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To design policies for sustainable irrigation planning, public decision-makers need knowledge about the potential environmental impacts of irrigated farming systems. In a previous paper, we proposed to couple Life Cycle Assessment (LCA) and Agrarian System Diagnosis (ASD) to build the Life Cycle Inventory (LCI) of a farming region in a context of data scarcity and farming system diversity. This method was applied to the semi-arid irrigated plain of Kairouan (Tunisia). The aim of the present paper is to demonstrate how this new ASD-based LCA method is used to conduct the impact assessment of this farming region, under current conditions and for two prospective scenarios. Two functional units (FU) were used: the area and the gross product generated. Life Cycle Impact Assessment (LCIA) was conducted based on a multilevel process, by converting LCI data collected for each cropping/ livestock system into LCIA outputs, which were then consolidated at the farming system (FS) and at the regional scales. Two scenarios, based on observed trends, were assessed: the "agrarian" scenario (driven by a shift from family to corporate farming) and the "hydrological" scenario (driven by a water table drawdown). Environmental hotspots were identified at each scale: the most impactful FS was the "mixed family farming" (intermediate access to water), because of its large share of land at the regional scale (45%). In this FS, the most harmful cropping system was input-intensive olive groves intercropped with a melon-pepper/ cereal/ tomato rotation, in which most impacts (35%) were attributable to the input-intensive "melon" crop, and more particularly to "manufacture and transport of fertilizer", including farmyard manure. Globally, the most harmful processes were water and fertilizer use (fertilizer manufacturing and transportation). This downscaling is very useful to inform public policies on the most harmful productions. The impacts in human, ecosystem and resource endpoints increased by 11%, 2%, 9% and 23%, 27% and 40%, for the agrarian and hydrological scenarios respectively. These results show that observed trends in farming practices evolution (more irrigation) should be stopped. Our method has three main strengths: i) inter-farms synergies are accounted for in the LCIA, which is essential to promote circularity; ii) thanks to the innovative and multilevel approach, the origins of environmental hotspots can be investigated and later mitigated by future policies; iii) ASD helps to design sustainable scenarios by identifying current trends and regional thresholds (resources, pollution and workforce) that cannot be overcome. [Display omitted] • Multilevel Life Cycle Impact Assessment (LCIA) was conducted in a semi-arid irrigated plain (Tunisia). • Agrarian System Diagnosis and Life Cycle Assessment methods were coupled. • Environmental hotspots are modeled from the plot /herd, up to the regional scale. • Main impacts are caused by water depletion, fertilizer manufacturing and manure transportation. • Environmental impacts may increase by 40% in trend evolution scenarios (watertable depletion and less familial farming). [ABSTRACT FROM AUTHOR]

Ancient irrigation systems (AISs) have been providing a multitude of ecosystem services to rural farming and urban communities in Asia and Africa, especially in arid and semi-arid climatic areas with low rainfall. Many AISs, however have now been degraded. A systematic analysis of AISs on their typologies, causes of degradation, and their ecosystem services is lacking. The objective of this review was to synthesize the knowledge on AISs on their typologies, status and causes of degradation, ecosystem services and functions, and identify gaps in research in Asia and Africa. A critical review of peer-reviewed journal papers, conference and workshop proceedings, book chapters, grey literature, and country reports was conducted. Qualitative and quantitative information from journal papers were used to conceptualize the typologies and analyze the status and causes of degradation, and ecosystems services and functions provided by the AISs. Based on the review, we classified AISs into three groups by source of irrigation water: Rainwater harvesting system (RHS) with small reservoirs, ground water based system, and floodwater based system. The RHSs, which used to receive reliable rainfall and managed by well cohesive social organizations for their maintenance and functioning in past, have now been silting due to extreme rainfall pattern and breakdown of the cohesive organizations in recent decades. In ground water based systems, indiscriminate development of deep tube wells causing siltation of channels has been a major challenge. In floodwater irrigation systems, irregular rainfall in the highlands and the breakage of irrigation structures by destructive floods were the main causes of degradation. Lack of maintenance and increased soil erosion, inadequate skilled manpower, and declining support from the government for repair and maintenance were the main causes of degradation of all AISs. The main ecosystem service provided by all AISs is water for agriculture. In tank- and pond-based systems, fish farming is also practiced. Tank irrigation systems provide various types of provisioning, regulatory, cultural and supporting services, especially in India and Sri Lanka. Ground water based systems provide water for domestic purposes and various cultural services. Floodwater based systems provide water for power generation and wildlife habitat maintenance and help in flood control. The knowledge generated through the review provide evidence-based information, and help aware governments, private sectors and development agencies for improved policy planning and decision making, and prioritizing the restoration, rehabilitation, and management of various AISs. Community Managed Ancient Irrigation Systems in Asia and Africa: Typologies, Degradation and Ecosystem services. [Display omitted] • Ancient irrigation systems (AISs) in Asia and Africa provide a multitude of benefits to mankind but are at a threat of degradation. • A systematic review conducted to identify typologies, status and causes of degradation of, and ecosystems services provided by, AISs. • Three typologies (rainwater harvesting, groundwater, and surface water based) and four ecosystems services identified. • Cascade tanks in Sri Lanka and India provide irrigation water for farming communities and ecosystem services for local communities and societies. • Rehabilitation of AISs needs urgent attention by governments, private sector, and development partners. [ABSTRACT FROM AUTHOR]

The improvement and application of pest and disease models to analyse and predict yield losses including those due to climate change is still a challenge for the scientific community. Applied modelling of crop diseases and pests has mostly targeted the development of support capabilities to schedule scouting or pesticide applications. There is a need for research to both broaden the scope and evaluate the capabilities of pest and disease models. Key research questions not only involve the assessment of the potential effects of climate change on known pathosystems, but also on new pathogens which could alter the (still incompletely documented) impacts of pests and diseases on agricultural systems. Yield loss data collected in various current environments may no longer represent a adequate reference to develop tactical, decision-oriented, models for plant diseases and pests and their impacts, because of the ongoing changes in climate patterns. Process-based agricultural simulation modelling, on the other hand, appears to represent a viable methodology to estimate the impacts of these potential effects. A new generation of tools based on state-of-the-art knowledge and technologies is needed to allow systems analysis including key processes and their dynamics over appropriate suitable range of environmental variables. This paper offers a brief overview of the current state of development in coupling pest and disease models to crop models, and discusses technical and scientific challenges. We propose a five-stage roadmap to improve the simulation of the impacts caused by plant diseases and pests; i) improve the quality and availability of data for model inputs; ii) improve the quality and availability of data for model evaluation; iii) improve the integration with crop models; iv) improve the processes for model evaluation; and v) develop a community of plant pest and disease modelers. [ABSTRACT FROM AUTHOR]

Place-based social, cultural, institutional and political dynamics not only influence the innovation capacity of agricultural systems, but also the willingness of relevant actors to be involved in participatory research processes, and the dynamics of their participation. This paper critically discusses the modification and application of one particular participatory approach to agricultural systems analysis (Rapid Appraisal of Agricultural Innovation Systems [RAAIS]) to agricultural adaptation in Southeast Kazakhstan. We consider the overall effectiveness of the method as a research tool, practical issues in the implementation of workshops, definition of and selection of participant groups, as well as the questions of participation and empowerment within the workshops themselves. We find that although RAAIS is adaptable to alternative theoretical frameworks, its implementation in different socio-cultural and political contexts may require more consideration than is apparent in previous discussions. In particular, the appropriate training of workshop organisers is of crucial importance to the success of this methodology. These findings will be useful to those adapting participatory research methods to different research topics and contexts more broadly. [ABSTRACT FROM AUTHOR]

As a result of population growth, urbanization and climate change, agricultural systems around the world face enormous pressure on the use of resources. There is a pressing need for wide-scale innovation leading to development that improves the livelihoods and food security of the world's population while at the same time addressing climate change adaptation and mitigation. A variety of promising climate-smart interventions have been identified. However, what remains is the prioritization of interventions for investment and broad dissemination. The suitability and adoption of interventions depends on a variety of bio-physical and socio-economic factors. Also their impacts, when adopted and out-scaled, are likely to be highly heterogeneous. This heterogeneity expresses itself not only spatially and temporally but also in terms of the stakeholders affected, some might win and some might lose. A mechanism that can facilitate a systematic, holistic assessment of the likely spread and consequential impact of potential interventions is one way of improving the selection and targeting of such options. In this paper we provide climate smart agriculture (CSA) planners and implementers at all levels with a generic framework for evaluating and prioritising potential interventions. This entails an iterative process of mapping out recommendation domains, assessing adoption potential and estimating impacts. Through examples, related to livestock production in sub-Saharan Africa, we demonstrate each of the steps and how they are interlinked. The framework is applicable in many different forms, scales and settings. It has a wide applicability beyond the examples presented and we hope to stimulate readers to integrate the concepts in the planning process for climate-smart agriculture, which invariably involves multi-stakeholder, multi-scale and multi-objective decision-making. [ABSTRACT FROM AUTHOR]

This paper describes an investigation of various adaptations of rice based cropping systems to climate variability in India's Telangana State. All adaptations were generated through participatory engagement and were field-tested with local smallholder households before being evaluated through cropping system simulation analysis. This approach contrasts with most research about adaptation of cropping systems to climate variability and climate change that is mostly based on simplifying assumptions about current farmer management practices and where the feasibility of implementing proposed adaptations is rarely tested. In this study, the investigation commenced with discussions about climate related issues in rice based farming systems between researchers, farmers and NGOs in three villages in three Mandals of the state of Telangana. Participatory intervention was used to identify new practices that could provide more adaptive and robust responses to climate variability. Suggested adaptations were implemented in on-farm experimentation. Fields demonstrating these adaptations were monitored and results were discussed with participating farmers at regular ‘Climate Club’ village meetings. Crop and soil data from these fields were used to locally parameterise the cropping systems simulator APSIM. Local adaptations that were trialled in the villages were simulated using local soil and long term historical weather data. In each of the case studies, a number of adaptations that were developed and implemented in the villages were shown through simulation to be successful in terms of agricultural production, stability of yields and resource use efficiency. Of the adaptations investigated, sowing rules to reduce the chance of crop failure due to early dry spells were most readily adopted and are also relatively easy to extend to other villages. Strategic irrigation of rainfed crops such as maize and cotton resulted in significant gains to profitability and stability of these crops but cannot be considered in isolation where access to water is limited. Reduced irrigation of rice resulted in over 60 mm/ha/yr. savings in water and some improvements in gross margins but this adaptation was not popular with farmers due to its burden on labour and added risks associated with unreliable supply of electricity for pumping at critical times. The reduced rice area for strategic irrigation of rainfed crops adaptation resulted in improved gross margins per hectare per year and higher net water productivity. This adaptation is most promising but will require institutional change around water use policy and more equitable allocation of limited water resources within villages. These results led us to the proposition that participatory action research with smallholder farmers, coupled with field-testing and simulation analysis can produce practical and productive adaptations to climate variability. [ABSTRACT FROM AUTHOR]

Abstract: The Ricardian approach has been applied to many different geographic contexts and most applications concern large countries. Only few studies deal with Europe. This paper applies the Ricardian approach to measure the impact of climate on the agricultural system of a small Italian Alpine region where permanent cultivations are the main crop. Structural and economic data about farmers growing apples and grapes are extracted from the Italian Farm Accountancy Data Network (FADN). It tests three possible functional forms and it highlights the importance of controlling not only for farms’ characteristics but also for farmers’ strategic decisions such as specialization and quality certification. In contrast with overall beneficial effects of climate change found for broad areas in Europe (Germany and England), climate change seems to imply a reduction in annual net revenues in our study area. From a methodological point of view, results show that if there is enough climatic variation across the sample and suitable control variables are available, the Ricardian approach can be applied also on a small territorial scale, even though the results depend heavily on the adopted functional form. [Copyright &y& Elsevier]

Abstract: Modern agriculture must meet new challenges such as production of healthy food, adaptation to climate change, protection of natural resources, and conservation of landscape. These challenges require changes in current agricultural systems and therefore, environmentally-friendly agricultural systems must be designed and their sustainability assessed. Over the past several years, various methods have been developed for making such assessments (e.g. the Balancing and Ranking Method, MEACROS, MODAM, the modelling framework of Pacini et al., ROTAT+FarmImages, MASC, and ROTOR) but few studies put forward simple solutions for selecting one method over another. In this paper, we propose a simple guide to distinguish methods one from another. Categories of the guide include the type of systems to assess, the spatial and temporal scales at which systems are assessed, the dimensions of sustainability for which systems are assessed, the type of visualisation for comparing options, the target users, and the ability to generate alternative systems. The guide was developed and tested with a group of farm advisors involved in a three-year project called RotAB, which aimed to assess the sustainability of organic arable farming systems: the advisors looked for a method for sustainability assessment of cropping systems. We presented seven recent assessment methods as well as the guide to advisors. The guide’s key points allowed them to clearly express their requirements: the method they looked for had to evaluate cropping systems and helped advisors to propose new ones; it had to evaluate multiple sustainability criteria that are easily understandable by farmers; indicators had to be scientifically based, without the need for many input data; the method had to be easy to use and produced graphical output that can be discussed with farmers. Finally, the guide helped advisors to choose one of the seven methods (in that case they chose MASC). This guide can help decision-makers distinguish assessment tools from one another using simple categories and choose the one best adapted to their expectations. [Copyright &y& Elsevier]

Abstract: Agro-meteorological metrics are indicators of weather determined environmental conditions on which agricultural management decisions are made. Metrics derived from an estimated future climate provide an opportunity to characterise the impacts of climate change on a wide range of agricultural systems, land use practices and ecosystem services. Such indications are vital for determining how changes in the biophysical environment can lead to land management and policy adaptations to achieve multiple objectives of financial viability, food security, biodiversity conservation and environmental sustainability. They provide valuable links between probable management adaptation responses and capacity for mitigating greenhouse gas emissions. However, there are large uncertainties associated with projected future climates, including the climate models’ spatial scale of representation and those at which agro-meteorological metrics are applied. This paper describes the estimation of agro-meteorological metrics derived from observed weather and downscaled Regional Climate Model projection data for 12 sites in Scotland. Results show that projected changes to seasonal rainfall distribution, growing season length, soil moisture deficits and accessibility will be substantially different from the present climate. Fundamentally, the metrics indicate a substantial shift in land management requirements and potential need for substantial changes in agricultural systems and land use that will have implications across a wide range of research disciplines. [Copyright &y& Elsevier]

Abstract: Sub-Saharan Africa (SSA) is predicted to experience considerable negative impacts of climate change. The IPCC Fourth Assessment emphasizes that adaptation strategies are essential. Addressing adaptation in the context of small-scale, semi-subsistence agriculture raises special challenges. High data demands including site-specific bio-physical and economic data are an important constraint. This paper applies a new approach to impact assessment, the Tradeoff Analysis model for Multi-Dimensional Impact Assessment (TOA-MD), which simulates technology adoption and associated economic, environmental and social outcomes in a heterogeneous farm population for a regional impact assessment. The methodology uses the kinds of survey, experimental and modeled data that are typically available in countries where semi-subsistence systems are important, combined with future socio-economic scenarios based on new scenario pathway concepts being developed by the climate change and impact assessment modeling communities. Characteristics of current and future agricultural systems, including land use, output, output price, cost of production, and farm and household size are analyzed and compared for both current and projected future climate (2030), with and without adaptation, and for different socio-economic scenarios. The methodology is applied to two study areas in Kenya. These case studies show the potential of this approach to provide a flexible, generic framework that can use available and modeled data to evaluate climate impact and adaptation strategies under a range of socio-economic scenarios. [Copyright &y& Elsevier]

Abstract: Policy makers in the agricultural sector are confronted with challenges which might drive land use change and ultimately agricultural profitability to a substantial degree. The challenges include questions around climate variability, demographic changes, use of land for bio-fuel production and ensuring an increase in food production. As profitability triggers many agri-business decisions, knowledge about the existing socio-economic landscape and the economic profile of a region as well as potential impacts on profits provides useful contextual information when agricultural policies are designed. Given the upcoming challenges and their associated uncertainties, it is important to ensure that a map of agricultural profit can be reproduced in a scenario and simulation setting which will allow exploring uncertainties around the impacts on agricultural profits as well. There is however currently no flexible system in operation which allows for a consistent update of a map of agricultural profits in Australia or elsewhere. This paper describes a process that has been developed to produce a map of agricultural profit for Australia for the year 2005/2006. The process involves a complex data architecture that accounts for heterogeneous information that is collected by a variety of institutions across different scales. All information can be comfortably queried and query results can be forwarded for immediate processing and subsequent visualisation in a geographic information system (GIS). To facilitate the production of profit maps in the future, the system provides flexibility regarding an update of new economic information but it can also be linked to maps that show an updated distribution of land use. A map of agricultural profit on a large scale and regular updates thereof will help understand profit trends in time and across space. It will help identifying regions that have a lower economic profile and will inform decisions regarding the design of regulatory policies. As these maps are developed using national scale data, we do not recommend using the results at the farm level but we suggest using separate catchment scale profit assessments to calibrate the national scale profit map. The proposed system is well suited to be used in various land use management and economic scenarios and will represent a step forward regarding a scenario impact assessment on agricultural profits. It will also help understand the economic benefit of land use on a large scale. [Copyright &y& Elsevier]

• Livestock systems in the United Kingdom will be affected by climate change. • A range of on-farm adaptation options are available at low-cost. • Adapting to observed and short-term impacts may overcome barriers. • Long-term changes should be planned for. Agriculture is a vital economic sector, providing food, fibre, and energy to a growing human population. Livestock are an important part of this sector, however the evidence and understanding of how a changing climate may affect livestock production systems, or how they may adapt to the changes, is a neglected area compared to the research into crop production. In this paper, we focus on livestock in the United Kingdom (UK), as an example of a temperate region likely to experience at least moderate changes in climate that will require changes to the way agricultural systems operate. We summarise the projected climate changes in this region, identify the main impacts likely to affect livestock agriculture, and discuss potential adaptation options at the farm level. We also categorise the adaptation options by the types of costs they incur, emphasising that many of these options involve management changes rather than investment and therefore no financial cost. Finally, we discuss the need for longer term planning to prepare for changes that have not yet been observed. [ABSTRACT FROM AUTHOR]