Review of ‘plant available water’ aspects of water use efficiency under irrigated and dryland conditions

This review provides an overview of Water Research Commission (WRC)-funded research over the past 36 years. A total of 28 WRC reports have been consulted, 13 of these compiled by the University of the Free State, 4 by the University of Fort Hare, and the remainder mainly by the ARC-Institute for Soil Climate and Water. This work has resulted in extensive capacity building in this field – numerous technical assistants and 58 researchers have been involved, of which 23 are still active in research.The focus on the water flow processes in the soil-plant-atmosphere continuum (SPAC), with particular emphasis on processes in the soil, has greatly enhanced understanding of the system, thereby enabling the formulation of a quantitative model relating the water supply from a layered soil profile to water demand; the formulation of logical quantitative definitions for crop-ecotope specific upper and lower limits of available water; the identification of the harmful rootzone development effects of compacted layers in fine sandy soils caused by cultivation, and amelioration procedures to prevent these effects; and management strategies to combat excessive water losses by deep drainage. The explanation of the way in which SPAC is expressed in the landscape in the form of the ecotope has been beneficial with regard to the extrapolation of studies on particular SPACs to the large number of ecotopes where detailed studies have not been possible. Valuable results are reported regarding rainfall and runoff management strategies. Longer fallow periods and deficit irrigation on certain crop ecotopes improved rainfall use efficiency. On semi-arid ecotopes with high-drought-risk clay and duplex soils and high runoff losses, in-field rainwater harvesting (IRWH), designed specifically for subsistence farmers, resulted in maize and sunflower yield increases of between 30% and 50% compared to yields obtained with conventional tillage. An indication of the level of understanding of the relevant processes that has been achieved is demonstrated by their quantitative description in mathematical and empirical models: BEWAB for irrigation, SWAMP mainly for dryland cropping, and CYP-SA for IRWH. Five important related research and development needs are identified. The WRC has played, and continues to play, an important role in commissioning and funding research on water utilisation in agriculture and has clearly made an excellent contribution to the progress made in addressing the needs and requirements of subsistence, emergent and dryland farmers in South Africa.Keywords: BEWAB, SWAMP, CYP-SA, in-field rainwater harvesting, dryland ecotope, irrigatio

Predicting microscale shifts in the distribution of the butterfly Plebejus argus at the northern edge of its range

This is the final version of the article. Available from Wiley via the DOI in this recordSpecies are often observed to occur in restricted patches of particularly warm microclimate at their high latitude/altitude geographic range margin. In these areas, global warming is expected to cause small-scale expansion of the occupied area, but most previous studies of range expansion have used very coarse scale data. Using high resolution microclimate models together with detailed field surveys, we tested whether the butterfly Plebejus argus, occurring on limestone grassland in north Wales, was responding as might be expected due to climate change in the last 30-40 yr. The abundance of adult Plebejus argus at 100 m resolution in 2011 was strongly affected by elevation and near-ground temperatures in May. A statistical model including microclimate, fitted to 2011 data, was successful (67% correct) at hindcasting the occurrence of Plebejus argus in 1983 when the average May air temperature was 1.4°C cooler. However, the model was less accurate at hindcasting occurrences in 1972 (50% correct). Given the distribution of micro-sites in this landscape, we predict that further warming of approximately 1°C would make the majority of sites highly microclimatically suitable for this species. There are a growing number of long-term studies of range change, and investigations into the mechanisms driving them, but still surprisingly few that explicitly make and test predictions with independent data. Our tests are a valuable example of how accurate predictions of distribution change can be, but also of the inevitable uncertainties. Improved understanding of how well models predict will be very important to plan robust climate change adaptation measures.JAH, JJB, RJW and CDT were supported by NERC grant NE/G006377/1 (). Fieldwork by JAH and NL was supported by a pump-priming grant from the Dept of Biology, Univ. of York

Unmanned aerial vehicle (UAV) derived structure-from-motion photogrammetry point clouds for oil palm (Elaeis guineensis) canopy segmentation and height estimation

This is the author accepted manuscript. The final version is available from Taylor & Francis via the DOI in this record.The vast size of oil palm (Elaeis guineensis) plantations has led to lightweight unmanned aerial vehicles (UAVs) being identified as cost effective tools to generate inventories for improved plantation management, with proximal aerial data capable of resolving single palm canopies at potentially, centimetric resolution. If acquired with sufficient overlap, aerial data from UAVs can be processed within structure-from-motion (SfM) photogrammetry workflows to yield volumetric point cloud representations of the scene. Point cloud-derived structural information on individual palms can benefit not only plantation management but is also of great environmental research interest, given the potential to deliver spatially contiguous quantifications of aboveground biomass, from which carbon can be accounted. Using lightweight UAVs we captured data over plantation plots of varying ages (2, 7 and 10 years) at peat soil sites in Sarawak, Malaysia, and we explored the impact of changing spatial resolution and image overlap on spatially variable uncertainties in SfM derived point clouds for the ten year old plot. Point cloud precisions were found to be in the decimetre range (mean of 26.7 31 cm) for a 10 year old plantation plot surveyed at 100 m flight altitude and >75% image overlap. Derived canopy height models were used and evaluated for automated palm identification using local height maxima. Metrics such as maximum canopy height and stem height, derived from segmented single palm point clouds were tested relative to ground validation data. Local maximum identification performed best for palms which were taller than surrounding undergrowth but whose fronds did not overlap significantly (98.2% mapping accuracy for 7 year old plot of 776 palms). Stem heights could be predicted from point cloud derived metrics with root-mean-square errors (RMSEs) of 0.27 m (R2= 0.63) for 7 year old and 0.45 m (R2=0.69) for 10 year old palms. It was also found that an acquisition designed to yield the minimal required overlap between images (60%) performed almost as well as higher overlap acquisitions (>75%) for palm identification and basic height metrics which is promising for operational implementations seeking to maximise spatial coverage and minimise processing costs. We conclude that UAV-based SfM can provide reliable data not only for oil palm inventory generation but allows the retrieval of basic structural parameters which may enable per-palm above-ground biomass estimations.European CommissionMarie Skłodowska-Curi

Effective Feedback to Improve Primary Care Prescribing Safety (EFIPPS) a pragmatic three-arm cluster randomised trial:designing the intervention (ClinicalTrials.gov registration NCT01602705)

Peer reviewedPublisher PD

Worldwide variations in artificial skyglow

Open access journalDespite constituting a widespread and significant environmental change, understanding of artificial nighttime skyglow is extremely limited. Until now, published monitoring studies have been local or regional in scope, and typically of short duration. In this first major international compilation of monitoring data we answer several key questions about skyglow properties. Skyglow is observed to vary over four orders of magnitude, a range hundreds of times larger than was the case before artificial light. Nearly all of the study sites were polluted by artificial light. A non-linear relationship is observed between the sky brightness on clear and overcast nights, with a change in behavior near the rural to urban landuse transition. Overcast skies ranged from a third darker to almost 18 times brighter than clear. Clear sky radiances estimated by the World Atlas of Artificial Night Sky Brightness were found to be overestimated by ~25%; our dataset will play an important role in the calibration and ground truthing of future skyglow models. Most of the brightly lit sites darkened as the night progressed, typically by ~5% per hour. The great variation in skyglow radiance observed from site-to-site and with changing meteorological conditions underlines the need for a long-term international monitoring program.MILIEU (FU Berlin)Federal Ministry of Education and Research, GermanyEU COST Action ES1204 (Loss of the Night Network)European Research Council (ERC) under the EU's Seventh Framework Program (FP7/2007-2013)panish Network for Light Pollution StudiesNational Aeronautics and Space Administration (Goddard Space Flight Center)Ohio State UniversityUniversity of IowaThe Adam Mickiewicz Universit

Fine-scale climate change: modelling spatial variation in biologically meaningful rates of warming

This is the author accepted manuscript. The final version is available from Wiley via the DOI in this record.The existence of fine-grain climate heterogeneity has prompted suggestions that species may be able to survive future climate change in pockets of suitable microclimate, termed 'microrefugia'. However, evidence for microrefugia is hindered by lack of understanding of how rates of warming vary across a landscape. Here we present a model that is applied to provide fine-grained, multi-decadal estimates of temperature change based on the underlying physical processes that influence microclimate. Weather station and remotely-derived environmental data were used to construct physical variables that capture the effects of terrain, sea-surface temperatures, altitude and surface albedo on local temperatures, which were then calibrated statistically to derive gridded estimates of temperature. We apply the model to the Lizard Peninsula, United Kingdom to provide accurate (mean error = 1.21°C; RMS error = 1.63°C) hourly estimates of temperature at a resolution of 100 m for the period 1977 to 2014. We show that rates of warming vary across a landscape primarily due to long-term trends in weather conditions. Total warming varied from 0.87 to 1.16°C, with the slowest rates of warming evident on north-east-facing slopes. This variation contributed to substantial spatial heterogeneity in trends in bioclimatic variables: for example, the change in the length of the frost-free season varied from +11 to -54 days and the increase annual growing degree-days from 51 to 267 °C days. Spatial variation in warming was caused primarily by a decrease in daytime cloud cover with a resulting increase in received solar radiation, and secondarily by a decrease in the strength of westerly winds, which has amplified the effects on temperature of solar radiation on west-facing slopes. We emphasise the importance of multi-decadal trends in weather conditions in determining spatial variation in rates of warming, suggesting that locations experiencing least warming may not remain consistent under future climate change. This article is protected by copyright. All rights reserved.We thank Michael Ashcroft, Richard Gunton and an anonymous referee for helpful comments on the manuscript and Ray Lawman and Rachel Holder for permission to deploy data loggers on land owned by or managed by the National Trust and Natural England. This research was partly funded by the European Social Fund (09099NCO5), NERC ((NE/L00268X/1) and by Natural England

Recent advances in the remote sensing of insects

This is the author accepted manuscript. The final version is available from Wiley via the DOI in this recordRemote sensing has revolutionised many aspects of ecological research, enabling spatiotemporal data to be collected in an efficient and highly automated manner. The last two decades have seen phenomenal growth in capabilities for high-resolution remote sensing that increasingly offers opportunities to study small, but ecologically important organisms, such as insects. Here we review current applications for using remote sensing within entomological research, highlighting the emerging opportunities that now arise through advances in spatial, temporal and spectral resolution. Remote sensing can be used to map environmental variables, such as habitat, microclimate and light pollution, capturing data on topography, vegetation structure and composition, and luminosity at spatial scales appropriate to insects. Such data can also be used to detect insects indirectly from the influences that they have on the environment, such as feeding damage or nest structures, whilst opportunities for directly detecting insects are also increasingly available. Entomological radar and light detection and ranging (LiDAR), for example, are transforming our understanding of aerial insect abundance and movement ecology, whilst ultra-high spatial resolution drone imagery presents tantalising new opportunities for direct observation. Remote sensing is rapidly developing into a powerful toolkit for entomologists, that we envisage will soon become an integral part of insect science.Spalding Associates (Environmental) Lt

Characterising inter-annual variation in the spatial pattern of thermal microclimate in a UK upland using a combined empirical-physical model

Temperature exerts a fundamental control on ecosystem function, species’ distributions and ecological processes across a range of spatial scales. At the landscape scale, near-surface air temperature may vary spatially over short distances, particularly inmountainous regions. Both the magnitude and spatial pattern of surface temperature may vary on diurnal, seasonal and inter-annual timescales. Furthermore, temperatures measured at the surface of vegetation, influenced by the energy balance of the surface, can differ considerably from air temperature. In order to explore spatial patterns in temperature across the MoorHouse sector of the MoorHouse—Upper Teesdale National Nature Reserve (NNR), Northern Pennines, UK,we derived anempirical linear regression model to predict airtemperature at 1 mheight as a function of landscape metrics derived from a digital elevation model (DTM), and coupled this to an existing physical land-surface model (JULES) in order to predict and map thermal climate at the vegetation surface across the study area. Spatial patterns in temperature associated with altitudinal lapse rate, katabatic flow and a local fohn effect were incorporated into the regression model. JULES was driven using spatially distributed air temperatures from the empirical model, along with distributed solar and long-wave radiation flux estimates adjusted for surface slope and aspect, and sky-view in order to model the surface energy balance and predict thermal climate at the vegetation surface (skin temperature). Aggregate properties such as annual degree days above 5 degC (GDD5), number of ‘‘frost days’’ when the temperature fell below 0 degC (FD0) and number of ‘‘severe frost days’’ when the minimum temperature fell below 5degC (FD5) were mapped across the reserve for the years 1994–2006. Spatial mapping of surface temperature revealed differences in the 12-year average spatial pattern between GDD5, FD0 and FD5, and differences in the spatial patterns of FD0 and FD5 between different years, depending on the relative strength of lapse rates, temperature inversions and the fohn effect. The location of ‘‘warm’’ and ‘‘cool’’ microclimates within the study area varies depending on the dominant atmospheric conditions in a given year and on the thermal property of interest. While GDD5 tended to decrease and FD0 increased with increasing altitude in all years, following the gradients in average temperature, the magnitude of these relationships varied considerably between years. FD5 increased in some years and decreased in others, due to the influence of temperature inversions during extreme cold temperature events. We conclude, that in order to predict the landscapescale response of species and communities to climatic change in upland areas accurately, it will be necessary to take into account changes in the frequency and magnitude of different synoptic atmospheric conditions under future climate scenarios