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.

Modelling sediment supply and transport in the River Lugg: strategies for controlling sediment loads

The River Lugg has particular problems with high sediment loads that have resulted in detrimental impacts on ecology and fisheries. A new dynamic, process-based model of hydrology and sediments (INCA- SED) has been developed and applied to the River Lugg system using an extensive data set from 1995–2008. The model simulates sediment sources and sinks throughout the catchment and gives a good representation of the sediment response at 22 reaches along the River Lugg. A key question considered in using the model is the management of sediment sources so that concentrations and bed loads can be reduced in the river system. Altogether, five sediment management scenarios were selected for testing on the River Lugg, including land use change, contour tillage, hedging and buffer strips. Running the model with parameters altered to simulate these five scenarios produced some interesting results. All scenarios achieved some reduction in sediment levels, with the 40% land use change achieving the best result with a 19% reduction. The other scenarios also achieved significant reductions of between 7% and 9%. Buffer strips produce the best result at close to 9%. The results suggest that if hedge introduction, contour tillage and buffer strips were all applied, sediment reductions would total 24%, considerably improving the current sediment situation. We present a novel cost-effectiveness analysis of our results where we use percentage of land removed from production as our cost function. Given the minimal loss of land associated with contour tillage, hedges and buffer strips, we suggest that these management practices are the most cost-effective combination to reduce sediment loads.

Pollen analysis and planted ancient woodland restoration strategies: a case study from the Wentwood, southeast Wales,UK

This paper considers the contribution of pollen analysis to conservation strategies aimed at restoring planted ancient woodland. Pollen and charcoal data are presented from organic deposits located adjacent to the Wentwood, a large planted ancient woodland in southeast Wales. Knowledge of the ecosystems preceding conifer planting can assist in restoring ancient woodlands by placing fragmented surviving ancient woodland habitats in a broader ecological, historical and cultural context. These habitats derive largely from secondary woodland that regenerated in the 3rd–5th centuries A.D. following largescale clearance of Quercus-Corylus woodland during the Romano-British period. Woodland regeneration favoured Fraxinus and Betula. Wood pasture and common land dominated the Wentwood during the medieval period until the enclosures of the 17th century. Surviving ancient woodland habitats contain an important Fagus component that probably reflects an earlier phase of planting preceding conifer planting in the 1880s. It is recommended that restoration measures should not aim to recreate static landscapes or woodland that existed under natural conditions. Very few habitats within the Wentwood can be considered wholly natural because of the long history of human impact. In these circumstances, restoration should focus on restoring those elements of the cultural landscape that are of most benefit to a range of flora and fauna, whilst taking into account factors that present significant issues for future conservation management, such as the adverse effects from projected climate change.

Livestock and climate change impacts in the developing world

Livestock farming is one of the most important sectors in agriculture both economically and socially. In the developing world, livestock is crucial to generating livelihoods and food security for some one billion of the world's poorest people. The demand for livestock products is growing as diets change and the world population increases, mainly in the developing world. Climate change only adds to the challenge facing the world's most disadvantaged people. It impacts on livestock production systems and in turn livestock farming impacts on climate change. This paper reviews the complex interaction between livestock production and climate change and proposes strategies that could be used to help sustain livestock as a key feature of rural livelihoods in the developing world.

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.

The use of scenarios as the basis for combined assessment of climate change mitigation and adaptation

Scenarios are used to explore the consequences of different adaptation and mitigation strategies under uncertainty. In this paper, two scenarios are used to explore developments with (1) no mitigation leading to an increase of global mean temperature of 4 °C by 2100 and (2) an ambitious mitigation strategy leading to 2 °C increase by 2100. For the second scenario, uncertainties in the climate system imply that a global mean temperature increase of 3 °C or more cannot be ruled out. Our analysis shows that, in many cases, adaptation and mitigation are not trade-offs but supplements. For example, the number of people exposed to increased water resource stress due to climate change can be substantially reduced in the mitigation scenario, but adaptation will still be required for the remaining large numbers of people exposed to increased stress. Another example is sea level rise, for which, from a global and purely monetary perspective, adaptation (up to 2100) seems more effective than mitigation. From the perspective of poorer and small island countries, however, stringent mitigation is necessary to keep risks at manageable levels. For agriculture, only a scenario based on a combination of adaptation and mitigation is able to avoid serious climate change impacts.

Exit strategies for business tenants

Many businesses in the UK occupy premises on fixed term leases, which usually run for several years. During this time property requirements can change. This research critically examines the three main mechanisms by which tenants can bring their leases to an end; breaks, assignment and subletting. We examine the legal rules governing these devices and undertake an analysis of lease data and surveys. Break clauses are providing a useful exit mechanism for many tenants, but they cannot give the more general flexibility of assignment and subletting. However, change is necessary to ensure that these latter provisions provide real flexibility for tenants.

Societal choice for climate change futures: trees, biotechnology and clean development

The rate and magnitude of predicted climate change require that we urgently mitigate emissions or sequester carbon on a substantial scale in order to avoid runaway climate change. Geo- and bioengineering solutions are increasingly proposed as viable and practical strategies for tackling global warming. Biotechnology companies are already developing transgenic “super carbon-absorbing” trees, which are sold as a cost-effective and relatively low-risk means of sequestering carbon. The question posed in this article is, Do super carbon trees provide real benefits or are they merely a fanciful illusion? It remains unclear whether growing these trees makes sense in terms of the carbon cost of production and the actual storage of carbon. In particular, it is widely acknowledged that “carbon-eating” trees fail to sequester as much carbon as they oxidize and return to the atmosphere; moreover, there are concerns about the biodiversity impacts of large-scale monoculture plantations. The potential social and ecological risks and opportunities presented by such controversial solutions warrant a societal dialogue.

Conceptualizing change in the Portuguese footwear industry: regional voices and cognitive spaces of agency

Expanding national services sectors and global competition aggravate current and perceived future market pressures on traditional manufacturing industries. These perceptions of change have provoked a growing intensification of geo-political discourses on technological innovation and ‘learning’, and calls for competency in design among other professional skills. However, these political discourses on innovation and learning have paralleled public concerns with the apparent ‘growth pains’ from factory closures and subsequent increases in unemployment, and its debilitating social and economic implications for local and regional development. In this respect the following investigation sets out to conceptualize change through the complementary and differing perceptions of industry and regional actors’ experiences or narratives, linking these perceptions to their structure-determined spheres of agent-environment interactivity. It aims to determine whether agents’ differing perceptions of industry transformation can have a role in the legitimization of their interests in, and in sustaining their organizational influence over the process of industry-regional transformation. It argues that industry and regional agent perceptions are among the cognitive aspects of agent-environment interactivity that permeate agency. It stresses agents’ ability to reason and manipulate their work environments to preserve their self-regulating interests in, and task representative influence over the multi-jurisdictional space of industry-regional transformation. The contributions of this investigation suggest that agents’ varied perceptions of industry and regional change inform or compete for influence over the redirection of regional, industry and business strategies. This claim offers a greater appreciation for the reflexive and complex institutional dimensions of industry planning and development, and the political responsibility to socially just forms of regional development. It positions the outcomes of this investigation at the nexus of intensifying geo-political discourses on the efficiency and equity of territorial development in Europe.

Agricultural adaptation to climate change: insights from a farming community in Sri Lanka

The vulnerability of smallholder farmers to climate change and variability is increasingly rising. As agriculture is the only source of income for most of them, agricultural adaptation with respect to climate change is vital for their sustenance and to ensure food security. In order to develop appropriate strategies and institutional responses, it is necessary to have a clear understanding of the farmers’ perception of climate change, actual adaptations at farm-level and what factors drive and constrain their decision to adapt. Thus, this study investigates the farm-level adaptation to climate change based on the case of a farming community in Sri Lanka. The findings revealed that farmers’ perceived the ongoing climate change based on their experiences. Majority of them adopted measures to address climate change and variability. These adaptation measures can be categorised into five groups, such as crop management, land management, irrigation management, income diversification, and rituals. The results showed that management of non-climatic factors was an important strategy to enhance farmers’ adaptation, particularly in a resource-constrained smallholder farming context. The results of regression analysis indicated that human cognition was an important determinant of climate change adaptation. Social networks were also found to significantly influence adaptation. The study also revealed that social barriers, such as cognitive and normative factors, are equally important as other economic barriers to adaptation. While formulating and implementing the adaptation strategies, this study underscored the importance of understanding socio-economic, cognitive and normative aspects of the local communities.

Extreme precipitation and climate change: the potential impacts on flooding

Recent extreme precipitation events have caused widespread flooding to the UK. The prediction of the intensity of such events in a warmer climate is important for adaption strategies against future events. This study highlights the importance of using high-resolution models to predict these events. Using a high-resolution GCM it is shown that extreme precipitation events are predicted to become more frequent under the IPCC A1B warming scenario. It is also shown that current forecast models have difficulty in predicting the location, timing and intensity of small scale precipitation in areas with significant orography.

A framework for agricultural adaptation to climate change in Southern Nigeria

The agricultural sector which contributes between 20-50% of gross domestic product in Africa and employs about 60% of the population is greatly affected by climate change impacts. Agricultural productivity and food prices are expected to rise due to this impact thereby worsening the food insecurity and poor nutritional health conditions in the continent. Incidentally, the capacity in the continent to adapt is very low. Addressing these challenges will therefore require a holistic and integrated adaptation framework hence this study. A total of 360 respondents selected through a multi-stage random sampling technique participated in the study that took place in Southern Nigeria from 2008-2011. Results showed that majority of respondents (84%) were aware that some climate change characteristics such as uncertainties at the onset of farming season, extreme weather events including flooding and droughts, pests, diseases, weed infestation, and land degradation have all been on the increase. The most significant effects of climate change that manifested in the area were declining soil fertility and weed infestation. Some of the adaptation strategies adopted by farmers include increased weeding, changing the timing of farm operations, and processing of crops to reduce post-harvest losses. Although majority of respondents were aware of government policies aimed at protecting the environment, most of them agreed that these policies were not being effectively implemented. A mutually inclusive framework comprising of both indigenous and modern techniques, processes, practices and technologies was then developed from the study in order to guide farmers in adapting to climate change effects/impacts.

Modelling the impact of land use change on water quality in agricultural catchments

Export coefficient modelling was used to model the impact of agriculture on nitrogen and phosphorus loading on the surface waters of two contrasting agricultural catchments. The model was originally developed for the Windrush catchment where the highly reactive Jurassic limestone aquifer underlying the catchment is well connected to the surface drainage network, allowing the system to be modelled using uniform export coefficients for each nutrient source in the catchment, regardless of proximity to the surface drainage network. In the Slapton catchment, the hydrological path-ways are dominated by surface and lateral shallow subsurface flow, requiring modification of the export coefficient model to incorporate a distance-decay component in the export coefficients. The modified model was calibrated against observed total nitrogen and total phosphorus loads delivered to Slapton Ley from inflowing streams in its catchment. Sensitivity analysis was conducted to isolate the key controls on nutrient export in the modified model. The model was validated against long-term records of water quality, and was found to be accurate in its predictions and sensitive to both temporal and spatial changes in agricultural practice in the catchment. The model was then used to forecast the potential reduction in nutrient loading on Slapton Ley associated with a range of catchment management strategies. The best practicable environmental option (BPEO) was found to be spatial redistribution of high nutrient export risk sources to areas of the catchment with the greatest intrinsic nutrient retention capacity.

Evaluation and management of the impact of land use change on the nitrogen and phosphorus load delivered to surface waters: the export coefficient modelling approach

A manageable, relatively inexpensive model was constructed to predict the loss of nitrogen and phosphorus from a complex catchment to its drainage system. The model used an export coefficient approach, calculating the total nitrogen (N) and total phosphorus (P) load delivered annually to a water body as the sum of the individual loads exported from each nutrient source in its catchment. The export coefficient modelling approach permits scaling up from plot-scale experiments to the catchment scale, allowing application of findings from field experimental studies at a suitable scale for catchment management. The catchment of the River Windrush, a tributary of the River Thames, UK, was selected as the initial study site. The Windrush model predicted nitrogen and phosphorus loading within 2% of observed total nitrogen load and 0.5% of observed total phosphorus load in 1989. The export coefficient modelling approach was then validated by application in a second research basin, the catchment of Slapton Ley, south Devon, which has markedly different catchment hydrology and land use. The Slapton model was calibrated within 2% of observed total nitrogen load and 2.5% of observed total phosphorus load in 1986. Both models proved sensitive to the impact of temporal changes in land use and management on water quality in both catchments, and were therefore used to evaluate the potential impact of proposed pollution control strategies on the nutrient loading delivered to the River Windrush and Slapton Ley

Strategies: Revolution in climate prediction is both necessary and possible: A declaration at the World Modelling Summit for Climate Prediction

The impending threat of global climate change and its regional manifestations is among the most important and urgent problems facing humanity. Society needs accurate and reliable estimates of changes in the probability of regional weather variations to develop science-based adaptation and mitigation strategies. Recent advances in weather prediction and in our understanding and ability to model the climate system suggest that it is both necessary and possible to revolutionize climate prediction to meet these societal needs. However, the scientific workforce and the computational capability required to bring about such a revolution is not available in any single nation. Motivated by the success of internationally funded infrastructure in other areas of science, this paper argues that, because of the complexity of the climate system, and because the regional manifestations of climate change are mainly through changes in the statistics of regional weather variations, the scientific and computational requirements to predict its behavior reliably are so enormous that the nations of the world should create a small number of multinational high-performance computing facilities dedicated to the grand challenges of developing the capabilities to predict climate variability and change on both global and regional scales over the coming decades. Such facilities will play a key role in the development of next-generation climate models, build global capacity in climate research, nurture a highly trained workforce, and engage the global user community, policy-makers, and stakeholders. We recommend the creation of a small number of multinational facilities with computer capability at each facility of about 20 peta-flops in the near term, about 200 petaflops within five years, and 1 exaflop by the end of the next decade. Each facility should have sufficient scientific workforce to develop and maintain the software and data analysis infrastructure. Such facilities will enable questions of what resolution, both horizontal and vertical, in atmospheric and ocean models, is necessary for more confident predictions at the regional and local level. Current limitations in computing power have placed severe limitations on such an investigation, which is now badly needed. These facilities will also provide the world's scientists with the computational laboratories for fundamental research on weather–climate interactions using 1-km resolution models and on atmospheric, terrestrial, cryospheric, and oceanic processes at even finer scales. Each facility should have enabling infrastructure including hardware, software, and data analysis support, and scientific capacity to interact with the national centers and other visitors. This will accelerate our understanding of how the climate system works and how to model it. It will ultimately enable the climate community to provide society with climate predictions, which are based on our best knowledge of science and the most advanced technology.