Improving productivity and water use efficiency: a case study of farms in England

The idea of Sustainable Intensification comes as a response to the challenge of avoiding resources such as land, water and energy being overexploited while increasing food production for an increasing demand from a growing global population. Sustainable Intensification means that farmers need to simultaneously increase yields and sustainably use limited natural resources, such as water. Within the agricultural sector water has a number of uses including irrigation, spraying, drinking for livestock and washing (vegetables, livestock buildings). In order to achieve Sustainable Intensification measures are needed that enable policy makers and managers to inform them about the relative performance of farms as well as of possible ways to improve such performance. We provide a benchmarking tool to assess water use (relative) efficiency at a farm level, suggest pathways to improve farm level productivity by identifying best practices for reducing excessive use of water for irrigation. Data Envelopment Analysis techniques including analysis of returns to scale were used to evaluate any excess in agricultural water use of 66 Horticulture Farms based on different River Basin Catchments across England. We found that farms in the sample can reduce on average water requirements by 35% to achieve the same output (Gross Margin) when compared to their peers on the frontier. In addition, 47% of the farms operate under increasing returns to scale, indicating that farms will need to develop economies of scale to achieve input cost savings. Regarding the adoption of specific water use efficiency management practices, we found that the use of a decision support tool, recycling water and the installation of trickle/drip/spray lines irrigation system has a positive impact on water use efficiency at a farm level whereas the use of other irrigation systems such as the overhead irrigation system was found to have a negative effect on water use efficiency.

Translation practices in political institutions: a comparison of national, supranational, and non-governmental organisations

This paper explores the settings and practices of translation at three types of political institutions, i.e. national, supranational, and non-governmental organisations. The three institutions are the translation service of the German Foreign Office, the translation department of the European Central Bank, and translation provision by the non-governmental organisation Amnesty International. The three case studies describe the specific translation practices in place at these institutions and illustrate some characteristic translation strategies. In this way, we reflect on how different translation practices can impact on translation agency and how these practices in turn are influenced by the type of institution and its organisational structure. The article also aims to explore to which extent the characteristics of collectivity, anonymity and standardisation, and of institutional translation as self-translation are applicable to the institutions under discussion.

Biogeochemical cycles and biodiversity as key drivers of ecosystem services provided by soils

Soils play a pivotal role in major global biogeochemical cycles (carbon, nutrient, and water), while hosting the largest diversity of organisms on land. Because of this, soils deliver fundamental ecosystem services, and management to change a soil process in support of one ecosystem service can either provide co-benefits to other services or result in trade-offs. In this critical review, we report the state-of-the-art understanding concerning the biogeochemical cycles and biodiversity in soil, and relate these to the provisioning, regulating, supporting, and cultural ecosystem services which they underpin. We then outline key knowledge gaps and research challenges, before providing recommendations for management activities to support the continued delivery of ecosystem services from soils. We conclude that, although soils are complex, there are still knowledge gaps, and fundamental research is still needed to better understand the relationships between different facets of soils and the array of ecosystem services they underpin, enough is known to implement best practices now. There is a tendency among soil scientists to dwell on the complexity and knowledge gaps rather than to focus on what we do know and how this knowledge can be put to use to improve the delivery of ecosystem services. A significant challenge is to find effective ways to share knowledge with soil managers and policy makers so that best management can be implemented. A key element of this knowledge exchange must be to raise awareness of the ecosystems services underpinned by soils and thus the natural capital they provide. We know enough to start moving in the right direction while we conduct research to fill in our knowledge gaps. The lasting legacy of the International Year of Soils in 2015 should be for soil scientists to work together with policy makers and land managers to put soils at the centre of environmental policy making and land management decisions.

Conditioning and preconditioning of the optimal state estimation problem

Optimal state estimation is a method that requires minimising a weighted, nonlinear, least-squares objective function in order to obtain the best estimate of the current state of a dynamical system. Often the minimisation is non-trivial due to the large scale of the problem, the relative sparsity of the observations and the nonlinearity of the objective function. To simplify the problem the solution is often found via a sequence of linearised objective functions. The condition number of the Hessian of the linearised problem is an important indicator of the convergence rate of the minimisation and the expected accuracy of the solution. In the standard formulation the convergence is slow, indicating an ill-conditioned objective function. A transformation to different variables is often used to ameliorate the conditioning of the Hessian by changing, or preconditioning, the Hessian. There is only sparse information in the literature for describing the causes of ill-conditioning of the optimal state estimation problem and explaining the effect of preconditioning on the condition number. This paper derives descriptive theoretical bounds on the condition number of both the unpreconditioned and preconditioned system in order to better understand the conditioning of the problem. We use these bounds to explain why the standard objective function is often ill-conditioned and why a standard preconditioning reduces the condition number. We also use the bounds on the preconditioned Hessian to understand the main factors that affect the conditioning of the system. We illustrate the results with simple numerical experiments.

EDITOR'S CHOICE: REVIEW: Trait matching of flower visitors and crops predicts fruit set better than trait diversity

Understanding the relationships between trait diversity, species diversity and ecosystem functioning is essential for sustainable management. For functions comprising two trophic levels, trait matching between interacting partners should also drive functioning. However, the predictive ability of trait diversity and matching is unclear for most functions, particularly for crop pollination, where interacting partners did not necessarily co-evolve. World-wide, we collected data on traits of flower visitors and crops, visitation rates to crop flowers per insect species and fruit set in 469 fields of 33 crop systems. Through hierarchical mixed-effects models, we tested whether flower visitor trait diversity and/or trait matching between flower visitors and crops improve the prediction of crop fruit set (functioning) beyond flower visitor species diversity and abundance. Flower visitor trait diversity was positively related to fruit set, but surprisingly did not explain more variation than flower visitor species diversity. The best prediction of fruit set was obtained by matching traits of flower visitors (body size and mouthpart length) and crops (nectar accessibility of flowers) in addition to flower visitor abundance, species richness and species evenness. Fruit set increased with species richness, and more so in assemblages with high evenness, indicating that additional species of flower visitors contribute more to crop pollination when species abundances are similar. Synthesis and applications. Despite contrasting floral traits for crops world-wide, only the abundance of a few pollinator species is commonly managed for greater yield. Our results suggest that the identification and enhancement of pollinator species with traits matching those of the focal crop, as well as the enhancement of pollinator richness and evenness, will increase crop yield beyond current practices. Furthermore, we show that field practitioners can predict and manage agroecosystems for pollination services based on knowledge of just a few traits that are known for a wide range of flower visitor species.

Ecological and social drivers of coffee pollination in Santander, Colombia

Bees and other insects provide pollination services that are key to determining the fruit set on coffee plantations. These pollination services are influenced by local ecology as well as human factors, both social and economic. To better understand these different factors, we assessed their effect on pollinators and coffee pollination services in Santander, Colombia. We quantified the effect of key ecological drivers on pollinator community composition, such as the method of farm management (either conventional or organic) and the surrounding landscape composition, specifically the proximity to forest. We found that ambient levels of pollination services provided by the local pollinator fauna (open pollination) accounted for a 10.5 ± 2.0% increase in final coffee fruit set, and that the various pollinators are affected differently by the differing factors. For example, our findings indicate that conventional farm management, using synthetic inputs, can promote pollinators, especially if they are in close proximity to natural forest fragments. This is particularly true for stingless bees. Honeybee visitation to coffee is also positively influenced by the conventional management of farms. Factors associated with greater numbers of stingless bees on farms include greater shade cover, lower tree densities, smaller numbers and types of trees in bloom, and younger coffee plantations. A forested landscape close to farms appears to enhance these factors, giving increased stability and resilience to the pollinating bees and insects. However we found that organic farms also support diverse pollinator communities, even if distant from forest fragments. The contribution of honeybees to pollination value (US$129.6/ha of coffee) is greater than that of stingless bees (US$16.5/ha of coffee). Since the method of farm management has a major impact on the numbers and types of pollinators attracted to farms, we have analysed the statistically significant social factors that influence farmers’ decisions on whether to adopt organic or conventional practices. These include the availability of technology, the type of landowner (whether married couples or individual owners), the number of years of farmers’ formal education, the role of institutions, membership of community organizations, farm size, coffee productivity and the number of coffee plots per farm. It is hoped that the use of our holistic approach, which combines investigation of the social as well as the ecological drivers of pollination, will help provide evidence to underpin the development of best practices for integrating the management of pollination into sustainable agricultural practices.

Environmentalities of urban climate governance in Maputo, Mozambique

Interest in the role that cities can play in climate change as sites of transformation has increased but research has been limited in its practical applications and there has been limited consideration of how policies and technologies play out. These challenges necessitate a re-thinking of existing notions of urban governance in order to account for the practices that emerge from governments and a plethora of other actors in the context of uncertainty. We understand these practices to constitute adaptive governance, underpinned by social learning guiding the actions of the multiplicity of actors. The aim here is to unpack how social learning for adaptive governance requires attention to competing understandings of risk and identity, and the multiplicity of mechanisms in which change occurs or is blocked in urban climate governance. We adopt a novel lens of 'environmentalities' which allows us to assess the historical and institutional context and power relations in the informal settlements of Maputo, Mozambique. Our findings highlight how environmental identities around urban adaptation to climate change are constituted in the social and physical divisions between the formal and informal settlements, whilst existing knowledge models prioritise dominant economic and political interests and lead to the construction of new environmental subjects. While the findings of this study are contextually distinct, the generalizable lessons are that governance of urban adaptation occurs and is solidified within a complex multiplicity of socioecological relations.