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Tamalia (Hemiptera: Aphididae: Tamaliinae), a Nearctic aphid genus, is associated with galls on woody plants in the family Ericaceae (Arctostaphylos spp., Arbutus arizonica, and Comarostaphylis diversifolia). Tamalia cruzensis Miller and Pike, n. sp., Tamalia glaucensis Miller and Pike, n. sp., and Tamalia moranae Miller and Pike, n. sp. are described and illustrated. Two of these, T. cruzensis and T. moranae, represent host plant records for Tamalia on genera other than Arctostaphylos spp. Character measurements, comparisons, and descriptions; DNA cytochrome oxidase subunit 1 sequences; geographic distributions; seasonal occurrence; biology; and host plant associations are provided, along with diagnoses and a key to the known species based on the gall-inhabiting apterous adult stage.

Unidad de excelencia María de Maeztu CEX2019-000940-M The paper presents insights from carrying out a pan-EU sustainability assessment using Farm Accountancy Data Network (FADN) data (the old wine) with societal metabolism accounting (SMA) processes (the new bottles). The SMA was deployed as part of a transdisciplinary study with EU policy stakeholders of how EU policy may need to change to deliver sustainability commitments, particularly to the UN Sustainable Development Goals. The paper outlines the concepts underlying SMA and its specific implementation using the FADN data. A key focus was on the interactions between crop and livestock systems and how this determines imported feedstuffs requirements, with environmental and other footprints beyond the EU. Examples of agricultural production systems performance are presented in terms of financial/efficiency, resource use (particularly the water footprint) and quantifies potential pressures on the environment. Benefits and limitations of the FADN dataset and the SMA outputs are discussed, highlighting the challenges of linking quantified pressures with environmental impacts. The paper concludes that the complexity of agriculture's interactions with economy and society means there is great need for conceptual frameworks, such as SMA, that can take multiple, non-equivalent, perspectives and that can be deployed with policy stakeholders despite generating uncomfortable knowledge.

This paper uses large-scale micro data to identify key factors affecting the decision to adopt renewable energy generation (wind, solar and biomass) on farms in Scotland. We construct an integrated dataset that includes the compulsory agricultural census and farm structural survey that cover almost all farms in Scotland. In addition to farm owner demographics and farm business structures, we also assess the effect of diversification activities such as tourism and forestry, as well as the spatial, biophysical and geophysical attributes of the farms on the adoption decision. We find that diversified farms are more likely to adopt renewable energy, especially solar and biomass energy. Farms are also more likely to adopt renewable energy if they have high local demand for energy, or suitable conditions for renewable energy production. We find that biophysical factors such as the agricultural potential of farm land are important in adoption decisions. We identify adopter profiles for each type of renewable energy, and map the geographic location of potential adopters. We argue that renewable energy policy should be more integrated with farm diversification policy and farm support schemes. It should also be tailored for each type of renewable energy, for the potential adopter profiles of wind, solar and biomass energy all differ in farm characteristics and geographic distribution.

The paper presents the results of a study that developed and applied social metabolism methods to assess the sustainability of a regional economy, particularly the dynamics related to changes in the production and use of energy. The first objective of the study was to assess the feasibility of using existing secondary data sources as a basis for sub-nation state and regional analysis (with the regions in this case differentiating the area based on rurality). The second was to structure the outputs of the analysis in ways that provided comprehensive yet succinct and interpretable assessments of the balance of flows of material, energy and money that underpin the economy, with the intention that ultimately these assessments would be used to inform policymaking. The paper provides an introduction to the key concepts used within social metabolism analysis particularly the use of emergy (a measure of the cumulative environmental support provided to a social-ecological system). This is a unifying metric into which the myriad flows within an economy can be translated and combined in meaningful ways. It does so by, preserving information on both the quantity and quality of flows and so avoiding the need for arbitrary weightings. The paper presents a range of options for the use of emergy-based metrics that could be used to inform policy making. Comparisons for the years 2001 and 2010 are made at country level for Scotland and for three degrees of rurality. The analysis highlights how decisions on the share of the offshore energy sector attributed to Scotland and on the share of services (particularly those imported from beyond U.K.) have profound effects on the sustainability trajectory of the economy and the conclusions that might be drawn for policy. The paper concludes that the methods have the potential to add value to existing administrative datasets, and provide new perspectives that may be of value to policy making, but acknowledges that challenges remain in translating this potential into tangible use within policymaking.

This paper develops an empirical agent-based model to assess the impacts of Brexit on Scottish cattle farms. We first identify several trends and processes among Scottish cattle farms that were ongoing before Brexit: the lack of succession, the rise of leisure farming, the trend to diversify and industrialise, and, finally, the phenomenon of the "disappearing middle", characterised by the decline of medium-sized farms and the polarization of farm sizes. We then study the potential impact of Brexit amid the local context and those ongoing social processes. We find that the impact of Brexit is indeed subject to pre-Brexit conditions. For example, whether industrialization is present locally can significantly alter the impact of Brexit. The impact of Brexit also varies by location: we find a clear divide between constituencies in the north (highland and islands), the middle (the central belt) and the south. Finally, we argue that policy analysis of Brexit should consider the heterogeneous social context and the complex social processes under which Brexit occurs. Rather than fitting the world into simple system models and ignoring the evidence when it does not fit, we need to develop policy analysis frameworks that can incorporate real world complexities, so that we can assess the impacts of major events and policy changes in a more meaningful way.

Area-based targets for afforestation are a frequent and prominent component of policy discourses on forestry, land use and climate change emissions abatement. Such targets imply an expected contribution of afforestation to the net reduction of greenhouse gas emissions, yet the nature of afforestation undertaken and its geographical distribution means that there is considerable uncertainty over the eventual emission reductions outcomes. This uncertainty is reduced if the net carbon balance is calculated for all potential afforestation sites, considering climate, soil characteristics and the possible types of afforestation (species and management regimes). To quantify the range of possible emissions outcomes for area-based afforestation targets, a new spatial analysis method was implemented. This improved the integration of spatial data on antecedent land use with mapped outputs from forest models defining the suitability and productivity of eleven forestry management alternatives. This above ground carbon data was then integrated with outputs from the ECOSSE (Estimation of Carbon in Organic Soils – Sequestration and Emissions) model which simulates the soil carbon dynamics. The maps and other model output visualisations combining above and below ground carbon highlight where net carbon surpluses and deficits are likely to occur, how long they persist after afforestation and their relationships with antecedent land use, soils, weather conditions and afforestation management strategies. Using more productive land classes delivers more net sequestration per hectare and could mean greater carbon storage than anticipated by emissions reduction plans. Extensive establishment of lower yielding trees on low-quality ground, with organo-mineral soils could, though, result in net emissions that persist for decades. From the spatial analysis, the range of possible outcomes for any target area of planting is substantial, meaning that outcomes are highly sensitive to policy and implementation decisions on the mix of forestry systems preferred and to spatial targeting or exclusions (both at regional and local scales). The paper highlights the importance of retaining the existing presumption against planting of deep peat areas, but also that additional incentives or constraints may be needed to achieve the aggregate rates of emission mitigation implied by policy commitments. Supplementary carbon storage tonnage targets for new forestry would introduce a floor for carbon sequestration outcomes, but would still allow for flexibility in achieving an appropriate balance in the trade-offs between carbon sequestration and the many other objectives that new woodlands are expected to deliver.

Closure of small schools has been a contentious policy issue, addressed most recently in the Schools Consultation (Scotland) Act 2010. Local authorities are currently delivering public service under great financial pressure and, given the high per capita costs of running small schools, have often sought to close them. One of the arguments for retaining small schools is the purported contribution that they make in maintaining rural community vibrancy. However, the evidence base for retaining small schools as ‘the heart of the rural community’ is largely untested, and such evidence as there is suggests that school closures have a modest effect on community vibrancy. School catchment studies show a long-term pattern of adjustment to demographic changes but this process may be curtailed by government policy in Scotland. A solid employment base and affordable housing are deemed by many to be more important factors in rural socio-economic wellbeing than the presence or absence of a primary school.

Summary Assessment of soil organic matter content using laboratory analysis can be costly and time consuming, so limiting how often land managers assess this important property. This work demonstrates an ability to estimate topsoil organic matter content from field observations alone and provides a method by which rapid and cost-effective assessments of soil organic matter status may be made. Models using environmental factors from the National Soil Inventory of Scotland (NSIS) dataset as inputs to a neural network model were used to predict loss on ignition (LOI). Two models, one for all soils and one for soils with small organic matter contents (LOI < 20%), were developed. It was found that the model developed for all soils produced reasonable predictive results across the entire LOI range (R2 = 0.877), although it was not as effective at predicting small LOI values (R2 = 0.354) as the small organic matter content model (R2 = 0.674). Both models were tested with imagery and data from samples outwith the NSIS dataset to validate the approach. Predictive results were less accurate than when using NSIS data. A discussion of possible improvements to make the model useful for field observations of soils is given.

The mechanical, electrical and electronic design and construction of the ZEUS central tracking detector are described, together with the chamber monitoring and environmental control. This cylindrical drift chamber is designed for track reconstruction, electron identification and fast event triggering in a high beam-crossing rate, high magnetic field application.

International audience; In estimating responses of crops to future climate realisations, it is necessary to understand and differentiate sources of uncertainty. This paper considers the specific aspect of input weather data quality from a Regional Climate Model (RCM) leading to differences in estimates made by three crop models. The availability of hindcast RCM estimates enables comparison of crop model outputs derived from observed and modelled weather data. Errors in estimating the past climate implies biases in future projections, and thus affect modelled crop responses. We investigate the complexities in using climate model projections representing different spatial scales within climate change impacts and adaptation studies. This is illustrated by simulating spring barley with three crop models run using site-specific observed (12 UK sites), original (50 x 50 km) and bias corrected downscaled (site-specific) hindcast (1960-1990) weather data from the HadRM3 RCM. Though the bias correction downscaling method improved the match between observed and hindcast data, this did not always translate into better matching of crop model estimates. At four sites the original HadRM3 data produced near identical mean simulated yield values as from the observed weather data, despite evaluated (observed-hindcast) differences. This is likely due to compensating errors in the input weather data and non-linearity in the crop models processes, making interpretation of results problematic. Understanding how biases in climate data manifest themselves in individual crop models gives greater confidence in the utility of the estimates produced using downscaled future climate projections and crop model ensembles. The results have implications on how future projections of climate change impacts are interpreted. Fundamentally, considerable care is required in determining the impact weather data sources have in climate change impact and adaptation studies, whether from individual models or ensembles. Crown Copyright (C) 2016 Published by Elsevier B.V. All rights reserved.