Quantifying the impact of land-use change on European farmland bird populations

The EU has adopted the European Farmland Bird Index (EFBI) as a Structural and Sustainable Development Indicator and a proxy for wider biodiversity health on farmland. Changes in the EFBI over coming years are likely to reflect how well agri-environment schemes (AES), funded under Pillar 2 (Axis 2) of the Common Agricultural Policy, have been able to offset the detrimental impacts of past agricultural changes and deliver appropriate hazard prevention or risk mitigation strategies alongside current and future agricultural change. The delivery of a stable or positive trend in the EFBI will depend on the provision of sufficient funding to appropriately designed and implemented AES. We present a trait-based framework which can be used to quantify the detrimental impact of land-use change on farmland bird populations across Europe. We use the framework to show that changes in resource availability within the cropped area of agricultural landscapes have been the key driver of current declines in farmland bird populations. We assess the relative contribution of each Member State to the level of the EFBI and explore the relationship between risk contribution and Axis 2 funding allocation. Our results suggest that agricultural changes in each Member State do not have an equal impact on the EFBI, with land-use and management change in Spain having a particularly large influence on its level, and that funding is poorly targeted with respect to biodiversity conservation needs. We also use the framework to predict the EFBI in 2020 for a number of land-use change scenarios. This approach can be used to guide both the development and implementation of targeted AES and the objective distribution of Pillar 2 funds between and within Member States. We hope that this will contribute to the cost-effective and efficient delivery of Rural Development strategy and biodiversity conservation targets.

Land-cover classification from airborne LIDAR data fused with aerial optical images

Airborne LIght Detection And Ranging (LIDAR) provides accurate height information for objects on the earth, which makes LIDAR become more and more popular in terrain and land surveying. In particular, LIDAR data offer vital and significant features for land-cover classification which is an important task in many application domains. In this paper, an unsupervised approach based on an improved fuzzy Markov random field (FMRF) model is developed, by which the LIDAR data, its co-registered images acquired by optical sensors, i.e. aerial color image and near infrared image, and other derived features are fused effectively to improve the ability of the LIDAR system for the accurate land-cover classification. In the proposed FMRF model-based approach, the spatial contextual information is applied by modeling the image as a Markov random field (MRF), with which the fuzzy logic is introduced simultaneously to reduce the errors caused by the hard classification. Moreover, a Lagrange-Multiplier (LM) algorithm is employed to calculate a maximum A posteriori (MAP) estimate for the classification. The experimental results have proved that fusing the height data and optical images is particularly suited for the land-cover classification. The proposed approach works very well for the classification from airborne LIDAR data fused with its coregistered optical images and the average accuracy is improved to 88.9%.

Idealized model for changes in equilibrium temperature, mixed layer depth, and boundary layer cloud over land in a doubled CO2 climate

An idealized equilibrium model for the undisturbed partly cloudy boundary layer (BL) is used as a framework to explore the coupling of the energy, water, and carbon cycles over land in midlatitudes and show the sensitivity to the clear‐sky shortwave flux, the midtropospheric temperature, moisture, CO2, and subsidence. The changes in the surface fluxes, the BL equilibrium, and cloud cover are shown for a warmer, doubled CO2 climate. Reduced stomatal conductance in a simple vegetation model amplifies the background 2 K ocean temperature rise to an (unrealistically large) 6 K increase in near‐surface temperature over land, with a corresponding drop of near‐surface relative humidity of about 19%, and a rise of cloud base of about 70 hPa. Cloud changes depend strongly on changes of mean subsidence; but evaporative fraction (EF) decreases. EF is almost uniquely related to mixed layer (ML) depth, independent of background forcing climate. This suggests that it might be possible to infer EF for heterogeneous landscapes from ML depth. The asymmetry of increased evaporation over the oceans and reduced transpiration over land increases in a warmer doubled CO2 climate.

Exporting construction professional services in a global service economy

Globalisation has prompted increasing numbers of construction profes-sional services (CPS) firms to internationalise and export their services. The driver has been twofold; firstly to increase turnover/profits and sec-ondly, to minimise the risk of a reliance on working in a single domestic market which has a fluctuating demand. Secondly, where firms have out-grown their domestic market, and in order to expand, they must export overseas. There has been little research into the way CPS firms operate overseas, yet construction represents approximately 10% of global GDP; this means that understanding CPS firms is important. This paper investigates how CPS firms internationalise and the drivers that impact their decisions and operations overseas. A survey was undertaken and interviews conducted that showed CPS firms are project driven, in-vesting heavily in the process of seeking work/bidding for projects, and are very focused on delivering projects with minimum risk. Increasing foreign ownership, changing procurement approaches and more consolidation of CPS firms in the global marketplace present a changing business land-scape. The research develops a framework of tangible and intangible factors, such as competencies, business organisation culture, leadership and reputation in order to better understand how CPS firms export their ser-vices. Whilst all CPS firms share the same framework of factors, the re-sulting synergies are different not only for each firm but also for each pro-ject. The knowledge-intensive and project-based nature of CPS firms presents a challenge in understanding the way they operate in the global service economy.

Innovation in facilities management: from trajectories to ownership

Purpose – Innovation in facilities management (FM) is a complex process as FM is a diverse discipline. This paper aims to use innovation trajectories to explore this complex process through the introduction of a technology innovation in two FM services of security and workspace management. It also aims to consider the discourse of individuals within their trajectory to understand their positions toward the innovation. Design/methodology/approach – A two-year case study was conducted and it was based in an in-house FM department that was part of a financial institution. The specific methods used for the paper were semi-structured interviews with key participants of the project. Critical discourse analysis was used to examine the data. Findings – Individuals who were involved in introducing the technology to the FM department were both internal and external to FM as innovation in FM does not happen in isolation to the organisation. Innovation trajectories were often intertwined or occurred simultaneously during the process of a project which sometimes resulted in conflict. Tensions within the discourse of ownership of the project were particularly apparent as this discourse had a power dimension in driving the project through to implementation. Research limitations/implications – The research is limited by being a single case study so it is not possible to generalise findings but the findings may have resonances with other organisations. Originality/value – The paper presents an original idea about how to understand innovation processes in FM services.

Modelling the likely impact of healthy eating guidelines on agricultural production and land use in England and Wales

Quadratic programming techniques were applied to household food consumption data in England and Wales to estimate likely changes in diet under healthy eating guidelines, and the consequences this would have on agriculture and land use in England and Wales. The first step entailed imposing nutrient restrictions on food consumption following dietary recommendations suggested by the UK Department of Health. The resulting diet was used, in a second step as a proxy for demand in agricultural commodities, to test the impact of such a scenario on food production and land use in England and Wales and the impacts of this on agricultural landscapes. Results of the diet optimisation indicated a large drop in consumption of foods rich in saturated fats and sugar, essentially cheese and sugar-based products, along with lesser cuts of fat and meat products. Conversely, consumption of fruit and vegetables, cereals, and flour would increase to meet dietary fibre recommendations. Such a shift in demand would dramatically affect production patterns: the financial net margin of England and Wales agriculture would rise, due to increased production of high market value and high economic margin crops. Some regions would, however, be negatively affected, mostly those dependent on beef cattle and sheep production that could not benefit from an increased demand for cereals and horticultural crops. The effects of these changes would also be felt in upstream industries, such as animal feed suppliers. While arable dominated landscapes would be little affected, pastoral landscapes would suffer through loss of grazing management and, possibly, land abandonment, especially in upland areas.

Predicting microbial pollution concentrations in UK rivers in response to land use change

The Water Framework Directive has caused a paradigm shift towards the integrated management of recreational water quality through the development of drainage basin-wide programmes of measures. This has increased the need for a cost-effective diagnostic tool capable of accurately predicting riverine faecal indicator organism (FIO) concentrations. This paper outlines the application of models developed to fulfil this need, which represent the first transferrable generic FIO models to be developed for the UK to incorporate direct measures of key FIO sources (namely human and livestock population data) as predictor variables. We apply a recently developed transfer methodology, which enables the quantification of geometric mean presumptive faecal coliforms and presumptive intestinal enterococci concentrations for base- and high-flow during the summer bathing season in unmonitored UK watercourses, to predict FIO concentrations in the Humber river basin district. Because the FIO models incorporate explanatory variables which allow the effects of policy measures which influence livestock stocking rates to be assessed, we carry out empirical analysis of the differential effects of seven land use management and policy instruments (fiscal constraint, production constraint, cost intervention, area intervention, demand-side constraint, input constraint, and micro-level land use management) all of which can be used to reduce riverine FIO concentrations. This research provides insights into FIO source apportionment, explores a selection of pollution remediation strategies and the spatial differentiation of land use policies which could be implemented to deliver river quality improvements. All of the policy tools we model reduce FIO concentrations in rivers but our research suggests that the installation of streamside fencing in intensive milk producing areas may be the single most effective land management strategy to reduce riverine microbial pollution.