Genotype and environment effects on dynamics of harvest index during grain filling in sorghum

An approach based on a linear rate of increase in harvest index (141) with time after anthesis has been used as a simple means-to predict grain growth and yield in many crop simulation models. When applied to diverse situations, however, this approach has been found to introduce significant error in grain yield predictions. Accordingly, this study was undertaken to examine the stability of the HI approach for yield prediction in sorghum [Sorghum bicolor (L.) Moench]. Four field experiments were conducted under nonlimiting water. and N conditions. The experiments were sown at times that ensured a broad range in temperature and radiation conditions. Treatments consisted of two population densities and three genotypes varying in maturity. Frequent sequential harvests were used to monitor crop growth, yield, and the dynamics of 111. Experiments varied greatly in yield and final HI. There was also a tendency for lower HI with later maturity. Harvest index dynamics also varied among experiments and, to a lesser extent, among treatments within experiments. The variation was associated mostly with the linear rate of increase in HI and timing of cessation of that increase. The average rate of HI increase was 0.0198 d(-1), but this was reduced considerably (0.0147) in one experiment that matured in cool conditions. The variations found in IN dynamics could be largely explained by differences in assimilation during grain filling and remobilization of preanthesis assimilate. We concluded that this level of variation in HI dynamics limited the general applicability of the HI approach in yield prediction and suggested a potential alternative for testing.

Rice yield estimation based on weather conditions and on technological level of production systems in Brazil

The objective of this work was to evaluate an estimation system for rice yield in Brazil, based on simple agrometeorological models and on the technological level of production systems. This estimation system incorporates the conceptual basis proposed by Doorenbos & Kassam for potential and attainable yields with empirical adjusts for maximum yield and crop sensitivity to water deficit, considering five categories of rice yield. Rice yield was estimated from 2000/2001 to 2007/2008, and compared to IBGE yield data. Regression analyses between model estimates and data from IBGE surveys resulted in significant coefficients of determination, with less dispersion in the South than in the North and Northeast regions of the country. Index of model efficiency (E1') ranged from 0.01 in the lower yield classes to 0.45 in higher ones, and mean absolute error ranged from 58 to 250 kg ha‑1, respectively.

Differences in phasic development rate amongst wheat cultivars independent of responses to photoperiod and vernalization. A viewpoint of the intrinsic earliness hypothesis

Differences amongst wheat cultivars in the rate of reproductive development are largely dependent on differences in their sensitivity to photoperiod and vernalization. However, when these responses are accounted for, by growing vernalized seedlings under long photoperiods, cultivars can still differ markedly in time to ear emergence. Control of rate of development by this ‘third factor’ has been poorly understood and is variously referred to as intrinsic earliness, earliness in the narrow sense, basic vegetative period, earliness per se, and basic development rate. Certain assumptions are made in the concept of intrinsic earliness. They are that differences in intrinsic earliness (i) are independent of the responses of the cultivars to photoperiod and vernalization, (ii) apply only to the length of the vegetative period up to floral initiation (as suggested by several authors), (iii) are maintained under different temperatures, measured either in days or degree days. As a consequence of this, the ranking of cultivars (from intrinsically early to intrinsically late) must be maintained at different temperatures. This paper, by the re-analysis of published data, examines the extent to which these assumptions can be supported. Although it is shown that intrinsic earliness operates independently of photoperiod and vernalization responses, the other assumptions were not supported. The differences amongst genotypes in time to ear emergence, grown under above-optimum vernalization and photoperiod (that is when the response to these factors is saturated), were not exclusively due to parallel differences in the length of the vegetative phase, and the length of the reproductive phase was independent of that of the vegetative phase. Thus, it would be possible to change the relative allocation of time to vegetative and reproductive periods with no change in the full period to ear emergence. The differences in intrinsic earliness between cultivars were modified by the temperature regime under which they were grown, i.e. the difference between cultivars (both considering the full phase to ear emergence or some sub-phases) was not a constant amount of time or thermal time at different temperatures. In addition, in some instances genotypes changed their ranking for ‘intrinsic earliness’ depending on the temperature regime. This was interpreted to mean that while all genotypes are sensitive to temperature they differ amongst themselves in the extent of that sensitivity. Therefore, ‘intrinsic earliness’ should not be considered as a static genotypic characteristic, but the result of the interaction between the genotype and temperature. Intrinsic earliness is therefore likely to be related to temperature sensitivity. Some implications of these conclusions for plant breeding and crop simulation modelling are discussed.

Translating climate forecasts into agricultural terms: advances and challenges

Seasonal climate prediction offers the potential to anticipate variations in crop production early enough to adjust critical decisions. Until recently, interest in exploiting seasonal forecasts from dynamic climate models (e.g. general circulation models, GCMs) for applications that involve crop simulation models has been hampered by the difference in spatial and temporal scale of GCMs and crop models, and by the dynamic, nonlinear relationship between meteorological variables and crop response. Although GCMs simulate the atmosphere on a sub-daily time step, their coarse spatial resolution and resulting distortion of day-to-day variability limits the use of their daily output. Crop models have used daily GCM output with some success by either calibrating simulated yields or correcting the daily rainfall output of the GCM to approximate the statistical properties of historic observations. Stochastic weather generators are used to disaggregate seasonal forecasts either by adjusting input parameters in a manner that captures the predictable components of climate, or by constraining synthetic weather sequences to match predicted values. Predicting crop yields, simulated with historic weather data, as a statistical function of seasonal climatic predictors, eliminates the need for daily weather data conditioned on the forecast, but must often address poor statistical properties of the crop-climate relationship. Most of the work on using crop simulation with seasonal climate forecasts has employed historic analogs based on categorical ENSO indices. Other methods based on classification of predictors or weather types can provide daily weather inputs to crop models conditioned on forecasts. Advances in climate-based crop forecasting in the coming decade are likely to include more robust evaluation of the methods reviewed here, dynamically embedding crop models within climate models to account for crop influence on regional climate, enhanced use of remote sensing, and research in the emerging area of 'weather within climate'.

Translating climate forecasts into agricultural terms: advances and challenges

Seasonal climate prediction offers the potential to anticipate variations in crop production early enough to adjust critical decisions. Until recently, interest in exploiting seasonal forecasts from dynamic climate models (e.g. general circulation models, GCMs) for applications that involve crop simulation models has been hampered by the difference in spatial and temporal scale of GCMs and crop models, and by the dynamic, nonlinear relationship between meteorological variables and crop response. Although GCMs simulate the atmosphere on a sub-daily time step, their coarse spatial resolution and resulting distortion of day-to-day variability limits the use of their daily output. Crop models have used daily GCM output with some success by either calibrating simulated yields or correcting the daily rainfall output of the GCM to approximate the statistical properties of historic observations. Stochastic weather generators are used to disaggregate seasonal forecasts either by adjusting input parameters in a manner that captures the predictable components of climate, or by constraining synthetic weather sequences to match predicted values. Predicting crop yields, simulated with historic weather data, as a statistical function of seasonal climatic predictors, eliminates the need for daily weather data conditioned on the forecast, but must often address poor statistical properties of the crop-climate relationship. Most of the work on using crop simulation with seasonal climate forecasts has employed historic analogs based on categorical ENSO indices. Other methods based on classification of predictors or weather types can provide daily weather inputs to crop models conditioned on forecasts. Advances in climate-based crop forecasting in the coming decade are likely to include more robust evaluation of the methods reviewed here, dynamically embedding crop models within climate models to account for crop influence on regional climate, enhanced use of remote sensing, and research in the emerging area of 'weather within climate'.

Apical leaf necrosis and leaf nitrogen dynamics in diseased leaves: a model study

Apical leaf necrosis is a physiological process related to nitrogen (N) dynamics in the leaf. Pathogens use leaf nutrients and can thus accelerate this physiological apical necrosis. This process differs from necrosis occurring around pathogen lesions (lesion-induced necrosis), which is a direct result of the interaction between pathogen hyphae and leaf cells. This paper primarily concentrates on apical necrosis, only incorporating lesion-induced necrosis by necessity. The relationship between pathogen dynamics and physiological apical leaf necrosis is modelled through leaf nitrogen dynamics. The specific case of Puccinia triticina infections on Triticum aestivum flag leaves is studied. In the model, conversion of indirectly available N in the form of, for example, leaf cell proteins (N-2(t)) into directly available N (N-1(t), i.e. the form of N that can directly be used by either pathogen or plant sinks) results in apical necrosis. The model reproduces observed trends of disease severity, apical necrosis and green leaf area (GLA) and leaf N dynamics of uninfected and infected leaves. Decreasing the initial amount of directly available N results in earlier necrosis onset and longer necrosis duration. Decreasing the initial amount of indirectly available N, has no effect on necrosis onset and shortens necrosis duration. The model could be used to develop hypotheses on how the disease-GLA relation affects yield loss, which can be tested experimentally. Upon incorporation into crop simulation models, the model might provide a tool to more accurately estimate crop yield and effects of disease management strategies in crops sensitive to fungal pathogens.

Uncertainty in simulating wheat yields under climate change

Projections of climate change impacts on crop yields are inherently uncertain1. Uncertainty is often quantified when projecting future greenhouse gas emissions and their influence on climate2. However, multi-model uncertainty analysis of crop responses to climate change is rare because systematic and objective comparisons among process-based crop simulation models1, 3 are difficult4. Here we present the largest standardized model intercomparison for climate change impacts so far. We found that individual crop models are able to simulate measured wheat grain yields accurately under a range of environments, particularly if the input information is sufficient. However, simulated climate change impacts vary across models owing to differences in model structures and parameter values. A greater proportion of the uncertainty in climate change impact projections was due to variations among crop models than to variations among downscaled general circulation models. Uncertainties in simulated impacts increased with CO2 concentrations and associated warming. These impact uncertainties can be reduced by improving temperature and CO2 relationships in models and better quantified through use of multi-model ensembles. Less uncertainty in describing how climate change may affect agricultural productivity will aid adaptation strategy development andpolicymaking.

CGIAR research program on grain legumes

EXECUTIVE SUMMARY Background and context The Grain Legumes CRP was established to bring all research and development work on grain legumes within the CGIAR system under one umbrella. It was set up to provide public goods outcomes to serve the needs of the sustainable production and consumption of grain legumes in the developing world, capitalising upon their properties that enhance the natural resource base upon which production so unequivocally depends. The choice of species and research foci were finalised following extensive consultation with all stakeholders (though perhaps fewer end users), and cover all disciplines that contribute to long-lasting solutions to the issues of developing country production and consumption. ICRISAT leads Grain Legumes and is partnered by the CGIAR centers ICARDA, IITA and CIAT and a number of other important partners, both public and private, and of course farmers in the developed and developing world. Originally in mid-2012 Grain Legumes was structured around eight Product Lines (PL) (i.e. technological innovations) intersecting five Strategic Components (SC) (i.e. arranged as components along the value chain). However, in 2015, it was restructured along a more R4D output model leading to Intermediate Development Outcomes (IDOs). Thus five Flagship Projects (FP) more closely reflecting a systematic pipeline of progression from fundamental science, implementation of interventions and the development of capacity and partnerships to promote and adopt impactful outcomes: FP1) Managing Productivity through crop interactions with biotic and abiotic constraints; FP2) Determination of traits that address production constraints and opportunities; FP3) Trait Deployment of those traits through breeding; FP4) Seed Systems, post-harvest processing and nutrition; FP5) Capacity-Building and Partnerships. Another three cross-cutting FPs analyse the broader environment surrounding the adoption of outputs, the capitalising of investments in genomics research, and a focus on the Management and Governance of Grain Legumes: FP6) Knowledge, impacts, priorities and gender organisation; FP7) Tools and platforms for high throughput genotyping and bioinformatics; and FP8) Management and Governance. Five FPs focus on R4D; FPs 5 and 6 are considered cross-cutting; FP 7 has a technical focus and FP 8 has an overarching objective. Over the three year period since its inception in July 1012, Grain Legumes has had a total budget of $140 million, with $62M originally to come from W1/W2 and the remaining $78M to come from W3/bilateral. In actuality only $45M came from W1/W2 but $106M from W3/bilateral corresponding to 106% of expectation. Purpose, scope and objectives of the external evaluation Principally, the evaluation of Grain Legumes is to ensure that the program is progressing in an effective manner towards addressing the system-level outcomes of the CGIAR as they relate to grain legumes. In essence, the evaluation aims to provide essential evaluative information for decision-making by Program Management and its funders on issues such as extension, expansion and structuring of the program and adjustments in relevant parts of the program. Subsequent to the formal signing of the agreed terms of reference, the evaluation team was also invited to comment upon the mooted options for merging and/or disaggregating of Grain Legumes. The audiences are therefore manifold, from the CGIAR Fund Council and Consortium, the Boards of Trustees of the four component CGIAR centres, the Grain Legumes Steering, Management and Independent Advisory Committees, to the researchers and others involved in the delivery of R4D outcomes and their partner organisations. The evaluation was not only summative in measuring results from Grain Legumes at arm’s length; it was also formative in promoting learning and improvements, and developmental in nurturing adaption to transformational change with time. The evaluation report was written in a manner that allows for engagement of key partners and funders in a dialogue as to how to increase ownership and a common understanding of how the goals are to be achieved. We reviewed research undertaken before the CRPs but leading to impacts during Grain Legumes, and research commenced over the past 2.5 years. For related activities pre- and post-commencement of Grain Legumes, we reviewed the relevance of activities and their relation to CGIAR and the Grain Legumes goals, whether they were likely to lead to the outcomes and impacts as documented in the Grain Legumes proposal, and the quality of the science underpinning the likelihood to deliver outcomes. Throughout, we were cognisant of the extent of the reach of CGIAR centres’ activities, and those of stakeholders upon which the impact of CGIAR R4D depends. Within our remit we evaluated the original and modified management and governance structures, and all the processes/responsibilities managed within those structures. Besides the evaluation of the technical and managerial issues of Grain Legumes, we addressed cross-cutting issues of gender sensitivity, capacity building and the creation and nurturing of partnerships. The evaluation also has the objective to provide information relating to the development of full proposals for the new CRP funding cycle. The evaluation addressed six overarching questions developed from the TOR questions (listed in the Inception Report, 2015 [http://1drv.ms/1POQSZh] and others including cross-cutting issues, phrasing them within the context of traditional evaluation criteria: 1. Relevance: Global development, urbanisation and technological innovation are progressing rapidly, are the aims and focus of Grain Legumes coherent, robust, fit for purpose and relevant to the global community? 2. Efficiency: Is the structure and effectiveness of leadership across Grain Legumes developing efficient partnership management and project management across PLs? 3. Quality of science: Is Grain Legumes utilising a wide range of technologies in a way that will increase our fundamental understanding of the biology that underpins several PLs; and are collected data used in the most effective way? 4. Effectiveness: Are Product Lines strategic contributors to the overarching aims and vision for Grain Legumes? 5. Impact: Are the impact pathways that underlie each PL well defined, measureable and achievable; and are they sufficiently defined in terms of beneficiaries? Does progress towards achieving outputs and outcomes from the major research areas indicate a lasting benefit for CGIAR and the communities it serves? 6. Sustainability: Is Grain Legumes managing the increasing level of restricted funding in terms of program quality and effectiveness, including attracting and retaining quality staff? Questions for the evaluation of governance and management focused on accountability, transparency, the effectiveness and success of program execution, change management processes and communication methods, taking account of the effects of CGIAR reform. The three crosscutting issues were considered as follows: i) gender balance in program delivery, e.g. whether each PL is able to contribute to the increased income, food security, nutrition, environmental and resource conservation for resource-poor women and men existing in rural livelihoods; ii) are internal and external capacity gaps identified/met, is capacity effectively developed within each product line, and are staff at all levels engaged in contributing ideas towards capacity building; and iii) is there effective involvement of partners in research and activity programming, what are the criteria for developing partnerships, how they are formalised and how is communication between partners and within Grain Legumes managed? It was not in remit to search for output, outcomes or impact, however as highlighted later, much of our time was spent on searching for information to support claims of impact, since Grain Legumes had no effective dedicated M&E in place at the time of undertaking the review. Approach and methodology The evaluation was conducted when Grain Legumes had been operational for approximately 3 years. The approach and methodology followed that outlined in the Inception Report [http://1drv.ms/1POQSZh]. The CCEE Team based its findings, conclusions and recommendations on data collection from several sources:  review of program documents, communications with the CO, minutes and presentations from all management and governance committee meetings  review of previous assessments and evaluations  sampling of Grain Legume projects in 7 countries1  more than 66 face to face interviews, a further 133 persons in groups and 4 phone/Skype conversations: ICRISAT, ICARDA, CIAT and IITA staff, partners and stakeholders. Meetings with one Independent Science and Partnership Council (ISPC) member.  meetings with over 100 people in 16 external groups, such as farmers’ groups  online survey completed by 126 (33.4%) scientists who contribute to Grain Legumes and a number of non-CGIAR partners and Management representatives  bibliometric review of 10 publications within each PL to qualitatively assess the design, conduct, analysis and presentation of results  quantitative and qualitative self-assessment of the contributions of each of the PLs to the six criteria and 3 cross-cutting issues of evaluation mentioned above completed by PLCs (see below). We reviewed the Logical Framework that underpins the desired Goals, or Impacts of Grain Legumes, and the links between the outputs and inputs as they related to the organisational units of Grain Legumes. The logical framework approach to planning and management of Grain Legumes activities implies a linear process, leading from activities, outputs, outcomes, to impacts, but within such an approach there may be room for a more systems dynamics approach allowing for feedback at every step and within every step, in order to refine and improve upon the respective activities as new results, ideas, and directions come to light. We then developed a matrix that summarised quantitatively and qualitatively the contributions of each of the PLs to the six criteria and 3 cross-cutting issues of evaluation mentioned above. Main findings and conclusions Grain legume production and consumption remain of great importance to the food security of not inconsiderable populations in the developing world, and merit sustained research investment. We conclude that Grain Legumes continues to contribute significant returns to research investments by the CGIAR, and such investment should continue. The global research community looks to the CGIAR for leadership in Grain legumes, but needs to be assured of value adding when bringing CGIAR centres under the expected umbrella of synergy. However, there is considerable scope for improving the efficiency with which outcomes are achieved. We note that an absence of an effective M&E has hampered the assessment of the effectiveness of proposed impact pathways. Likewise progress has been hampered by the limited numbers of research partnerships with Advanced Institutes and by budgetary constraints (lamented for their stifling effects on continuation of ongoing exciting research). The unworkable management structure constrains the CRP Director’s leadership role; responsibility without authority will never lead to effective outcomes. Good fortune is responsible for many of the successes of Grain Legumes, underpinned by a devoted work force across the participating CGIAR centres and partners. The quality of the science is not uniformly high, and we believe that mentoring of scientists should be given priority where quality is poor. Simplified yet informative reporting is an imperative to this. World class science underpins the identification of, and molecular basis for, traits important for yield improvement and this expertise should be extended to all grain legume species, capitalising upon the germplasm collections. The linking of Grain Legumes with regional research and development consortia has been very successful, with outcomes aligning with those of Grain Legumes. We see that with declining funding consolidation of research effort based on likely successes will be necessary, and welcome the move afoot to incorporate grain legumes into an agri-food system focused on successful value chains that deliver sustainable outcomes. Relevance and Strategy Grain Legumes has geographic and disciplinary relevance, addressing the major supply chain issues of variety development seed system and agronomy, with some attention to quality and postharvest marketing systems. The CRP has provided the opportunity to cut ongoing and to initiate new research. Research funded by the Gates Foundation (Anon, 2014) suggests that the need for improvement is greatest in Africa and advocates reducing the number of crop by country combinations when resources are sparse. The lesser research investment in Latin America, however, is not in line with the regions’ dependency on legumes. In spite of the fact that there is no evidence of strong inter-partner CGIAR centre or internal synergy, the program is still moving ahead on most fronts in line with the overall project logframe. This is in spite of continual pushing and pulling by in particular donors and the CO. However, to quantify real impact, we believe Grain Legumes must have access to reliable baseline data on production and consumption, and this is missing. Similarly, there is little evidence of the proposed ‘Inclusive Market Oriented Development’ (IMOD) framework being used to assist with priority setting. The product lines, eight of which cover most of the historical programmes in place in the partner CGIAR centres at the commencement of the Grain Legumes, do not cover all the constraints for formal constraints analysis was not undertaken at the inception of the Grain Legumes, and some of this additionally identified research is undertaken under the umbrella of the FPs; this needs to be rationalised. We found the PLs to be isolated in activity, even with minimally-integrated activities within each PL, with little evidence of synergy between PLs. Even though the SCs should ensure a systems approach, as with the new FPs, we did not get a feel that this is so. The underplaying of agronomy, and production practices may be one reason for this. We believe that treating legume crops as if they were horticultural crops will increase farmer returns from investment. The choice of Flagship Projects makes sense, with the flow of activity firstly around crop management and agronomy followed by the logical sequence of trait discovery, incorporation into improved varieties, dissemination of those varieties through appropriate seed chains leading to market impacts, and the capacity building required at all steps. One obvious omission, however, is the lack of a central and strategic policy on the role of transgenics in Grain Legumes. We found four notable comparative advantages for Grain Legumes: the access to germplasm of component species, the use of the phenotyping facility at ICRISAT, the approach for village level industry for IPM, and the emphasis on hybrid pigeonpea. Efficiency Each centre has strong control of, and emphasis on, their ‘species’ domains, and ownership of the same detracts from possible synergy. Without synergy or value add, the Grain Legumes brings with it no comparative advantage over each centre continuing their own pre-CRP research agendas. We found little evidence of integration of programmes between centres and almost no cross-centre authorship of publications, such as could have occurred with the integrated cross-centre approaches to stress tolerance including crop modelling: the one publication (Gaur et al., 2015) on heat tolerance by ICRISAT, CIAT and ICARDA does not provide any keys to inter-centre collaboration. The integration of each centre with NARS and university research programmes is good, but the cross-centre links with NARS are poor. A better coordinated integration with Grain Legumes, , rather than through the individual centres, may reduce transactions costs for NARS, Monitoring and evaluation is, as noted throughout our report, one area of Grain Legumes research management that has not been given the attention it should have received. If it had have received proper attention, some of the issues of poor efficiency might have been nipped in the bud. A strong monitoring and evaluation system would have provided the baseline data and set the milestones that would have allowed both efficiency and effectiveness to be better appraised. We found no attempt to define comparative advantages of the CGIAR centres and their R4D activities, although practice showed the better grasp of CIAT in developing innovative seed distribution systems. During field visits and interviews, the CCEE Team observed shortcomings in the communication processes within Grain Legumes and with the broader scientific community and the public. For example, the public face of the program on the internet is out of date. Survey findings, however, suggest that information is shared freely and routinely within the PL within which scientists work. Some external issues, such as those with funding, low W1/W2 and poor sustainability of funding (especially if funding is top heavy with a few agencies), undermine research investment and confidence of partners in the system (e.g. as voiced by researchers working on crops and countries not included in TL III and the cessation of ongoing competitively-funded projects especially in India), but other issues attributable to the governance and management of the Grain Legumes, such as opaque integration of W3/bilaterals with W1/W2 funding require attention. Offsetting this, the existence of the Grain Legumes did mobilise additional funding [that it would not have if Grain Legumes did not exist]. We were concerned that Grain Legumes is simply not recognised outside of the CRP, with a limited www presence and centres promote themselves, rather than Grain Legumes (with exception in IITA). This is not a good move if one wishes to increase investment in the Grain Legumes. Although funding agencies require cost:benefit ratios, for example for each PL we faced difficulty in determining comparative value for money between investment in different types of research, and in being able to clearly attribute research and development outcomes to financial investment. There was also a time CCEE frame issue too. There is poor interaction with the private sector, notably in areas where they have a comparative financial advantage. We questioned in particular the apparent lack of interaction with the major agro-chemical companies, with respect to the development of herbicide tolerant (HT) grain legumes and the lack of evidence that the regulatory and trade aspects related to herbicide tolerant crops had been considered. Quality of science The quality of the science is highly variable across Grain Legumes, with pockets of real excellence that are linked to good levels of productivity, whereas other PLs are struggling to deliver quality publications, and outputs and outcomes that are based on these. There is much evidence of gradualism in terms of research output and outcomes, i.e. essentially the same activities that were ongoing at the time of the launch of Grain Legumes are still in place. However, there are examples of game changers including those from valuable investments in genomics, phenotyping, and bio-control. We were pleased to see large proportions of collaboration on publications with non-CGIAR centres, reflecting cooperation with partners in developed and developing countries. The value of collaboration when ensuring quality of science cannot be stressed highly enough both within the CRP, and with other global and national partners. PLs should be given incentives to collaborate with other CRPs and external institutions. There is little cohesion between PLs and with other CRPs as evidenced by publications, although there are some exceptions. We suspect the reasons for this are driven by funding. Productivity from the different PLs is also highly variable and it is not clear what other activities staff are engaged in since, in some PLs, they do not appear to lead to quality publications. Effectiveness Grain Legumes has been very effective in addressing component issues of research, but not the continuum from variety development to legumes on someone’s dinner plate. Our overall assessment of the effectiveness of Grain Legumes in stimulating synergy, innovation and impact indicate that gradualism is more prevalent than innovation. It also shows, as do publications, that there is little integration of disciplines or a focus on ‘systems’. The absence of socio-economists from research teams is evident in the general lack of an end user focus. However, research on genomics, plant breeding and seed systems have made great strides forward, on the brink of delivering impact. Agronomy has been a poor sister, but some of the competitive grants within Grain Legumes have unearthed some potential game changers, such as objective use of transplanting as an agronomic practice. As mentioned earlier, the lack of effective M&E (however, this was part of some major projects such as TL II/TL III), and therefore the ability to monitor impact pathways and achievement of impact, implies no systematic management of data. This creates difficulty when attempting to evaluate the achievement of the Grain Legumes objectives. One might have expected at least one attempt to try to develop publications between centres arguing for similar biologies/research approaches, bringing species together under one umbrella, but we did not find any evidence for this. It is most unfortunate that, due to budgetary cuts, the new ‘schemes’, e.g. competitive grants and scholarships, were cut off before gaining a foothold. With 8 species addressed by Grain Legumes, it is not unexpected that there will be little evidence of shared protocols across centres/species. One rare example was that hosted by the United States Department of Agriculture (USDA) on shared methods for phenotyping of legume germplasm. Researchers from CIAT, IITA, ICRISAT and three USDA stations attended, focusing in simple canopy temperature and root morphology measurements. It is our belief that as a set of research centres, the CGIAR centres should be focusing on the research for which they have a comparative advantage. While imposing the restructure to FPs, which is fine for development objectives and outcomes (funded through W3/bilateral), it is less so for a research institute, and the structure should not detract from the more basic work expected of an international CGIAR centre (or set of centres as in a CRP). Impact It is well known that research does not always lead to scientific breakthroughs. Also, activities such as plant breeding are long term; making impacts difficult to assess. We believe that sufficient progress with genomics and associated research has been made to warrant impact, but we are unable to quantify the levels of impact, or the timeframe for the same. Work in Grain Legumes has enormous potential for real impact in scientific research, commercial, farming, smallholder and household communities, much of which is being realised. However, the PLs need to become more adept at providing convincing cases that are strongly evidenced for these impacts, as this is likely to be a key factor in leveraging future funding. Claimed gains must be referenced against baseline data, and these are not always readily available. The CCEE Team realises that such impact evaluation represents a significant drain on resources, and Grain Legumes should determine whether the balance of costs to benefits favours such investment. Interviews conducted by the CCEE during site visits showed that PLs are quantifying the area of adoption of varieties, but in most cases they are not measuring the impact on environment, health/nutrition. Since the health and nutritional benefits and the environmental gains from growing legumes are major arguments for supporting grain legume research, the community is currently missing substantial opportunities to strengthen its own case for continued support. Whilst there are some impressive examples of considering the whole value chain, e.g. white beans from production through to export; in the main, the pipeline to end user is somewhat piece-meal, with no clear definition of the end user nor differential responsibility of Grain Legumes and of partners. The lack of robust time-defined impact pathways is highlighted in Section 7.4, and even though developed for PL5, timeframes are essential for measuring progress against prediction. Sustainability In summary, there is general acknowledgement that future funding is likely to become more limited, specifically in W1&2 and there is understandable concern over the support for the staff and basic infrastructure that underpin the Grain Legumes programme. For example, it is reported that staffing in parts of CIAT has been dependent on W1&2 and that this is too unstable to re-establish a critical mass. The present system whereby W3 and bilateral projects do not pay a realistic level of overheads means that such projects are being effectively subsidised by W1&2. This position is not sustainable in the long term as there will be a progressive but definite loss of basic skills and resources in the core centres. The only obvious options to prevent this outcome include a severe reduction in the fixed costs of the centres and/or a refusal to accept W3 and bilateral funding with an inadequate overhead component. In the latter case, there is an obvious danger that funders will move their resources away from the CGIAR system towards other, perhaps less expensive, suppliers of research, and possibly more relevant development expertise. This issue must be addressed. As the Grain Legumes moves into the future, and if sustainable funding cannot be assured, decisions must be made concerning a reduction in activities, keeping some caretaker breeding maintenance, and focus (as has TL III) on fewer species and a reduced geographic focus. Cross cutting issues: Gender, capacity building and partnerships Gender is not mainstreamed, but there is some evidence that this is improving, especially with dedicated gender specialists and the slow integration of gender across CRPs. There is a need to approach gender through the vision of agriculture as a social practice, with recognition of what changes will be acceptable culturally and what not, and capitalising upon the perceived and actual features of production and processing that grain legumes are primarily women-based crops. Gender awareness may be high among Scientists, but it appears to be a predominantly passive attribute with few proactively seeking opportunities for gender equity. It is, however, a sound sensitivity base on which to build. Nevertheless, examples of notable gender initiatives were identified during field visits. For example, in Benin, the development of biocontrol technologies has enthusiastically integrated diversity, engaging with women farmers’ and youths while maintaining cultural norms. Women are gathering and processing, youths are taking the product to market. The implication is that several groups benefit, rather than domination by the majority group. In Malawi, innovative approaches have been developed to improving nutrition for children, such as incorporating nutrient enriched bean flour products into snacks. In India, scientists collaborating with gender scientists and socio-economists are identifying the impact of mechanical harvesting on agricultural labour and the potential displacement of female labourers. In Kenya, a novel initiative is improving the accessibility of certified seed for new varieties. Seed suppliers have introduced small packs of grain legume seed at low unit cost, which are being purchased by young people and women. Capacity building efforts for external partners are not clearly aligned with the research mandate and delivery of Grain Legumes. However, there are a number of training activities that are being undertaken by Grain Legumes, largely through the W3/bilateral project. Gender balance never reaches parity, but it appears that efforts are made to include female participants. Within the evaluation timeframe it was not possible to conduct external surveys to further validate or review external capacity building efforts in Grain Legumes. Training of scientists is significant, with >40 benefiting. Postgraduate training is varied across PLs, and there is some opportunity to increase the numbers being supervised. We consider that support for postgraduates at ICRISAT could be better coordinated, satisfying more of the students’ needs. It is important, however, to follow up investments in capacity building by monitoring effectiveness, career progressions and so on. Training activities appear to be rather centre-specific, not following a coordinated programme managed by, nor at the level of, the Grain Legumes. Numbers of persons trained and their gender are important, but a measure of the effectiveness of the training is more important. Although optimism is expressed by the great majority of Research Managers that partnerships were working well to leverage knowledge and research capacities, scientists have a less favourable view, particularly in terms of their incentives to participate. It seems likely that the activities taking place within Grain Legumes were, in the most part, continuations of previous collaborations. This is not surprising in light of the reduction in the emphasis on partnerships as Grain Legumes evolved to a funded project, and the consequent lack of opportunity and ambition for establishing novel partnerships. Where they exist, partnerships are good on the whole, especially with US. They could be expanded where comparative advantages exist (for example with Canada and Australia for machine harvestable legumes), but some earlier identified partnerships, e.g. with Turkey, have not been capitalised upon. Others experience problems of variety access (the embargo on exports of some sources of materials from India), yet others do have relevance e.g. imported Brazilian varieties in pre-release in Ethiopia (even though two of the three are from CIAT materials). Governance and Management The standard format of committee structure and responsibilities is common to other CRPs, as are the attendant problems. One of the major problems is that the Grain Legumes Director has responsibility but no authority; hence, even with the support of the RMC, the Director is unable to ‘direct’ in the literal sense of the work the activities of Grain Legumes. We also see the same sense of helplessness with the role of the PLCs. They have responsibility but no authority in managing the affairs of their PL, and they have no access to funds with which to promote intellectual collaboration and cooperation. Minutes from governance and management meetings do not reflect the compromised weak position of the Director and the associated difficulties in the management of Grain Legumes. Nor do the minutes reflect concerns about the amount of time spent by scientists in meetings for planning, integration, evaluation and reporting. Many scientists reported significant opportunity costs in participating in the ongoing imposed [by the CO] evolution of Grain Legumes and CRPs in general. The changes brought in by the CO have not helped promote any greater authority and capacity of the Grain Legumes Director to direct. Likewise, they do not address any of the issues with the conflict of interest in having the Lead Centre chair the Steering Committee. Indeed, we believe that the combining of the Steering Committee with the Independent Advisory Committee, besides becoming unwieldy in number, annuls any sense of independence in advice offered to the Grain Legumes management. We have concerns with the declining proportion of W1/W2 funds (as expressed in the section on Sustainability), and believe that when basic financial planning takes place, integration of W1/W2 and W3/bilateral sources must occur, and be linked to anticipated outcomes and impacts. This will ensure a close alignment of collaborators’ and partners’ objectives and contributions to that of the Grain Legumes. We also queried the process for, and the formality, or lack of, surrounding, the approval of annual budgets, and the level of priority setting when budgets are cut. Recommendations for Grain Legumes The CCEE Team makes the following recommendations, critical issues are highlighted in bold, and those that require action by an entity other than the Grain Legumes Research Management Committee or Project Management united are identified in a footnote. Relevance and Strategy Recommendation 1: A period of consistency is necessary to raise confidence, morale and trust across scientists, managers and partners to foster the assembly of enduring Grain Legumes outcomes2.  There needs to be a concerted effort to undertake baseline studies and to implement a robust M&E activity during this period. Without these data the foundation for integrated research in grain legumes is jeopardised.  There is a strong need to link more closely with the private sector, especially where there are financial and other comparative advantages to do so. Recommendation 2: The agronomic and physiological trait targets of Grain Legumes (tolerance to changing climate patterns, to the pests and diseases of today and of the future, incorporation of quality traits and adaptations to intensive production systems [machine-harvestability and herbicide tolerance], and short season high yielding characters) are all worthy of continued investment when selecting for improved varieties.  There needs to be a common strategy, implemented across centres and species, as to how to address these trait targets through conventional and modern breeding approaches, but only if adequate funding is assured and secured and if a consistency and unity of purpose can be achieved across a large-scale. This should take the form of cross-species coordinated research programmes to address these breeding targets that cooperate across centres and make efficient use of facilities and other resources.  The CRP should undertake a detailed strategic review of the role of transgenics across the range of targets in the mandate crops. Efficiency Recommendation 3: The lack of an effective M&E process is a significant omission, not least in terms of more efficient use of resources and the lack of baseline data with which to measure impact, and must be rectified.  Reinforcing Recommendation 1, an effective M&E system initially directed towards baseline studies must be implemented.  Transaction costs may be reduced through bilateral projects, which are seen as more cost effective than W1/W2 where transaction costs are disproportionately higher. Recommendation 4: To improve communication and coordination within the CRP, and with a broader audience:  There is a priority need for a central database containing, names of staff associated with Grain Legumes and their time commitments, their responsibilities, and involvement in CRP activities, their progress and achievements, their publications, plans of training, travel, and other opportunities for interaction.  Regular global meetings of staff involved in managing PLs, the entire CRP management staff and the IAC are essential for effective coordination of all activity within Grain Legumes.  The website must be given a complete overhaul and improvement and then regular maintenance must be provided to keep it current. Quality of Science Recommendation 5: It is essential to continue investment in good science and to institute a change from gradualism in research output and outcomes to an expectation of innovative and concrete achievements that can be attributed clearly to people, centres and core facilities.  A cost:benefit analysis and subsequent strategic planning must be undertaken to justify further investment in the genomics and phenotyping facilities at ICRISAT especially as such technologies advance rapidly. Strategic planning and coordination must also be implemented for capitalising on the investment in crop simulation modelling. (The phenotyping facility of ICRISAT needs to focus on delivering some outcomes, not only outputs.)  PLs should be given incentives to collaborate with other CRPs and external institutions. The CCEE recommends special recognition of high quality collaborative papers, thereby encouraging increased quality of the research programmes and widening the penetration of research impacts.  More importance should be placed on the quality of publication, rather than quantity of outputs and there should be recognition of other types of outputs from Grain Legumes. The CRP Director must be party to this.  If staff are engaged in activities that relate more to impact than publication then this needs to be monitored and recorded and a clearer understanding developed of what constitutes a pathway to impact and how success of such activities can be evaluated. A system must be devised and incorporated into the M&E to enable recognition of other types of outputs (non- publication based) from Grain Legumes, e.g. varieties for breeders. Effectiveness Recommendation 6: To develop greater synergy, Grain Legumes should review management processes and the direction of research activities. In particular, far more extensive integration of research and knowledge exchange should take place across both African and Asian continents so that the best aspects of both can be shared. A multidisciplinary approach is recommended that considers processing solutions, as well as breeding solutions, to capitalise upon the nutritional benefits of the grain legume crops. We recommend:  A better collaboration with social scientists at the design stage of experiments in order to improve the utility of the work carried out and to understand its reach.  Supporting3 the adoption of best practice electronic data collection, central storage and open access, particularly of genomic data, for public use.  Given the focus on the link between phenotyping and genotyping, we note that there is a lack of congruence between the populations that are being phenotyped and those being genotyped, and therefore these could be better aligned within each species.  Concentrating investment external to Grain Legumes on scaling up production of varieties with the most promising trait profiles to meet the basic seed requirement.  Developing a more holistic approach that coordinates an understanding of the disease pathology and epidemiology, and of new chemicals before they become commercially available, together with agronomic practice such that recommendations can be made for growers. Continuing work to establish whether agronomic factors hold true in different environments and to assess GxE effects within breeding programmes. Such rigorous trial practices should be used to inform the evaluation of breeding lines and to provide phenotype data to associate with markers for traits such as heat, drought and herbicide tolerance.  Considering grain legumes as if they were vegetable crops in terms of the strategy for intensification of production, both from the management perspective and for seed systems, will be a useful development objective into the future. This will bring about more rapid intensification and is likely to increase farmer returns from investment. Recommendation 7: The CGIAR centres should focus in on the research for which they have a comparative advantage. While imposing the restructure to FPs, which is fine for development objectives and outcomes (funded through W3/bilateral) it is less so for a research institute, and should not detract from the more basic work expected of an international CGIAR centre (or set of centres in a CRP).  Collaborative approaches should be explored within Grain Legumes, e.g. similar biologies/research approaches, bringing species together under one umbrella. Similarly better alignment is needed to address the lack of congruence between the populations that are being phenotyped and those being genotyped.  Despite positive impacts from research in genomics, plant breeding and seed systems, the lack of an effective M&E, already mentioned elsewhere, has reduced the ability to monitor impact pathways. This must be addressed.  The absence of socio-economists from research teams is evident in the general lack of an end user focus. Responsibilities of the different actors in the whole value chain must be considered and identified when developing impact targets, and the pathway leading to them, for individual projects. People with socio-economist skills must be part of the team from project inception so that appropriate frameworks are incorporated for measuring and influencing sociological and economic changes brought about by Grain Legumes research. Impact Recommendation 8: PLs need to become more adept at providing convincing cases in which impact is strongly evidenced, as this is likely to be a key factor in leveraging future funding.  Claimed gains must be referenced against baseline data, and these are not always readily available. The CCEE Team realises that such impact evaluation represents a significant drain on resources, and Grain Legumes should determine whether the balance of costs to benefits favours such investment.  It is essential that Grain Legumes provides training to staff on what constitutes impact and how it can be recorded.  Specific, rather than generalised, potential impacts arising from activity within Grain Legumes should be defined at the time of justifying the programme of work and a pathway to impact should form part of the documentation prepared ahead of a piece of research commencing. . In other words, centres should submit work plans to Grain Legumes before they are undertaken using W1/W2 funds Recommendation 9: The reporting activity must be streamlined to a single (brief) format that can be used to report to Grain Legumes, Centres and to donors for special project activities4. Sustainability Recommendation 10: As Grain Legumes moves into the future, and if sustainable funding cannot be assured, decisions must be made concerning a reduction in activities, keeping some caretaker breeding maintenance, and focus (as has TL III) on fewer species and a reduced geographic focus. Zeigler (Director General of IRRI) states “…time and effort would be better spent … making tough decisions about which programs deserve the precious support.”  The present system whereby W3 and bilateral projects do not pay a realistic level of overheads means that such projects are being effectively subsidised by W1&2 and there will be a progressive but definite loss of basic skills and resources in the core centres. To prevent this outcome it is necessary to significantly reduce the fixed costs of the centres and/or refuse to accept W3 and bilateral funding without an adequate overhead component.  In the absence of long term certainty, the scale of the budget allocated to each of the new CRPs should be very conservative, a feature that can only be achieved by restricting/reducing the scope, probably quite significantly. Cross cutting issues: Gender, capacity building and partnerships Recommendation 11: The challenge for Grain Legumes is to achieve pro-active gender mainstreaming, which facilitates opportunities for gender diversity within all activities, from employment processes through research to end users.  Strategic measurable gender indicators need to be embedded in research design, for instance, through specific IDOs for each of the flagships projects. Accurate baseline data are also required to facilitate M&E reviews of progress.  Implementation of the Gender Strategy is the responsibility of everyone, not solely the Gender Team. Thus, ownership could be encouraged by setting personal development for key personnel objectives with specific outcomes, e.g. employment practices or research outcomes.  Recognising the positive gender initiatives in progress or planned, feedback must be communicated and integrated into broader research planning to share opportunities, methods and outcomes.  In addition to promoting gender equity in research, Grain Legumes also needs to ensure that working environments are gender sensitive and that recruitment processes, including promotion opportunities are equitable. Gender imbalance in management should be actively examined to identify further opportunities for developing female leadership. Recommendation 12: It is recommended that a training plan be devised to ensure that capacity building efforts are more clearly aligned with the research mandate, delivery and timeframe of Grain Legumes. Moreover, we recommend that ICRISAT develop a strategy to treat their new cohort of researchers more equitably in the future. Recommendation 13: To develop a more coherent strategic programme designed to eliminate overlap and promote synergy between programmes with common aims, Grain Legumes should hold a meeting with a range of partners. Governance Recommendation 14: Governance processes should be re-assessed and the structure altered to ensure that the Grain Legumes Director has the authority and budget control to drive the execution of strategy.  The ISC should be truly independent and given the power to influence strategic decisions before they become final. We also recommend that PLCs are provided with the authority to manage the direction and finances of their PL; and that ring-fenced funds are provided for the promotion of collaboration, coordination and staff training5. The way ahead In our view, having seen the ineffectiveness of much of the attempts [or lack of attempts] to harness synergies between multiple centres, and of the strength in few or sole centre partnerships, we believe that there is little to justify a full retention of the 8 legume species and 4 CGIAR centres in a CRP. TL I and II and PABRA have shown to be reasonably good cross-centre and single centre integrated programmes, but even they suffer from incomplete value chain approaches to increasing rural incomes while increasing food and nutritional security; they both need multi-faceted solutions which are not immediately forthcoming from Grain Legumes. It is important to embed Grain Legumes research within the agri-food systems these crops serve. Figure ES1 broadly shows the perceived current and potential degrees of synergy between centres, PLs and species, and is discussed more in the text. It is clear that the value chains for individual species from trait determination to nutritional impact have more cohesion than do the individual activities (e.g. trait deployment) across species. For this reason we believe that the future for research in Grain Legumes is best addressed by focusing on each of the species separately, and within an ecosystem framework; any synergy for research across species can be effected through communication and not necessarily through obligatory cooperative research. The ecosystem framework will allow for strengthening of agronomy type systems research, the arguments for benefits of inclusion of grain legumes in cropping systems, which is notable by its absence in much of what Grain Legumes currently undertakes. Figure ES1. Current and potential degrees of synergy between centres, PLs and crop species We therefore agree with the innovation in agri-food systems approach of the CG, and believe that Grain Legumes rightly belongs in the Dryland Cereals and Legumes Agri-food Systems. We believe that the option of combining the crops of dryland cereals and legumes in the cereal-legume-livestock systems of subsistence farming communities for whole-farm productivity is closest to the best way forward. Indeed the inclusion of grain legumes may not warrant even a CRP alone, rather the legume components should fit in with the major crops that determine the production systems. Legumes will always be subservient to the major cereals, as necessary adjuncts to the whole production system, providing both nutritional diversity and environmental services, neither achievable from cereals alone. Figure ES2. Most suitable option for integration of Grain Legumes and Dryland Cereals into an Agri-Food Systems CRP Most suitable option for integration of Grain Legumes and Dryland Cereals into an Agri-Food Systems CRP, which  Incorporates ex-Dryland Systems, Dryland Cereals, Grain Legumes, some HumidTropics, some ex-Livestock &Fisheries into a new CRP  Will cover full agri-food system VC for all 8 legumes in all ecologies, but must interact (dock) with the relevant AFS-CRPs for the dominant cereal in the relevant ecology  Hence, will need to negotiate with other Agrifood Systems-CRPs on who does what for legumes  In addition, responsible for sorghum and millet in the mixed dryland crop-livestock agro-ecologies For major game changers to be effected, we believe that the game has to change, and there is little evidence of this. The direction of CRPs is the correct route, but the journey has not yet come to its destination. A major change of game [such as the adoption of a Flagship Project approach as exemplified by the Australian CSIRO – where flagships contract services from centres of research excellence] would be painful to implant. The CGIAR system is going down the right pathway but it has not gone far enough.

Impacts of projected maximum temperature extremes for C21 by an ensemble of regional climate models on cereal cropping systems in the Iberian Peninsula

Crops growing in the Iberian Peninsula may be subjected to damagingly high temperatures during the sensitive development periods of flowering and grain filling. Such episodes are considered important hazards and farmers may take insurance to offset their impact. Increases in value and frequency of maximum temperature have been observed in the Iberian Peninsula during the 20th century, and studies on climate change indicate the possibility of further increase by the end of the 21st century. Here, impacts of current and future high temperatures on cereal cropping systems of the Iberian Peninsula are evaluated, focusing on vulnerable development periods of winter and summer crops. Climate change scenarios obtained from an ensemble of ten Regional Climate Models (multimodel ensemble) combined with crop simulation models were used for this purpose and related uncertainty was estimated. Results reveal that higher extremes of maximum temperature represent a threat to summer-grown but not to winter-grown crops in the Iberian Peninsula. The study highlights the different vulnerability of crops in the two growing seasons and the need to account for changes in extreme temperatures in developing adaptations in cereal cropping systems. Finally, this work contributes to clarifying the causes of high-uncertainty impact projections from previous studies.

Simulating improved combinations tillage-rotation under dryland conditions.

The adequate combination of reduced tillage and crop rotation could increase the viability of dry land agriculture in Mediterrenean zones. Crop simulation models can support to examine various tillage-rotation combinations and explore management scenarios. The decision support system for agrotechnology transfer (DSSAT) (Hoogenboom et al., 2010) provides a suite of crop models suitable for this task. The objective of this work was to simulate the effects of two tillage systems, conventional tillage (ConvT) and no tillage (NoT), and three crop rotations, continuous cereal (CC), fallow-cereal (FallowC) and legume-cereal (LegumeC), under dry conditions, on the cereal yield, soil organic carbon (SOC) and nitrogen (SON) in a 15-year experiment, comparing these simulations with field observations.

AquaData and AquaGIS: Two computer utilities for temporal and spatial simulations of water-limited yield with AquaCrop.

The crop simulation model AquaCrop, recently developed by FAO can be used for a wide range of purposes. However, in its present form, its use over large areas or for applications that require a large number of simulations runs (e.g., long-term analysis), is not practical without developing software to facilitate such applications. Two tools for managing the inputs and outputs of AquaCrop, named AquaData and AquaGIS, have been developed for this purpose and are presented here. Both software utilities have been programmed in Delphi v. 5 and in addition, AquaGIS requires the Geographic Information System (GIS) programming tool MapObjects. These utilities allow the efficient management of input and output files, along with a GIS module to develop spatial analysis and effect spatial visualization of the results, facilitating knowledge dissemination. A sample of application of the utilities is given here, as an AquaCrop simulation analysis of impact of climate change on wheat yield in Southern Spain, which requires extensive input data preparation and output processing. The use of AquaCrop without the two utilities would have required approximately 1000 h of work, while the utilization of AquaData and AquaGIS reduced that time by more than 99%. Furthermore, the use of GIS, made it possible to perform a spatial analysis of the results, thus providing a new option to extend the use of the AquaCrop model to scales requiring spatial and temporal analyses.

Simulating improved combinations tillage-rotation under dryland conditions.

Crop simulation models allow analyzing various tillage-rotation combinations and exploring management scenarios. This study was conducted to test the DSSAT (Decision Support System for Agrotechnology Transfer) modelling system in rainfed semiarid central Spain. The focus is on the combined effect of tillage system and winter cereal-based rotations (cereal/legume/fallow) on the crop yield and soil quality. The observed data come from a 16-year field experiment. The CERES and CROPGRO models, included in DSSAT v4.5, were used to simulate crop growth and yield, and DSSAT- CENTURY was used in the soil organic carbon (SOC) and soil nitrogen (SN) simulations. Genetic coefficients were calibrated using part of the observed data. Field observations showed that barley grain yield was lower for continuous cereal (BB) than for vetch (VB) and fallow (FB) rotations for both tillage systems. The CERES-Barley model also reflected this trend. The model predicted higher yield in the conventional tillage (CT) than in the no tillage (NT) probably due to the higher nitrogen availability in the CT, shown in the simulations. The SOC and SN in the top layer only, were higher in NT than in CT, and decreased with depth in both simulated and observed values. These results suggest that CT-VB and CT-FB were the best combinations for the dry land conditions studied. However, CT presented lower SN and SOC content than NT. This study shows how models can be a useful tool for assessing and predicting crop growth and yield, under different management systems and under specific edapho-climatic conditions. Additional key words: CENTURY model; CERES-Barley; crop simulation models; DSSAT; sequential simula- tion; soil organic carbon.

Climate variability effects on field crops in Iberian Peninsula. Predictability

La presente Tesis constituye un avance en el conocimiento de los efectos de la variabilidad climática en los cultivos en la Península Ibérica (PI). Es bien conocido que la temperatura del océano, particularmente de la región tropical, es una de las variables más convenientes para ser utilizado como predictor climático. Los océanos son considerados como la principal fuente de almacenamiento de calor del planeta debido a la alta capacidad calorífica del agua. Cuando se libera esta energía, altera los regímenes globales de circulación atmosférica por mecanismos de teleconexión. Estos cambios en la circulación general de la atmósfera afectan a la temperatura, precipitación, humedad, viento, etc., a escala regional, los cuales afectan al crecimiento, desarrollo y rendimiento de los cultivos. Para el caso de Europa, esto implica que la variabilidad atmosférica en una región específica se asocia con la variabilidad de otras regiones adyacentes y/o remotas, como consecuencia Europa está siendo afectada por los patrones de circulaciones globales, que a su vez, se ven afectados por patrones oceánicos. El objetivo general de esta tesis es analizar la variabilidad del rendimiento de los cultivos y su relación con la variabilidad climática y teleconexiones, así como evaluar su predictibilidad. Además, esta Tesis tiene como objetivo establecer una metodología para estudiar la predictibilidad de las anomalías del rendimiento de los cultivos. El análisis se centra en trigo y maíz como referencia para otros cultivos de la PI, cultivos de invierno en secano y cultivos de verano en regadío respectivamente. Experimentos de simulación de cultivos utilizando una metodología en cadena de modelos (clima + cultivos) son diseñados para evaluar los impactos de los patrones de variabilidad climática en el rendimiento y su predictibilidad. La presente Tesis se estructura en dos partes: La primera se centra en el análisis de la variabilidad del clima y la segunda es una aplicación de predicción cuantitativa de cosechas. La primera parte está dividida en 3 capítulos y la segundo en un capitulo cubriendo los objetivos específicos del presente trabajo de investigación. Parte I. Análisis de variabilidad climática El primer capítulo muestra un análisis de la variabilidad del rendimiento potencial en una localidad como indicador bioclimático de las teleconexiones de El Niño con Europa, mostrando su importancia en la mejora de predictibilidad tanto en clima como en agricultura. Además, se presenta la metodología elegida para relacionar el rendimiento con las variables atmosféricas y oceánicas. El rendimiento de los cultivos es parcialmente determinado por la variabilidad climática atmosférica, que a su vez depende de los cambios en la temperatura de la superficie del mar (TSM). El Niño es el principal modo de variabilidad interanual de la TSM, y sus efectos se extienden en todo el mundo. Sin embargo, la predictibilidad de estos impactos es controversial, especialmente aquellos asociados con la variabilidad climática Europea, que se ha encontrado que es no estacionaria y no lineal. Este estudio mostró cómo el rendimiento potencial de los cultivos obtenidos a partir de datos de reanálisis y modelos de cultivos sirve como un índice alternativo y más eficaz de las teleconexiones de El Niño, ya que integra las no linealidades entre las variables climáticas en una única serie temporal. Las relaciones entre El Niño y las anomalías de rendimiento de los cultivos son más significativas que las contribuciones individuales de cada una de las variables atmosféricas utilizadas como entrada en el modelo de cultivo. Además, la no estacionariedad entre El Niño y la variabilidad climática europea se detectan con mayor claridad cuando se analiza la variabilidad de los rendimiento de los cultivos. La comprensión de esta relación permite una cierta predictibilidad hasta un año antes de la cosecha del cultivo. Esta predictibilidad no es constante, sino que depende tanto la modulación de la alta y baja frecuencia. En el segundo capítulo se identifica los patrones oceánicos y atmosféricos de variabilidad climática que afectan a los cultivos de verano en la PI. Además, se presentan hipótesis acerca del mecanismo eco-fisiológico a través del cual el cultivo responde. Este estudio se centra en el análisis de la variabilidad del rendimiento de maíz en la PI para todo el siglo veinte, usando un modelo de cultivo calibrado en 5 localidades españolas y datos climáticos de reanálisis para obtener series temporales largas de rendimiento potencial. Este estudio evalúa el uso de datos de reanálisis para obtener series de rendimiento de cultivos que dependen solo del clima, y utilizar estos rendimientos para analizar la influencia de los patrones oceánicos y atmosféricos. Los resultados muestran una gran fiabilidad de los datos de reanálisis. La distribución espacial asociada a la primera componente principal de la variabilidad del rendimiento muestra un comportamiento similar en todos los lugares estudiados de la PI. Se observa una alta correlación lineal entre el índice de El Niño y el rendimiento, pero no es estacionaria en el tiempo. Sin embargo, la relación entre la temperatura del aire y el rendimiento se mantiene constante a lo largo del tiempo, siendo los meses de mayor influencia durante el período de llenado del grano. En cuanto a los patrones atmosféricos, el patrón Escandinavia presentó una influencia significativa en el rendimiento en PI. En el tercer capítulo se identifica los patrones oceánicos y atmosféricos de variabilidad climática que afectan a los cultivos de invierno en la PI. Además, se presentan hipótesis acerca del mecanismo eco-fisiológico a través del cual el cultivo responde. Este estudio se centra en el análisis de la variabilidad del rendimiento de trigo en secano del Noreste (NE) de la PI. La variabilidad climática es el principal motor de los cambios en el crecimiento, desarrollo y rendimiento de los cultivos, especialmente en los sistemas de producción en secano. En la PI, los rendimientos de trigo son fuertemente dependientes de la cantidad de precipitación estacional y la distribución temporal de las mismas durante el periodo de crecimiento del cultivo. La principal fuente de variabilidad interanual de la precipitación en la PI es la Oscilación del Atlántico Norte (NAO), que se ha relacionado, en parte, con los cambios en la temperatura de la superficie del mar en el Pacífico Tropical (El Niño) y el Atlántico Tropical (TNA). La existencia de cierta predictibilidad nos ha animado a analizar la posible predicción de los rendimientos de trigo en la PI utilizando anomalías de TSM como predictor. Para ello, se ha utilizado un modelo de cultivo (calibrado en dos localidades del NE de la PI) y datos climáticos de reanálisis para obtener series temporales largas de rendimiento de trigo alcanzable y relacionar su variabilidad con anomalías de la TSM. Los resultados muestran que El Niño y la TNA influyen en el desarrollo y rendimiento del trigo en el NE de la PI, y estos impactos depende del estado concurrente de la NAO. Aunque la relación cultivo-TSM no es igual durante todo el periodo analizado, se puede explicar por un mecanismo eco-fisiológico estacionario. Durante la segunda mitad del siglo veinte, el calentamiento (enfriamiento) en la superficie del Atlántico tropical se asocia a una fase negativa (positiva) de la NAO, que ejerce una influencia positiva (negativa) en la temperatura mínima y precipitación durante el invierno y, por lo tanto, aumenta (disminuye) el rendimiento de trigo en la PI. En relación con El Niño, la correlación más alta se observó en el período 1981 -2001. En estas décadas, los altos (bajos) rendimientos se asocian con una transición El Niño - La Niña (La Niña - El Niño) o con eventos de El Niño (La Niña) que están finalizando. Para estos eventos, el patrón atmosférica asociada se asemeja a la NAO, que también influye directamente en la temperatura máxima y precipitación experimentadas por el cultivo durante la floración y llenado de grano. Los co- efectos de los dos patrones de teleconexión oceánicos ayudan a aumentar (disminuir) la precipitación y a disminuir (aumentar) la temperatura máxima en PI, por lo tanto el rendimiento de trigo aumenta (disminuye). Parte II. Predicción de cultivos. En el último capítulo se analiza los beneficios potenciales del uso de predicciones climáticas estacionales (por ejemplo de precipitación) en las predicciones de rendimientos de trigo y maíz, y explora métodos para aplicar dichos pronósticos climáticos en modelos de cultivo. Las predicciones climáticas estacionales tienen un gran potencial en las predicciones de cultivos, contribuyendo de esta manera a una mayor eficiencia de la gestión agrícola, seguridad alimentaria y de subsistencia. Los pronósticos climáticos se expresan en diferentes formas, sin embargo todos ellos son probabilísticos. Para ello, se evalúan y aplican dos métodos para desagregar las predicciones climáticas estacionales en datos diarios: 1) un generador climático estocástico condicionado (predictWTD) y 2) un simple re-muestreador basado en las probabilidades del pronóstico (FResampler1). Los dos métodos se evaluaron en un caso de estudio en el que se analizaron los impactos de tres escenarios de predicciones de precipitación estacional (predicción seco, medio y lluvioso) en el rendimiento de trigo en secano, sobre las necesidades de riego y rendimiento de maíz en la PI. Además, se estimó el margen bruto y los riesgos de la producción asociada con las predicciones de precipitación estacional extremas (seca y lluviosa). Los métodos predWTD y FResampler1 usados para desagregar los pronósticos de precipitación estacional en datos diarios, que serán usados como inputs en los modelos de cultivos, proporcionan una predicción comparable. Por lo tanto, ambos métodos parecen opciones factibles/viables para la vinculación de los pronósticos estacionales con modelos de simulación de cultivos para establecer predicciones de rendimiento o las necesidades de riego en el caso de maíz. El análisis del impacto en el margen bruto de los precios del grano de los dos cultivos (trigo y maíz) y el coste de riego (maíz) sugieren que la combinación de los precios de mercado previstos y la predicción climática estacional pueden ser una buena herramienta en la toma de decisiones de los agricultores, especialmente en predicciones secas y/o localidades con baja precipitación anual. Estos métodos permiten cuantificar los beneficios y riesgos de los agricultores ante una predicción climática estacional en la PI. Por lo tanto, seríamos capaces de establecer sistemas de alerta temprana y diseñar estrategias de adaptación del manejo del cultivo para aprovechar las condiciones favorables o reducir los efectos de condiciones adversas. La utilidad potencial de esta Tesis es la aplicación de las relaciones encontradas para predicción de cosechas de la próxima campaña agrícola. Una correcta predicción de los rendimientos podría ayudar a los agricultores a planear con antelación sus prácticas agronómicas y todos los demás aspectos relacionados con el manejo de los cultivos. Esta metodología se puede utilizar también para la predicción de las tendencias futuras de la variabilidad del rendimiento en la PI. Tanto los sectores públicos (mejora de la planificación agrícola) como privados (agricultores, compañías de seguros agrarios) pueden beneficiarse de esta mejora en la predicción de cosechas. ABSTRACT The present thesis constitutes a step forward in advancing of knowledge of the effects of climate variability on crops in the Iberian Peninsula (IP). It is well known that ocean temperature, particularly the tropical ocean, is one of the most convenient variables to be used as climate predictor. Oceans are considered as the principal heat storage of the planet due to the high heat capacity of water. When this energy is released, it alters the global atmospheric circulation regimes by teleconnection1 mechanisms. These changes in the general circulation of the atmosphere affect the regional temperature, precipitation, moisture, wind, etc., and those influence crop growth, development and yield. For the case of Europe, this implies that the atmospheric variability in a specific region is associated with the variability of others adjacent and/or remote regions as a consequence of Europe being affected by global circulations patterns which, in turn, are affected by oceanic patterns. The general objective of this Thesis is to analyze the variability of crop yields at climate time scales and its relation to the climate variability and teleconnections, as well as to evaluate their predictability. Moreover, this Thesis aims to establish a methodology to study the predictability of crop yield anomalies. The analysis focuses on wheat and maize as a reference crops for other field crops in the IP, for winter rainfed crops and summer irrigated crops respectively. Crop simulation experiments using a model chain methodology (climate + crop) are designed to evaluate the impacts of climate variability patterns on yield and its predictability. The present Thesis is structured in two parts. The first part is focused on the climate variability analyses, and the second part is an application of the quantitative crop forecasting for years that fulfill specific conditions identified in the first part. This Thesis is divided into 4 chapters, covering the specific objectives of the present research work. Part I. Climate variability analyses The first chapter shows an analysis of potential yield variability in one location, as a bioclimatic indicator of the El Niño teleconnections with Europe, putting forward its importance for improving predictability in both climate and agriculture. It also presents the chosen methodology to relate yield with atmospheric and oceanic variables. Crop yield is partially determined by atmospheric climate variability, which in turn depends on changes in the sea surface temperature (SST). El Niño is the leading mode of SST interannual variability, and its impacts extend worldwide. Nevertheless, the predictability of these impacts is controversial, especially those associated with European climate variability, which have been found to be non-stationary and non-linear. The study showed how potential2 crop yield obtained from reanalysis data and crop models serves as an alternative and more effective index of El Niño teleconnections because it integrates the nonlinearities between the climate variables in a unique time series. The relationships between El Niño and crop yield anomalies are more significant than the individual contributions of each of the atmospheric variables used as input in the crop model. Additionally, the non-stationarities between El Niño and European climate variability are more clearly detected when analyzing crop-yield variability. The understanding of this relationship allows for some predictability up to one year before the crop is harvested. This predictability is not constant, but depends on both high and low frequency modulation. The second chapter identifies the oceanic and atmospheric patterns of climate variability affecting summer cropping systems in the IP. Moreover, hypotheses about the eco-physiological mechanism behind crop response are presented. It is focused on an analysis of maize yield variability in IP for the whole twenty century, using a calibrated crop model at five contrasting Spanish locations and reanalyses climate datasets to obtain long time series of potential yield. The study tests the use of reanalysis data for obtaining only climate dependent time series of simulated crop yield for the whole region, and to use these yield to analyze the influences of oceanic and atmospheric patterns. The results show a good reliability of reanalysis data. The spatial distribution of the leading principal component of yield variability shows a similar behaviour over all the studied locations in the IP. The strong linear correlation between El Niño index and yield is remarkable, being this relation non-stationary on time, although the air temperature-yield relationship remains on time, being the highest influences during grain filling period. Regarding atmospheric patterns, the summer Scandinavian pattern has significant influence on yield in IP. The third chapter identifies the oceanic and atmospheric patterns of climate variability affecting winter cropping systems in the IP. Also, hypotheses about the eco-physiological mechanism behind crop response are presented. It is focused on an analysis of rainfed wheat yield variability in IP. Climate variability is the main driver of changes in crop growth, development and yield, especially for rainfed production systems. In IP, wheat yields are strongly dependent on seasonal rainfall amount and temporal distribution of rainfall during the growing season. The major source of precipitation interannual variability in IP is the North Atlantic Oscillation (NAO) which has been related in part with changes in the Tropical Pacific (El Niño) and Atlantic (TNA) sea surface temperature (SST). The existence of some predictability has encouraged us to analyze the possible predictability of the wheat yield in the IP using SSTs anomalies as predictor. For this purpose, a crop model with a site specific calibration for the Northeast of IP and reanalysis climate datasets have been used to obtain long time series of attainable wheat yield and relate their variability with SST anomalies. The results show that El Niño and TNA influence rainfed wheat development and yield in IP and these impacts depend on the concurrent state of the NAO. Although crop-SST relationships do not equally hold on during the whole analyzed period, they can be explained by an understood and stationary ecophysiological mechanism. During the second half of the twenty century, the positive (negative) TNA index is associated to a negative (positive) phase of NAO, which exerts a positive (negative) influence on minimum temperatures (Tmin) and precipitation (Prec) during winter and, thus, yield increases (decreases) in IP. In relation to El Niño, the highest correlation takes place in the period 1981-2001. For these decades, high (low) yields are associated with an El Niño to La Niña (La Niña to El Niño) transitions or to El Niño events finishing. For these events, the regional associated atmospheric pattern resembles the NAO, which also influences directly on the maximum temperatures (Tmax) and precipitation experienced by the crop during flowering and grain filling. The co-effects of the two teleconnection patterns help to increase (decrease) the rainfall and decrease (increase) Tmax in IP, thus on increase (decrease) wheat yield. Part II. Crop forecasting The last chapter analyses the potential benefits for wheat and maize yields prediction from using seasonal climate forecasts (precipitation), and explores methods to apply such a climate forecast to crop models. Seasonal climate prediction has significant potential to contribute to the efficiency of agricultural management, and to food and livelihood security. Climate forecasts come in different forms, but probabilistic. For this purpose, two methods were evaluated and applied for disaggregating seasonal climate forecast into daily weather realizations: 1) a conditioned stochastic weather generator (predictWTD) and 2) a simple forecast probability resampler (FResampler1). The two methods were evaluated in a case study where the impacts of three scenarios of seasonal rainfall forecasts on rainfed wheat yield, on irrigation requirements and yields of maize in IP were analyzed. In addition, we estimated the economic margins and production risks associated with extreme scenarios of seasonal rainfall forecasts (dry and wet). The predWTD and FResampler1 methods used for disaggregating seasonal rainfall forecast into daily data needed by the crop simulation models provided comparable predictability. Therefore both methods seem feasible options for linking seasonal forecasts with crop simulation models for establishing yield forecasts or irrigation water requirements. The analysis of the impact on gross margin of grain prices for both crops and maize irrigation costs suggests the combination of market prices expected and the seasonal climate forecast can be a good tool in farmer’s decision-making, especially on dry forecast and/or in locations with low annual precipitation. These methodologies would allow quantifying the benefits and risks of a seasonal weather forecast to farmers in IP. Therefore, we would be able to establish early warning systems and to design crop management adaptation strategies that take advantage of favorable conditions or reduce the effect of adverse conditions. The potential usefulness of this Thesis is to apply the relationships found to crop forecasting on the next cropping season, suggesting opportunity time windows for the prediction. The methodology can be used as well for the prediction of future trends of IP yield variability. Both public (improvement of agricultural planning) and private (decision support to farmers, insurance companies) sectors may benefit from such an improvement of crop forecasting.

A simple regional-scale model for forecasting sorghum yield across North-Eastern Australia

Sorghum is the main dryland summer crop in NE Australia and a number of agricultural businesses would benefit from an ability to forecast production likelihood at regional scale. In this study we sought to develop a simple agro-climatic modelling approach for predicting shire (statistical local area) sorghum yield. Actual shire yield data, available for the period 1983-1997 from the Australian Bureau of Statistics, were used to train the model. Shire yield was related to a water stress index (SI) that was derived from the agro-climatic model. The model involved a simple fallow and crop water balance that was driven by climate data available at recording stations within each shire. Parameters defining the soil water holding capacity, maximum number of sowings (MXNS) in any year, planting rainfall requirement, and critical period for stress during the crop cycle were optimised as part of the model fitting procedure. Cross-validated correlations (CVR) ranged from 0.5 to 0.9 at shire scale. When aggregated to regional and national scales, 78-84% of the annual variation in sorghum yield was explained. The model was used to examine trends in sorghum productivity and the approach to using it in an operational forecasting system was outlined. (c) 2005 Elsevier B.V. All rights reserved.

Increasing profits and reducing risks in crop production using participatory systems simulation approaches

The development of cropping systems simulation capabilities world-wide combined with easy access to powerful computing has resulted in a plethora of agricultural models and consequently, model applications. Nonetheless, the scientific credibility of such applications and their relevance to farming practice is still being questioned. Our objective in this paper is to highlight some of the model applications from which benefits for farmers were or could be obtained via changed agricultural practice or policy. Changed on-farm practice due to the direct contribution of modelling, while keenly sought after, may in some cases be less achievable than a contribution via agricultural policies. This paper is intended to give some guidance for future model applications. It is not a comprehensive review of model applications, nor is it intended to discuss modelling in the context of social science or extension policy. Rather, we take snapshots around the globe to 'take stock' and to demonstrate that well-defined financial and environmental benefits can be obtained on-farm from the use of models. We highlight the importance of 'relevance' and hence the importance of true partnerships between all stakeholders (farmer, scientists, advisers) for the successful development and adoption of simulation approaches. Specifically, we address some key points that are essential for successful model applications such as: (1) issues to be addressed must be neither trivial nor obvious; (2) a modelling approach must reduce complexity rather than proliferate choices in order to aid the decision-making process (3) the cropping systems must be sufficiently flexible to allow management interventions based on insights gained from models. The pro and cons of normative approaches (e.g. decision support software that can reach a wide audience quickly but are often poorly contextualized for any individual client) versus model applications within the context of an individual client's situation will also be discussed. We suggest that a tandem approach is necessary whereby the latter is used in the early stages of model application for confidence building amongst client groups. This paper focuses on five specific regions that differ fundamentally in terms of environment and socio-economic structure and hence in their requirements for successful model applications. Specifically, we will give examples from Australia and South America (high climatic variability, large areas, low input, technologically advanced); Africa (high climatic variability, small areas, low input, subsistence agriculture); India (high climatic variability, small areas, medium level inputs, technologically progressing; and Europe (relatively low climatic variability, small areas, high input, technologically advanced). The contrast between Australia and Europe will further demonstrate how successful model applications are strongly influenced by the policy framework within which producers operate. We suggest that this might eventually lead to better adoption of fully integrated systems approaches and result in the development of resilient farming systems that are in tune with current climatic conditions and are adaptable to biophysical and socioeconomic variability and change. (C) 2001 Elsevier Science Ltd. All rights reserved.