vegetation change.
Abstract.
Assmann JJ, Myers-Smith IH, Kerby J, Cunliffe AM, Daskalova GN (2020). Drone data reveal heterogeneity in tundra greenness and phenology not captured by satellites.
Assmann JJ, Myers-Smith IH, Kerby JT, Cunliffe AM, Daskalova GN (2020). Drone data reveal heterogeneity in tundra greenness and phenology not captured by satellites.
ENVIRONMENTAL RESEARCH LETTERS,
15(12).
Author URL.
2019
Myers-Smith IH, Grabowski MM, Thomas HJD, Angers-Blondin S, Daskalova GN, Bjorkman AD, Cunliffe AM, Assmann JJ, Boyle JS, McLeod E, et al (2019). Eighteen years of ecological monitoring reveals multiple lines of evidence for tundra vegetation change.
Ecological Monographs,
89(2).
Abstract:
Eighteen years of ecological monitoring reveals multiple lines of evidence for tundra vegetation change
The Arctic tundra is warming rapidly, yet the exact mechanisms linking warming and observed ecological changes are often unclear. Understanding mechanisms of change requires long-term monitoring of multiple ecological parameters. Here, we present the findings of a collaboration between government scientists, local people, park rangers, and academic researchers that provide insights into changes in plant composition, phenology, and growth over 18 yr on Qikiqtaruk-Herschel Island, Canada. Qikiqtaruk is an important focal research site located at the latitudinal tall shrub line in the western Arctic. This unique ecological monitoring program indicates the following findings: (1) nine days per decade advance of spring phenology, (2) a doubling of average plant canopy height per decade, but no directional change in shrub radial growth, and (3) a doubling of shrub and graminoid abundance and a decrease by one-half in bare ground cover per decade. Ecological changes are concurrent with satellite-observed greening and, when integrated, suggest that indirect warming from increased growing season length and active layer depths, rather than warming summer air temperatures alone, could be important drivers of the observed tundra vegetation change. Our results highlight the vital role that long-term and multi-parameter ecological monitoring plays in both the detection and attribution of global change.
Abstract.
Cunliffe A, Tanski G, Radosavljevic B, Palmer W, Sachs T, Lantuit H, Kerby J, Myers-Smith I (2019). Rapid retreat of permafrost coastline observed with aerial drone photogrammetry.
Cryosphere,
13(5), 1513-1528.
Abstract:
Rapid retreat of permafrost coastline observed with aerial drone photogrammetry
Permafrost landscapes are changing around the Arctic in response to climate warming, with coastal erosion being one of the most prominent and hazardous features. Using drone platforms, satellite images, and historic aerial photographs, we observed the rapid retreat of a permafrost coastline on Qikiqtaruk - Herschel Island, Yukon Territory, in the Canadian Beaufort Sea. This coastline is adjacent to a gravel spit accommodating several culturally significant sites and is the logistical base for the Qikiqtaruk - Herschel Island Territorial Park operations. In this study we sought to (i) assess short-term coastal erosion dynamics over fine temporal resolution, (ii) evaluate short-term shoreline change in the context of long-term observations, and (iii) demonstrate the potential of low-cost lightweight unmanned aerial vehicles (drones) to inform coastline studies and management decisions. We resurveyed a 500m permafrost coastal reach at high temporal frequency (seven surveys over 40 d in 2017). Intra-seasonal shoreline changes were related to meteorological and oceanographic variables to understand controls on intra-seasonal erosion patterns. To put our short-term observations into historical context, we combined our analysis of shoreline positions in 2016 and 2017 with historical observations from 1952, 1970, 2000, and 2011. In just the summer of 2017, we observed coastal retreat of 14.5 m, more than 6 times faster than the long-term average rate of 2:20:1ma1 (1952-2017). Coastline retreat rates exceeded 1:00:1md1 over a single 4 d period. Over 40 d, we estimated removal of ca. 0.96m3 m1 d1. These findings highlight the episodic nature of shoreline change and the important role of storm events, which are poorly understood along permafrost coastlines. We found drone surveys combined with image-based modelling yield fine spatial resolution and accurately geolocated observations that are highly suitable to observe intra-seasonal erosion dynamics in rapidly changing Arctic landscapes.
Abstract.
Assmann JJ, Kerby JT, Cunliffe AM, Myers-Smith IH (2019). Vegetation monitoring using multispectral sensors — best practices and lessons learned from high latitudes.
Journal of Unmanned Vehicle Systems,
7(1), 54-75.
Abstract:
Vegetation monitoring using multispectral sensors — best practices and lessons learned from high latitudes
Rapid technological advances have dramatically increased affordability and accessibility of unmanned aerial vehicles (UAVs) and associated sensors. Compact multispectral drone sensors capture high-resolution imagery in visible and near-infrared parts of the electromagnetic spectrum, allowing for the calculation of vegetation indices, such as the normalised difference vegetation index (NDVI) for productivity estimates and vegetation classification. Despite the technological advances, challenges remain in capturing high-quality data, highlighting the need for standardized workflows. Here, we discuss challenges, technical aspects, and practical considerations of vegetation monitoring using multispectral drone sensors and propose a workflow based on remote sensing principles and our field experience in high-latitude environments, using the Parrot Sequoia (Pairs, France) sensor as an example. We focus on the key error sources associated with solar angle, weather conditions, geolocation, and radiometric calibration and estimate their relative contributions that can lead to uncertainty of more than ±10% in peak season NDVI estimates of our tundra field site. Our findings show that these errors can be accounted for by improved flight planning, metadata collection, ground control point deployment, use of reflectance targets, and quality control. With standardized best practice, multispectral sensors can provide meaningful spatial data that is reproducible and comparable across space and time.
Abstract.
2018
Karthikeyan, K, Vasu, D, Tiwary, P, Cunliffe AM, Chandran, P, Mariappan S, Singh S (2018). Comparison of methods for evaluating the suitability of Vertisols for Gossypium hirsutum (Bt cotton) in two contrasting agro-ecological regions.
Archives of Agronomy and Soil ScienceAbstract:
Comparison of methods for evaluating the suitability of Vertisols for Gossypium hirsutum (Bt cotton) in two contrasting agro-ecological regions
Cotton (Gossypium sp.) is a major crop grown under rainfed conditions in
Vertisols and associated soils in semi-arid tropical (SAT) regions of
Peninsular India. In recent years, cotton productivity has declined due to
various biophysical factors including pest and diseases, seasonal water
stress soil degradation and poor crop management practices. In this study,
we compare two methods for evaluating the suitability of Vertisols for
cotton in contrasting two agro-ecological regions viz. sub-humid moist
(SHM) region and semi-arid dry(SAD) were characterized. Twelve cotton
growing Vertisols (seven from SHM and five from SAD) were evaluated for
their suitability for cotton cultivation using soil quality index (SQI) and
modified Sys-FAO method. SQIs were calculated using the weighted
additive index from transformed scores of selected indicators by principal
component analysis. For Sys-FAO method both biophysical and soil characteristics
were considered for suitability evaluation. We found that the
soils of SHM region were moderately suitable for cotton cultivation with
soil moisture as the major limiting factor, whereas the soils of SAD region
are marginally suitable due to high exchangeable sodium percentage and
poor hydraulic conductivity. From this, it may be concluded that the
weighted SQI has better agreement with the cotton yield.
Abstract.
2017
Cunliffe A, Anderson K, Duffy JP, DeBell L (2017). A UK Civil Aviation Authority (CAA)-approved operations manual for safe deployment of lightweight drones in research. International Journal of Remote Sensing, 1-8.
Puttock A, Graham HA, Cunliffe AM, Elliott M, Brazier RE (2017). Eurasian beaver activity increases water storage, attenuates flow and mitigates diffuse pollution from intensively-managed grasslands. Science of the Total Environment, 576, 430-443.
Duffy J, Cunliffe A, DeBell L, Sandbrook C, Wich S, Shutler JD, Myers-Smith IH, Varela MR, Anderson K (2017). Location, location, location: Considerations when using lightweight drones in challenging environments. Remote Sensing in Ecology and Conservation
2016
Cunliffe AM, Puttock AK, Turnbull L, Wainwright J, Brazier RE (2016). Dryland, calcareous soils store (and lose) significant quantities of near-surface organic carbon. Journal of Geophysical Research: Earth Surface, 121(4), 684-702.
Cunliffe A, Brazier RE, Anderson K (2016). Ultra-fine grain landscape-scale quantification of dryland vegetation structure with drone-acquired structure-from-motion photogrammetry.
Remote Sensing of Environment,
183, 129-143.
Abstract:
Ultra-fine grain landscape-scale quantification of dryland vegetation structure with drone-acquired structure-from-motion photogrammetry
Covering 40% of the terrestrial surface, dryland ecosystems characteristically have distinct vegetation structures that are strongly linked to their function. Existing survey approaches cannot provide sufficiently fine-resolution data at landscape-level extents to quantify this structure appropriately. Using a small, unpiloted aerial system (UAS) to acquire aerial photographs and processing theses using structure-from-motion (SfM) photogrammetry, three-dimensional models were produced describing the vegetation structure of semi-arid ecosystems at seven sites across a grass–to shrub transition zone. This approach yielded ultra-fine (< 1 cm2) spatial resolution canopy height models over landscape-levels (10 ha), which resolved individual grass tussocks just a few cm3 in volume. Canopy height cumulative distributions for each site illustrated ecologically-significant differences in ecosystem structure. Strong coefficients of determination (r2 from 0.64 to 0.95) supported prediction of above-ground biomass from canopy volume. Canopy volumes, above-ground biomass and carbon stocks were shown to be sensitive to spatial changes in the structure of vegetation communities. The grain of data produced and sensitivity of this approach is invaluable to capture even subtle differences in the structure (and therefore function) of these heterogeneous ecosystems subject to rapid environmental change. The results demonstrate how products from inexpensive UAS coupled with SfM photogrammetry can produce ultra-fine grain biophysical data products, which have the potential to revolutionise scientific understanding of ecology in ecosystems with either spatially or temporally discontinuous canopy cover.
Abstract.
2015
Puttock A, Cunliffe AM, Anderson K, Brazier RE (2015). Aerial photography collected with a multirotor drone reveals impact of Eurasian beaver reintroduction on ecosystem structure.
Journal of Unmanned Vehicle Systems Author URL.
2013
Cunliffe AM, Baird AJ, Holden J (2013). Hydrological hotspots in blanket peatlands: Spatial variation in peat permeability around a natural soil pipe.
Water Resources Research,
49(9), 5342-5354.
Abstract:
Hydrological hotspots in blanket peatlands: Spatial variation in peat permeability around a natural soil pipe
Measurements were made of the hydraulic conductivity (K) of peat around a natural soil pipe in a blanket bog. This is the first investigation of decimeter-scale variability in both vertical K and horizontal K in blanket peats, which were found to be higher than indicated by previous research. This information suggests that it may be appropriate to reconsider (I) the spatial sampling strategies employed to investigate subsurface flow in blanket peatlands, and (II) how field data are used to parameterize flow models. Critically, there was spatial structure in the heterogeneity, with a wedge of high-K peat directly above the pipe forming a hydrological conduit between near-surface peat and the perennially flowing pipe. There was also significantly greater horizontal K parallel to the pipe's orientation compared with horizontal K perpendicular to the pipe. Determinations of the triaxial anisotropy of K, undertaken for the first time in peat soils, revealed substantial directional variations in K. The K around the pipe-peat interface was investigated; however, sample length dependency of K for peat samples precluded the investigation of a hypothesized low-K skin around the pipe. Key Points Blanket peat hydraulic conductivity (K) is very variable over decimetre-scales Horizontal K is spatially structured, with K higher parallel to a soil pipe Spatial sampling of blanket peats to investigate sub-surface flow needs review- ©2013. American Geophysical Union. All Rights Reserved.
Abstract.