Agroforestry Options in Northwest Vietnam

The mountainous northwest of Vietnam is home for the majority of the country’s ethnic minorities. Poverty and food insecurity are common in the region, increasing population and land scarcity have induced the expansion of agricultural areas and consequent decline of land productivity due to soil erosion and land degradation. Local farmers have begun to practice agroforestry through the introduction of high value trees into traditional cropping systems with various combinations of timber, fruit, nut forage trees and annual crops. However, because of inherent production risks and many remaining uncertainties, assessing the long-term performance of agroforestry has remained challenging. We simulated prospective system benefits of agroforestry options by developing comprehensive and holistic models that aimed to explicitly consider all relevant risks and uncertainties. The initial findings reveal model components such as drought and frost and potential extreme weather events as the primary risks to agroforestry in the region. The analysis approach is a promising tool for ex-ante assessments of other planned interventions

Data for the evaluation of irrigation development interventions in Northern Ethiopia

This data article provides the datasets that are used in the holistic ex-ante impact evaluation of an irrigation dam construction project in Northern Ethiopia [1]. We used an expert knowledge elicitation approach as a means of acquiring the data. The data shared here captures all the parameters considered important in the impact pathway (i.e. the expected benefits, costs, and risks) of the decision to construct an irrigation dam. The dataset is disaggregated for two impact pathway models: one complementing the dam construction with catchment restoration and the other without catchment restoration. Both models are scripted in the R programming language. The data can be used to examine how the construction of an irrigation dam affects the incomes as well as the food and nutritional status of farmers that are affected by the intervention

Unusually warm winter seasons may compromise the performance of current phenology models : Predicting bloom dates in young apple trees with PhenoFlex

Phenology models are crucial tools for assessing climate change impacts in forestry, ecology and agriculture. Such models are typically calibrated with observational or experimental data and validated with a set of independent observations. While there have been extensive discussions about validation approaches, systematic studies assessing the effects of the calibration data on the predictive performance of the fitted model are scarce. We evaluated the impact of marginal seasons in the calibration data set on the predictive power of an integrated modeling framework (PhenoFlex) that was recently proposed to predict spring phenology in temperate trees. We calibrated PhenoFlex with phenology records of apple trees from a multi-season experiment (59 experimental seasons) that included five unusually warm winter seasons. For comparison, we excluded these marginal seasons in a second version of the analysis. We fitted the 12 model parameters to data, assessed model performance using a common validation data set and evaluated the chill and heat responses during dormancy for both versions. Despite high overall accuracy, our results indicated a better model performance (Root Mean Square Errors of 2.3 versus 5.5 days) when excluding the marginal seasons. We observed a similar shape for the chill response curve across versions but a greater chill effectiveness when including the marginal seasons. Fitted parameters suggest a hard drop in heat efficiency beyond the optimum temperature when including the marginal seasons, probably highlighting the need for more moderate conditions during model calibration. Our results demonstrate a good performance of PhenoFlex when calibration and validation data were comparable, but they also indicate risks involved in using the framework to project phenology under conditions that differ strongly from those used for calibration. Further evaluation and validation under experimentally or naturally occurring warm conditions may improve our understanding of the response of temperate trees to mild winter conditions

Decision analysis methods guide: agricultural policy for nutrition

It is often very difficult to make accurate projections about how interventions will affect the real world and to use such projections to develop effective implementation plans, monitor progress and evaluate project impacts. This is due to a variety of factors including lack of data, complex impact pathways and risks and uncertainties that are difficult to factor into intervention planning. Scientific approaches to produce reliable impact projections are rarely applied in agricultural development, but Decision Analysis techniques commonly used in other fields have the potential to improve development decisions. This working paper outlines a Decision Analysis approach that can help decision makers efficiently allocate resources to enhance the effectiveness of policy decisions. The procedures outlined in this publication feature the construction of causal models – models that describe the mechanisms through which intervention impacts will be delivered – that are codeveloped by experts, stakeholders and analysts through facilitated participatory processes. These models are then formalized as Bayesian Network (BN) models, a modelling approach that has been widely applied in a range of disciplines, including medical sciences, genetics, environmental sciences and legal reasoning. BNs allow for the formal representation of causal models, such as intervention impact pathways. They can work effectively with incomplete information, combine expert knowledge with other sources of information and allow for adequate consideration of risk. This paper illustrates the use of participatory workshops that convene experts on the systems, stakeholders involved in ongoing or prospective projects and analysts. These teams can jointly develop impact pathways for the interventions, which can be formalized into quantitative BN models. After several rounds of feedback elicitation and the inclusion of data from experts and other sources, stochastic simulations can be run to determine the likely impacts of the interventions. Results can be presented back to stakeholders for feedback. Through the tools presented in this working paper, critical uncertainties in the models of intervention impact pathways can be identified. These high-value variables can determine uncertainty about project outcomes. Further measurement or disaggregation of these variables can support decisionmaking processes. By demonstrating improved intervention decisions with little additional investment and improved tools for intervention decision modelling, we hope that this approach will be widely adopted and used to enhance the efficacy of development activitie

Climate Change Affects Winter Chill for Temperate Fruit and Nut Trees

Temperate fruit and nut trees require adequate winter chill to produce economically viable yields. Global warming has the potential to reduce available winter chill and greatly impact crop yields.We estimated winter chill for two past (1975 and 2000) and 18 future scenarios (mid and end 21st century; 3 Global Climate Models [GCMs]; 3 greenhouse gas emissions [GHG] scenarios). For 4,293 weather stations around the world and GCM projections, Safe Winter Chill (SWC), the amount of winter chill that is exceeded in 90% of all years, was estimated for all scenarios using the "Dynamic Model" and interpolated globally. We found that SWC ranged between 0 and about 170 Chill Portions (CP) for all climate scenarios, but that the global distribution varied across scenarios. Warm regions are likely to experience severe reductions in available winter chill, potentially threatening production there. In contrast, SWC in most temperate growing regions is likely to remain relatively unchanged, and cold regions may even see an increase in SWC. Climate change impacts on SWC differed quantitatively among GCMs and GHG scenarios, with the highest GHG leading to losses up to 40 CP in warm regions, compared to 20 CP for the lowest GHG.The extent of projected changes in winter chill in many major growing regions of fruits and nuts indicates that growers of these commodities will likely experience problems in the future. Mitigation of climate change through reductions in greenhouse gas emissions can help reduce the impacts, however, adaption to changes will have to occur. To better prepare for likely impacts of climate change, efforts should be undertaken to breed tree cultivars for lower chilling requirements, to develop tools to cope with insufficient winter chill, and to better understand the temperature responses of tree crops

Delayed chilling appears to counteract flowering advances of apricot in southern UK

Temperatures are rising across the globe, and the UK is no exception. Spring phenology of perennial fruit crops is to a large extent determined by temperature during effective chilling (endo-dormancy) and heat accumulation (eco-dormancy) periods. We used the apricot flowering records of the UK National Fruit Collections (NFC) to determine the influence of temperature trends over recent decades (1960 to 2014) on apricot (Prunus armeniaca L.) flowering time. Using Partial Least Squares (PLS) regression, we determined the respective periods for calculating chill and heat accumulation. Results suggested intervals between September 27th and February 26th and between December 31st and April 12th as the effective chilling and warming periods, respectively. Flowering time was correlated with temperature during both periods, with warming during chilling corresponding to flowering delays by 4.82 d°C-1, while warming during heat accumulation was associated with bloom advances by 9.85 d°C-1. Heat accumulation started after accumulating 62.7 ± 5.6 Chill Portions, and flowering occurred after a further 3744 ± 1538 Growing Degree Hours (above a base temperature of 4°C, with optimal growth at 26°C). When examining the time series, the increase in temperature during the chilling period did not appear to decrease overall chill accumulation during the chilling period but to delay the onset of chill accumulation and the completion of the the average chill accumulation necessary to start heat accumulation. The resulting delay in heat responsiveness appeared to weaken the phenology-advancing effect of spring warming. These processes may explain why apricot flowering time remained relatively unchanged despite significant temperature increases. A consequence of this may be a reduction of frost risk for early flowering crops such as apricot in the UK

Differential responses of trees to temperature variation during the chilling and forcing phases

AbstractTemperate-zone trees must fulfill cultivar-specific chilling and heat requirements during the dormant period, in order to produce leaves and flowers in the following growing season. Timing and accumulation rate of chill and heat are understood to determine the timing of spring events, but both processes are difficult to observe in dormant tree buds. Where long-term phenological observations are available, Partial Least Squares (PLS) regression offers a statistical opportunity to delineate phases of chill and heat accumulation and determine the climatic requirements of trees. This study uses PLS regression to explore how the timing of spring events of chestnut in China, cherry in Germany and walnut in California is related to variation in the daily rates of chill and heat accumulation, as calculated with horticultural models. Dependent variables were 39 years of flowering dates for chestnuts in Beijing (China), 25 years of cherry bloom in Klein-Altendorf (Germany) and 54 years of walnut leaf emergence in Davis (California, USA). These were related to daily accumulation rates of chill, calculated with the Dynamic Model, and heat, calculated with the Growing Degree Hours Model. Compared to an earlier version of the procedure, in which phenological dates were related to unprocessed temperature data, delineation of chilling and forcing phases was much clearer when using horticultural metrics to quantify chill and heat. Chestnut bloom in the cold-winter climate of Beijing was found to depend primarily on the rate of heat accumulation, while cherry bloom in the temperate climate of Germany showed dependence on both chill and heat accumulation rates. The timing of walnut leaf emergence in the mild-winter climate of California depended much more strongly on chill accumulation rates. Chilling (in Chill Portions=CP) and heat (in Growing Degree Hours=GDH) requirements determined based on PLS regression were 79.8±5.3 CP and 13,466±1918 GDH for chestnut bloom in Beijing, 104.2±8.9 CP and 2698±1183 GDH for cherry bloom in Germany, and 37.5±5.0 CP and 11,245±1697 GDH for walnut leaf emergence in California. Spring phases of cherry in Klein-Altendorf and especially chestnut in Beijing will likely continue to advance in response to global warming, while for walnut in California, inadequate chilling may cause delays in flowering and leaf emergence. Such delays could serve as an early-warning indicator that future productivity may be threatened by climate change. The R package ‘chillR’ makes the method used in this study available for wider use