Search

This study determined the effect of two tree planting methods (woodland and a silvopastoral agroforestry system) on the soil bulk density and organic carbon content of a grassland site in lowland England. Soil organic carbon was measured in pasture, silvopastoral tree, and woodland treatments at six depths representative of 0–150 cm. Fourteen years after tree planting, the organic carbon content in the surface soil layer (0–10 cm) was greatest in the pasture (6.0 g 100 g − 1 ) and least in the woodland (4.6 g 100 g − 1 ); the value (5.3 g 100 g − 1 ) below the silvopastoral trees was intermediate. In the 10–20 cm layer, the organic carbon content in the woodland was 13% lower than the pasture. No treatment effects on soil carbon were detected below 20 cm. Possible reasons for the decline in surface soil carbon include a decline in grass cover and reduced soil water content. Measurements of above ground carbon storage by the trees indicated that tree planting increased overall carbon storage, with the silvopastoral system predicted to achieve a higher level of carbon storage than equivalent areas of separate woodland and pasture. A power analysis indicates that a prohibitively large number of replicates is needed to ensure a lower than 20% risk of falsely concluding no treatment differences at individual depth increments below 10 cm and cumulative depths extending below 40 cm. [ABSTRACT FROM AUTHOR]

Abstract: The drive for sustainable energy production is leading to increased deployment of land based renewables. Although there is public support, in principle, for renewable energy at a national level, major resistance to renewable energy technologies often occurs at a local level. Within this context, it can be useful to consider the “energyscape” which we initially define as the complex spatial and temporal combination of the supply, demand and infrastructure for energy within a landscape. By starting with a consideration of the energyscape, we can then consider the positive and negative interactions with other ecosystem services within a particular landscape. This requires a multi-disciplinary systems-approach that uses existing knowledge of landscapes, energy options, and the different perspectives of stakeholders. The approach is examined in relation to pilot case-study comprising a 155 km2 catchment in Bedfordshire, England. [Copyright &y& Elsevier]

Silvoarable agroforestry, the integration of trees and arable crops on the same area, has the potential to offer production, ecological, and societal benefits. However, the uptake of such systems in Europe has been limited by a combination of unsupportive policies and uncertainty concerning their productivity, profitability, and environmental impact. Faced with a lack of experimental data, the parameter-sparse Yield-SAFE model offers one method for generating plausible yield data and improving understanding of production in mixed tree–crop systems under European conditions. The applicability of the model was examined by: (i) selecting two contrasting sites in France and the UK with measured agricultural, silvoarable and/or forestry data, (ii) implementing the model in a software package, and (iii) inputting data and parameters on the climate, soils, management regime, and tree and crop types. Following calibration, Yield-SAFE provided credible descriptions of measured arable and tree (Populus spp.) yields in the monoculture and silvoarable systems at the two sites. An examination of the response of the model to changes in model parameters and environmental and management data showed that silvoarable crop yields were most sensitive to variations in tree parameters. Increased soil depths increased timber yields, and increasing stand density increased stand volume whilst decreasing individual tree volume. In all the simulations, the model predicted greater efficiency in use of land, i.e. greater land equivalent ratios, when trees and crops were combined rather than grown as sole crops. These results, supported by the sparse experimental data available, indicate that agroforestry provides a method of increasing food, timber and biomass production from limited land resources in Europe. [Copyright &y& Elsevier]

Abstract: Silvoarable agroforestry could promote use of trees on farms in Europe, but its likely effect on production, farm profitability, and environmental services is poorly understood. Hence, from 2001 to 2005, the Silvoarable Agroforestry for Europe project developed a systematic process to evaluate the biophysical and economic performance of arable, forestry, and silvoarable systems in Spain, France, and The Netherlands. A biophysical model called “Yield-SAFE” was developed to predict long-term yields for the different systems and local statistics and expert opinion were used to derive their revenue, costs, and pre- and post-2005 grant regimes. These data were then used in an economic model called “Farm-SAFE” to predict plot- and farm-scale profitability. Land equivalent ratios were greater than one, showing Yield-SAFE predicted that growing trees and crops in silvoarable systems was more productive than growing them separately. Pre-2005 grants in Spain and The Netherlands penalised silvoarable systems, but post-2005 grants were more equitable. In France, walnut and poplar silvoarable systems were consistently the most profitable system under both grant regimes. In Spain, holm oak and stone pine silvoarable systems were the least profitable system under pre-2005 grants, but only marginally less profitable than arable systems under post-2005 grants. In The Netherlands, low timber values and the opportunity cost of losing arable land for slurry manure application made silvoarable and forestry systems uncompetitive with arable systems under both grant regimes. [Copyright &y& Elsevier]

• Air pollution removal by dry deposition of trees in the Basque Country is estimated. • Deposition is estimated at a 1 km x 1 km resolution at a regional scale. • Mean annual removal rates were 12.9 kg O 3 ha−1, 12.7 kg PM 10 ha−1, 3.0 kg NO 2 ha−1, 0.8 kg SO 2 ha−1 and 0.2 kg CO ha−1. • Coniferous forests provided the highest air pollution removal. • Tree cover density and duration of leaf lifespan determine deposition. There is increased interest in the role of trees to reduce air pollution and thereby improve human health and well-being. This study determined the removal of air pollutants by dry deposition of trees across the Basque Country and estimated its annual economic value. A model that calculates the hourly dry deposition of NO 2 , O 3 , SO 2 , CO and PM 10 on trees at a 1 km x 1 km resolution at a regional scale was developed. The calculated mean annual rates of removal of air pollution across various land uses were 12.9 kg O 3 ha−1, 12.7 kg PM 10 ha−1, 3.0 kg NO 2 ha−1, 0.8 kg SO 2 ha−1 and 0.2 kg CO ha−1. The results were then categorised according to land use in order to determine how much each land use category contributed to reducing air pollution and to determine to what extent trees provided pollution reduction benefits to society. Despite not being located in the areas of highest pollutions, coniferous forests, which cover 25% of the land, were calculated to absorb 21% of the air pollution. Compared to other land uses, coniferous forests were particularly effective in removing air pollution because of their high tree cover density and the duration of leaf life-span. The total economic value provided by the trees in reducing these pollutants in terms of health benefits was estimated to be €60 million yr−1 which represented around 0.09% of the Gross Domestic Product of the Basque Country in 2016. Whilst most health impacts from air pollution are in urban areas the results indicate that most air pollution is removed in rural areas. [ABSTRACT FROM AUTHOR]

In recent years water companies have started to adopt catchment management to reduce diffuse pollution in drinking water supply areas. The heterogeneity of catchments and the range of pollutants that must be removed to meet the EU Drinking Water Directive (98/83/EC) limits make it difficult to prioritise areas of a catchment for intervention. Thus conceptual frameworks are required that can disaggregate the components of pollutant risk and help water companies make decisions about where to target interventions in their catchments to maximum effect. This paper demonstrates the concept of generalising pollutants in the same framework by reviewing key pollutant processes within a source-mobilisation-delivery context. From this, criteria are developed (with input from water industry professionals involved in catchment management) which highlights the need for a new water industry specific conceptual framework. The new CaRPoW ( Ca tchment R isk to Po table W ater) framework uses the Source-Mobilisation-Delivery concept as modular components of risk that work at two scales, source and mobilisation at the field scale and delivery at the catchment scale. Disaggregating pollutant processes permits the main components of risk to be ascertained so that appropriate interventions can be selected. The generic structure also allows for the outputs from different pollutants to be compared so that potential multiple benefits can be identified. CaRPow provides a transferable framework that can be used by water companies to cost-effectively target interventions under current conditions or under scenarios of land use or climate change. [ABSTRACT FROM AUTHOR]

Abstract: Crop rotations are allocations by growers of crop types to specific fields through time. This paper aims at presenting (i) a systematic and rigorous mathematical representation of crops rotations; and (ii) a concise mathematical framework to model crop rotations, which is useable on landscape scale modelling of agronomical practices. Rotations can be defined as temporal arrangements of crops and can be classified systematically according to their internal variability and cyclical pattern. Crop sequences in a rotation can be quantified as a transition matrix, with the Markovian property that the allocation in a given year depends on the crop allocated in the previous year. Such transition matrices can represent stochastic processes and thus facilitate modelling uncertainty in rotations, and forecasting of the long-term proportions of each crop in a rotation, such as changes in climate or economics. The matrices also permit modelling transitions between rotations due to external variables. Computer software was developed that incorporates these techniques and was used to simulate landscape scale agronomic processes over decadal periods. [Copyright &y& Elsevier]

Abstract: The environmental and economic performance of silvoarable agroforestry in Europe is highly variable. Multi-criteria analysis, using the PROMETHEE outranking approach, was used to evaluate the integrated performance of silvoarable agroforestry on hypothetical farms in nineteen landscape test sites in Spain, France, and The Netherlands. The silvoarable scenarios allocated a proportion of the hypothetical farms (10 or 50%) to silvoarable agroforestry at two different tree densities (50 or 113 trees ha−1) on two different qualities of land (best or worst quality land). The status quo (conventional arable farming) was also assessed for comparison. The criteria used in the evaluation (soil erosion, nitrogen leaching, carbon sequestration, landscape biodiversity, and infinite net present value) were assessed at each landscape test site; infinite net present value was assessed under six levels of government support. In France, the analysis showed, assuming equal weighting between environmental and economic performance, that silvoarable agroforestry was preferable to conventional arable farming. The best results were observed when agroforestry was implemented on 50% of the highest quality land on the farm; the effect of tree density (50–113 trees ha−1) was small. By contrast, in Spain and The Netherlands, the consistently greater profitability of conventional arable agriculture relative to the agroforestry alternatives made overall performance of agroforestry systems dependent on the proportion of the farm planted, and the tree density and land quality used. [Copyright &y& Elsevier]

Abstract: Silvoarable agroforestry, the deliberate combined use of trees and arable crops on the same area of land, has been proposed in order to improve the environmental performance of agricultural systems in Europe. Based on existing models and algorithms, we developed a method to predict the environmental effects of SAF at a farm and landscape scale. The method is comprised of an assessment of soil erosion, nitrogen leaching, carbon sequestration, and landscape diversity and allowed the comparison of the environmental performance of SAF with arable systems using these four indicators. The method was applied to three landscape test sites of 4km×4km each in Spain, France, and The Netherlands, and compared different levels of agroforestry adoption on farmland of different potential productivity. Silvoarable agroforestry was predicted to reduce soil erosion by up to 70%, to reduce N leaching by 20–30%, to increase C sequestration over 60 years by up to 140tonnesCha−1, and to increase landscape diversity up to four times. The method developed was executed with widely available landscape and farm structural data and can therefore be applied to other regions in order to obtain a broader assessment of the environmental performance of silvoarable agroforestry systems. [Copyright &y& Elsevier]

The COVID‐19 pandemic is a major shock to society in terms of health and economy that is affecting both UK and global food and nutrition security. It is adding to the 'perfect storm' of threats to society from climate change, biodiversity loss and ecosystem degradation, at a time of considerable change, rising nationalism and breakdown in international collaboration. In the UK, the situation is further complicated due to Brexit. The UK COVID‐19Food andNutritionSecurity project, lasting one year, is funded by the Economic and Social Research Council and is assessing the ongoing impact of COVID‐19 on the four pillars of food and nutrition security: access, availability, utilisation and stability. It examines the food system, how it is responding, and potential knock on effects on the UK's food and nutrition security, both in terms of the cascading risks from the pandemic and other threats. The study provides an opportunity to place the initial lessons being learnt from the on‐going responses to the pandemic in respect of food and nutrition security in the context of other long‐term challenges such as climate change and biodiversity loss. [ABSTRACT FROM AUTHOR]

Whilst numerous studies have examined the environmental benefits of introducing additional trees within wood pasture systems few studies have assessed the impact on farm profitability. This paper describes a model, called Forage-SAFE, which has been developed to improve understanding of the management and economics of wood pastures. The model simulates the daily balance between food production and the livestock demand for food to estimate annual farm net margins. Parameters in Forage-SAFE such as tree cover density, carrying capacity, and type of livestock can be modified to analyse their interactions on profitability and to identify optimal managerial decisions against a range of criteria. A modelled dehesa wood pasture in South-western Spain was used as a case study to demonstrate the applicability of the model. The results for the modelled dehesa showed that for a carrying capacity of 0.44 livestock units per hectare the maximum net margin was achieved at a tree cover of around 53% with a mixture of Iberian pigs (28% of the livestock units) and ruminants (72%). The results also showed that the higher the carrying capacity the more profitable the tree cover was. This was accentuated as the proportion of Iberian pigs increased. [ABSTRACT FROM AUTHOR]

Carbon dioxide and nitrous oxide are two important greenhouse gases (GHG) released from cropping systems. Their emissions can vary substantially with climate, soil, and crop management. While different methods are available to account for GHG emissions in life cycle assessments (LCA) of crop production, there are no standard procedures. In this study, the objectives were: (i) to compare several methods of estimating CO 2 and N 2 O emissions for a LCA of cropping systems and (ii) to estimate the relative contribution of soil GHG emissions to the overall global warming potential (GWP) using results from a field experiment located in Manitoba, Canada. The methods were: (A) measurements; (B) Tier I and (C) Tier II IPCC (Intergovernmental panel on Climate Change) methodology, (D) a simple carbon model combined with Intergovernmental Panel for Climate Change (IPCC) Tier II methodology for soil N 2 O emissions, and (E) the DNDC (DeNitrification DeComposition) agroecosystem model. The estimated GWPs (−7.2–17 Mg CO 2 eq ha −1 y −1 ; −80 to 600 kg CO 2 eq GJ −1 y −1 ) were similar to previous results in North America and no statistical difference was found between GWP based on methods D and E and GWP based on observations. The five methods gave estimates of soil CO 2 emissions that were not statistically different from each other, whereas for N 2 O emissions only DNDC estimates were similar to observations. Across crop types, all methods gave comparable CO 2 and N 2 O emission estimates for perennial and legume crops, but only DNDC gave similar results with respect to observations for both annual and cereal crops. Whilst the results should be confirmed for other locations, the agroecosystem model and method D can be used, at certainly one selected site, in place of observations for estimating GHGs in agricultural LCA. [ABSTRACT FROM AUTHOR]

Abstract: The spatial and temporal arrangement of crops is a conspicuous feature of rural landscapes. It has been identified as an important factor in many environmental issues, such as the coexistence of genetically modified (GM) and non-GM crops, and the mitigation of soil erosion. This paper examines a scenario-based approach for rapid generation and screening of crop allocations that meet user’s constraints without requiring mechanistic modelling. LandSFACTS (Landscape Scale Functional Allocation of Crops Temporally and Spatially) is a software application specifically designed to simulate such crop arrangement scenarios, whilst ensuring both spatial and temporal coherence with regard to the initial constraints. The software uses an empirical approach to allocate crops to fields (polygons in vector format) over a sequence of years, using a stochastic process (Markov chains) and rule-based constraints. Crop rotations are represented by transition probabilities complemented by other temporal constraints such as return period or prohibited sequences. Further spatial and temporal constraints on crop arrangement can be applied through separation distances, yearly proportions, and the application of statistical tests. The software outputs a crop allocation solution with a crop for every field for every year, respecting all user-defined constraints; the range of potential solutions can then be explored through multiple model runs. Metrics based upon the difficulty of obtaining such an allocation from the initial constraints are also generated. A case study is provided to demonstrate the use of combined agronomic and environmental criteria for exploring GM crop coexistence at the landscape scale. [Copyright &y& Elsevier]

Increased adoption of silvoarable agroforestry (SAF) systems in Europe, by integrating trees and arable crops on the same land, could offer a range of environmental benefits compared with conventional agricultural systems. Soil erosion, nitrogen leaching, carbon sequestration and landscape biodiversity were chosen as indicators to assess a stratified random sample of 19 landscape test sites in the Mediterranean and Atlantic regions of Europe. At each site, the effect of introducing agroforestry was examined at plot-scale by simulating the growth of one of five tree species (hybrid walnut Juglans spp., wild cherry Prunus avium L., poplar Populus spp., holm oak Quercus ilex L. subsp. ilex and stone pine Pinus pinea L.) at two tree densities (50 and 113treesha−1) in combination with up to five crops (wheat Triticum spp., sunflower Helianthus annuus L., oilseed rape Brassica napus L., grain maize and silage maize Zea mays L.). At landscape-scale, the effect of introducing agroforestry on 10 or 50% of the agricultural area, on either the best or worst quality land, was examined. Across the 19 landscape test sites, SAF had a positive impact on the four indicators with the strongest effects when introduced on the best quality land. The computer simulations showed that SAF could significantly reduce erosion by up to 65% when combined with contouring practices at medium (>0.5 and <3tha−1 a−1) and high (>3tha−1 a−1) erosion sites. Nitrogen leaching could be reduced by up to 28% in areas where leaching is currently estimated high (>100kgNh−1 a−1), but this was dependent on tree density. With agroforestry, predicted mean carbon sequestration through immobilization in trees, over a 60-year period, ranged from 0.1 to 3.0tCh−1 a−1 (5–179tCh−1) depending on tree species and location. Landscape biodiversity was increased by introducing SAF by an average factor of 2.6. The implications of this potential for environmental benefits at European-scale are discussed. [Copyright &y& Elsevier]