Climate change impacts on temperate fruit and nut production: a systematic review.

Temperate fruit and nut crops require distinctive cold and warm seasons to meet their physiological requirements and progress through their phenological stages. Consequently, they have been traditionally cultivated in warm temperate climate regions characterized by dry-summer and wet-winter seasons. However, fruit and nut production in these areas faces new challenging conditions due to increasingly severe and erratic weather patterns caused by climate change. This review represents an effort towards identifying the current state of knowledge, key challenges, and gaps that emerge from studies of climate change effects on fruit and nut crops produced in warm temperate climates. Following the PRISMA methodology for systematic reviews, we analyzed 403 articles published between 2000 and 2023 that met the defined eligibility criteria. A 44-fold increase in the number of publications during the last two decades reflects a growing interest in research related to both a better understanding of the effects of climate anomalies on temperate fruit and nut production and the need to find strategies that allow this industry to adapt to current and future weather conditions while reducing its environmental impacts. In an extended analysis beyond the scope of the systematic review methodology, we classified the literature into six main areas of research, including responses to environmental conditions, water management, sustainable agriculture, breeding and genetics, prediction models, and production systems. Given the rapid expansion of climate change-related literature, our analysis provides valuable information for researchers, as it can help them identify aspects that are well understood, topics that remain unexplored, and urgent questions that need to be addressed in the future.

Climatic drivers and ecological implications of variation in the time interval between leaf-out and flowering.

Leaf-out and flowering in any given species have evolved to occur in a predetermined sequence, with the inter-stage time interval optimized to maximize plant fitness. Although warming-induced advances of both leaf-out and flowering are well documented, it remains unclear whether shifts in these phenological phases differ in magnitudes and whether changes have occurred in the length of the inter-stage intervals. Here, we present an extensive synthesis of warming effects on flower-leaf time intervals, using long-term (1963-2014) and in situ data consisting of 11,858 leaf-out and flowering records for 183 species across China. We found that the timing of both spring phenological events was generally advanced, indicating a dominant impact of forcing conditions compared with chilling. Stable time intervals between leaf-out and flowering prevailed for most of the time series despite increasing temperatures; however, some of the investigated cases featured significant changes in the time intervals. The latter could be explained by differences in the temperature sensitivity (ST) between leaf and flower phenology. Greater ST for flowering than for leaf-out caused flowering times to advance faster than leaf emergence. This shortened the inter-stage intervals in leaf-first species and lengthened them in flower-first species. Variation in the time intervals between leaf-out and flowering events may have far-reaching ecological and evolutionary consequences, with implications for species fitness, intra/inter-species interactions, and ecosystem structure, function, and stability.

Impact of Chill and Heat Exposures under Diverse Climatic Conditions on Peach and Nectarine Flowering Phenology.

The present study aims to generalize cultivar-specific tree phenology responses to winter and spring temperatures and assess the effectiveness of the Tabuenca test and various chill and heat accumulation models in predicting bloom dates for a wide range of climatic conditions and years. To this end, we estimated the dates of rest completion and blooming and correlated them with observed bloom dates for 14 peach and nectarine cultivars that were evaluated in 11 locations across Europe (Greece, France, Italy, Romania and Spain), within the EUFRIN cultivar testing trial network. Chill accumulation varied considerably among the studied sites, ranging from 45 Chill Portions (CP) in Murcia-Torre Pacheco (Spain) to 97-98 CP in Cuneo (Italy) and Bucharest (Romania). Rest completion occurred latest or was not achieved at all for some cultivars in the southern sites in Murcia. Dormancy release happened earliest in Bucharest and Cuneo, sites where heat accumulation had a strong influence on the regulation of bloom time. Blooming occurred earliest in the moderately cold regions of Lleida (Spain) and Bellegarde (France), and 7-11 days later in the warmer locations of Rome (Italy) and Naoussa (Greece), suggesting that bloom timing is strongly influenced by delayed rest completion in these locations. The Dynamic Model resulted in both more homogeneous chill accumulation across years and better predictions of bloom dates, compared with the Utah, Positive Utah and Chilling Hours models. Prediction of bloom dates was less successful for low-chill cultivars than for medium- and high-chill cultivars. Further climatic and experimental data are needed to make estimates of the climatic needs of peach cultivars more robust and to generate reliable advice for enhancing the resilience of peach production under varying and changing climatic conditions.

Prioritizing farm management interventions to improve climate change adaptation and mitigation outcomes-a case study for banana plantations.

Intervening into agricultural systems necessarily includes risks, uncertainties, and ultimately unknown outcomes. Decision analysis embraces uncertainty through an interdisciplinary approach that involves relevant stakeholders in evaluating complex decisions. We applied decision analysis approaches to prioritize 21 farm management interventions, which could be considered in certification schemes for banana production. We estimated their contribution to climate change adaptation and mitigation as well as ecological outcomes. We used a general model that estimated the impacts of each intervention on adaptation (benefits minus costs), mitigation (global warming potential), ecological parameters (e.g., biodiversity and water and soil quality), and farming aspects (e.g., yield, implementation costs and production risks). We used expert and documented knowledge and presented uncertainties in the form of 90% confidence intervals to feed the model and forecast the changes in system outcomes caused by each intervention compared to a baseline scenario without the measure. By iterating the model function 10,000 times, we obtained probability distributions for each of the outcomes and farm management interventions. Our results suggest that interventions associated with nutrient management (e.g., composting and nutrient management plan) positively affect climate change adaptation, mitigation, and ecological aspects. Measures with no direct yield benefits (e.g., plastic reduction) correlate negatively with adaptation but have positive impacts on ecology. Creating buffer zones and converting low-productivity farmland (incl. unused land) also have positive ecological and adaptation outcomes. Decision analysis can help in prioritizing farm management interventions, which may vary considerably in their relationship with the expected outcomes. Additional work may be required to elaborate a comprehensive assessment of the underlying aspects modulating the impacts of a given measure on the evaluated outcome. Our analysis provides insights on the most promising interventions for banana plantations and may help practitioners and researchers in focusing further studies. Supplementary Information: The online version contains supplementary material available at 10.1007/s13593-022-00809-0.

Assessing expected utility and profitability to support decision-making for disease control strategies in ornamental heather production.

Many farmers hesitate to adopt new management strategies with actual or perceived risks and uncertainties. Especially in ornamental plant production, farmers often stick to current production strategies to avoid the risk of economically harmful plant losses, even though they may recognize the need to optimize farm management. This work focused on the economically important and little-researched production system of ornamental heather (Calluna vulgaris) to help farmers find appropriate measures to sustainably improve resource use, plant quality, and profitability despite existing risks. Probabilistic cost-benefit analysis was applied to simulate alternative disease monitoring strategies. The outcomes for more intensive visual monitoring, as well as sensor-based monitoring using hyperspectral imaging were simulated. Based on the results of the probabilistic cost-benefit analysis, the expected utility of the alternative strategies was assessed as a function of the farmer's level of risk aversion. The analysis of expected utility indicated that heather production is generally risky. Concerning the alternative strategies, more intensive visual monitoring provides the highest utility for farmers for almost all levels of risk aversion compared to all other strategies. Results of the probabilistic cost-benefit analysis indicated that more intensive visual monitoring increases net benefits in 68% of the simulated cases. The application of sensor-based monitoring leads to negative economic outcomes in 85% of the simulated cases. This research approach is widely applicable to predict the impacts of new management strategies in precision agriculture. The methodology can be used to provide farmers in other data-scarce production systems with concrete recommendations that account for uncertainties and risks. Supplementary information: The online version contains supplementary material available at 10.1007/s11119-022-09909-z.

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.

Stochastic impact evaluation of an irrigation development intervention in Northern Ethiopia.

Irrigation plays a significant role in achieving food and nutrition security in dry regions. However, detailed ex-ante appraisals of irrigation development investments are required to efficiently allocate resources and optimize returns on investment. Due to the inherent system complexity and uncertain consequences of irrigation development interventions coupled with limited data availability, deterministic cost-benefit analysis can be ineffective in guiding formal decision-making. Stochastic Impact Evaluation (SIE) helps to overcome the challenges of evaluating investments in such contexts. In this paper, we applied SIE to assess the viability of an irrigation dam construction project in northern Ethiopia. We used expert knowledge elicitation to generate a causal model of the planned intervention's impact pathway, including all identified benefits, costs and risks. Estimates of the input variables were collected from ten subject matter experts. We then applied the SIE tools: Monte Carlo simulation, Partial Least Squares regression, and Value of Information analysis to project prospective impacts of the project and identify critical knowledge gaps. Model results indicate that the proposed irrigation dam project is highly likely to increase the overall benefits and improve food and nutrition status of local farmers. However, the overall value of these benefits is unlikely to exceed the sum of the investment costs and negative externalities involved in the intervention. Simulation results suggest that the planned irrigation dam may improve income, as well as food and nutrition security, but would generate negative environmental effects and high investment costs. The Stochastic Impact Evaluation approach proved effective in this study and is likely to have potential for evaluating other agricultural development interventions that face system complexity, data scarcity and uncertainty.

Climate change threatens central Tunisian nut orchards.

Temperate deciduous trees can only be productive where winters are cold enough to meet their chilling needs. In the Mediterranean region, chill has traditionally been sufficient for many species, but this may change as temperatures increase. We explored the region's present and future suitability for temperate trees by quantifying chill for the Sfax region in central Tunisia, one of the warmest regions where temperate nuts are commercially grown. We assessed climatic risk by calculating historic chill (since 1973) and using a weather generator calibrated with local weather data (1973-2015) to produce 101 years of chill estimates (computed with the Dynamic Model) and 3 past and 72 future scenarios (for 2041-2070 and 2071-2100, using two representative concentration pathways: RCP4.5 and RCP8.5). For almonds and pistachios, we compared available chill during the chilling period with the species' estimated chilling requirements, and we computed the date by which sufficient chill was expected to have accumulated. Our findings indicated severe chill losses for all future scenarios. For all species, the current chill period is no longer expected to be sufficient for meeting chilling requirements in the future. Chill needs may still be fulfilled later in the year, especially for low-chill almonds, but this would result in delayed phenology, with possible adverse effects on productivity. Temperate nut production is thus unlikely to remain viable at this site, highlighting an urgent need to identify locally appropriate adaptation options. This challenge is likely shared by other warm production regions of temperate fruits and nuts around the world.

Interpolating hourly temperatures for computing agroclimatic metrics.

Calculating many agroclimatic metrics, e.g., chill or heat accumulation in orchards, requires continuous records of hourly temperature. Such records are often unavailable, with farm managers and researchers relying on daily data or hourly records with gaps. While procedures for generating idealized temperature curves exist, interpolating hourly records has long been a challenge. The SolveHours procedure combines measured hourly temperatures, idealized daily temperature curves and proxy data to fill gaps in such records. It first determines daily temperature extremes by solving systems of linear equations that express the typical relationships between hourly temperatures and daily temperature extremes for every hour. After filling gaps in this record with bias-corrected data from proxy stations or by linear interpolation, SolveHours uses these data to generate an idealized temperature curve. Deviations of recorded hourly temperatures from this curve are calculated, linearly interpolated, and added to the idealized curve to obtain a gapless record. The procedure was compared to alternative gap-filling algorithms using an 8-month dataset from an orchard near Winters, CA, in which half the records were replaced by 500 gaps of random length. The SolveHours procedure achieved ratio of performance to interquartile distance (RPIQ) values of 6.7 (when using temperature extremes from a proxy station) and 8.2 (with temperature extremes measured on site), with root mean square errors of 1.6 and 1.3 °C, respectively. It outperformed all other algorithms in reproducing recorded accumulation of Chill Portions and Growing Degree Hours. The SolveHours procedure is implemented in the chillR package for the R programming environment ( https://cran.r-project.org/web/packages/chillR/vignettes/hourly_temperatures.html ).

Multiple lines of evidence for the origin of domesticated chili pepper, Capsicum annuum, in Mexico.

The study of crop origins has traditionally involved identifying geographic areas of high morphological diversity, sampling populations of wild progenitor species, and the archaeological retrieval of macroremains. Recent investigations have added identification of plant microremains (phytoliths, pollen, and starch grains), biochemical and molecular genetic approaches, and dating through (14)C accelerator mass spectrometry. We investigate the origin of domesticated chili pepper, Capsicum annuum, by combining two approaches, species distribution modeling and paleobiolinguistics, with microsatellite genetic data and archaeobotanical data. The combination of these four lines of evidence yields consensus models indicating that domestication of C. annuum could have occurred in one or both of two areas of Mexico: northeastern Mexico and central-east Mexico. Genetic evidence shows more support for the more northern location, but jointly all four lines of evidence support central-east Mexico, where preceramic macroremains of chili pepper have been recovered in the Valley of Tehuacán. Located just to the east of this valley is the center of phylogenetic diversity of Proto-Otomanguean, a language spoken in mid-Holocene times and the oldest protolanguage for which a word for chili pepper reconstructs based on historical linguistics. For many crops, especially those that do not have a strong archaeobotanical record or phylogeographic pattern, it is difficult to precisely identify the time and place of their origin. Our results for chili pepper show that expressing all data in similar distance terms allows for combining contrasting lines of evidence and locating the region(s) where cultivation and domestication of a crop began.

Chilling and heat requirements for flowering in temperate fruit trees.

Climate change has affected the rates of chilling and heat accumulation, which are vital for flowering and production, in temperate fruit trees, but few studies have been conducted in the cold-winter climates of East Asia. To evaluate tree responses to variation in chill and heat accumulation rates, partial least squares regression was used to correlate first flowering dates of chestnut (Castanea mollissima Blume) and jujube (Zizyphus jujube Mill.) in Beijing, China, with daily chill and heat accumulation between 1963 and 2008. The Dynamic Model and the Growing Degree Hour Model were used to convert daily records of minimum and maximum temperature into horticulturally meaningful metrics. Regression analyses identified the chilling and forcing periods for chestnut and jujube. The forcing periods started when half the chilling requirements were fulfilled. Over the past 50 years, heat accumulation during tree dormancy increased significantly, while chill accumulation remained relatively stable for both species. Heat accumulation was the main driver of bloom timing, with effects of variation in chill accumulation negligible in Beijing's cold-winter climate. It does not seem likely that reductions in chill will have a major effect on the studied species in Beijing in the near future. Such problems are much more likely for trees grown in locations that are substantially warmer than their native habitats, such as temperate species in the subtropics and tropics.

Identification of chilling and heat requirements of cherry trees--a statistical approach.

Most trees from temperate climates require the accumulation of winter chill and subsequent heat during their dormant phase to resume growth and initiate flowering in the following spring. Global warming could reduce chill and hence hamper the cultivation of high-chill species such as cherries. Yet determining chilling and heat requirements requires large-scale controlled-forcing experiments, and estimates are thus often unavailable. Where long-term phenology datasets exist, partial least squares (PLS) regression can be used as an alternative, to determine climatic requirements statistically. Bloom dates of cherry cv. 'Schneiders späte Knorpelkirsche' trees in Klein-Altendorf, Germany, from 24 growing seasons were correlated with 11-day running means of daily mean temperature. Based on the output of the PLS regression, five candidate chilling periods ranging in length from 17 to 102 days, and one forcing phase of 66 days were delineated. Among three common chill models used to quantify chill, the Dynamic Model showed the lowest variation in chill, indicating that it may be more accurate than the Utah and Chilling Hours Models. Based on the longest candidate chilling phase with the earliest starting date, cv. 'Schneiders späte Knorpelkirsche' cherries at Bonn exhibited a chilling requirement of 68.6 ± 5.7 chill portions (or 1,375 ± 178 chilling hours or 1,410 ± 238 Utah chill units) and a heat requirement of 3,473 ± 1,236 growing degree hours. Closer investigation of the distinct chilling phases detected by PLS regression could contribute to our understanding of dormancy processes and thus help fruit and nut growers identify suitable tree cultivars for a future in which static climatic conditions can no longer be assumed. All procedures used in this study were bundled in an R package ('chillR') and are provided as Supplementary materials. The procedure was also applied to leaf emergence dates of walnut (cv. 'Payne') at Davis, California.

Flowering phenology of tree rhododendron along an elevation gradient in two sites in the Eastern Himalayas.

Flowering phenology of tree rhododendron (Rhododendron arboreum Sm.) was monitored in situ along elevation gradients in two distinct ecological settings. Observations were carried out in Gaoligong Nature Reserve (GNR) in China and in the Kanchenjunga Conservation Area (KCA) in Nepal. Using the crown density method, flowering events of the selected species were recorded. Flowering duration and synchrony were determined within each site and along the elevation gradient in each study area. Our observations showed high synchrony throughout the elevation gradient, especially for peak flowering. Mean 15-day soil temperature, soil parameters (soil moisture, nitrogen, organic matter and pH), age of the observed trees, and site characteristics (litter cover, canopy cover, inclination) were related to mean initial and peak flowering dates using partial least squares regression (PLS). Results differed between the two sites, but winter temperature was the most important variable affecting the regression model for both initial flowering and peak flowering at both sites. After temperature, soil moisture was the most important variable for explaining initial flowering dates. The distribution of tree rhododendron indicates that it is able to grow in a wide range of habitats with different environmental conditions. The recent trend of rising winter-spring temperature and the detected bloom-advancing effect of high temperatures during this period suggest that tree rhododendron might expand its distributional range in response to global warming.

Seasonal response of grasslands to climate change on the Tibetan Plateau.

BACKGROUND: Monitoring vegetation dynamics and their responses to climate change has been the subject of considerable research. This paper aims to detect change trends in grassland activity on the Tibetan Plateau between 1982 and 2006 and relate these to changes in climate. METHODOLOGY/PRINCIPAL FINDINGS: Grassland activity was analyzed by evaluating remotely sensed Normalized Difference Vegetation Index (NDVI) data collected at 15-day intervals between 1982 and 2006. The timings of vegetation stages (start of green-up, beginning of the growing season, plant maturity, start of senescence and end of the growing season) were assessed using the NDVI ratio method. Mean NDVI values were determined for major vegetation stages (green-up, fast growth, maturity and senescence). All vegetation variables were linked with datasets of monthly temperature and precipitation, and correlations between variables were established using Partial Least Squares regression. Most parts of the Tibetan Plateau showed significantly increasing temperatures, as well as clear advances in late season phenological stages by several weeks. Rainfall trends and significant long-term changes in early season phenology occurred on small parts of the plateau. Vegetation activity increased significantly for all vegetation stages. Most of these changes were related to increasing temperatures during the growing season and in some cases during the previous winter. Precipitation effects appeared less pronounced. Warming thus appears to have shortened the growing season, while increasing vegetation activity. CONCLUSIONS/SIGNIFICANCE: Shortening of the growing season despite a longer thermally favorable period implies that vegetation on the Tibetan Plateau is unable to exploit additional thermal resources availed by climate change. Ecosystem composition may no longer be well attuned to the local temperature regime, which has changed rapidly over the past three decades. This apparent lag of the vegetation assemblage behind changes in climate should be taken into account when projecting the impacts of climate change on ecosystem processes.

Climate change affects winter chill for temperate fruit and nut trees.

BACKGROUND: 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. METHODOLOGY/PRINCIPAL FINDINGS: 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. CONCLUSIONS/SIGNIFICANCE: 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.

A global analysis of the comparability of winter chill models for fruit and nut trees.

Many fruit and nut trees must fulfill a chilling requirement to break their winter dormancy and resume normal growth in spring. Several models exist for quantifying winter chill, and growers and researchers often tacitly assume that the choice of model is not important and estimates of species chilling requirements are valid across growing regions. To test this assumption, Safe Winter Chill (the amount of winter chill that is exceeded in 90% of years) was calculated for 5,078 weather stations around the world, using the Dynamic Model [in Chill Portions (CP)], the Chilling Hours (CH) Model and the Utah Model [Utah Chill Units (UCU)]. Distributions of the ratios between different winter chill metrics were mapped on a global scale. These ratios should be constant if the models were strictly proportional. Ratios between winter chill metrics varied substantially, with the CH/CP ratio ranging between 0 and 34, the UCU/CP ratio between -155 and +20 and the UCU/CH ratio between -10 and +5. The models are thus not proportional, and chilling requirements determined in a given location may not be valid elsewhere. The Utah Model produced negative winter chill totals in many Subtropical regions, where it does not seem to be useful. Mean annual temperature and daily temperature range influenced all winter chill ratios, but explained only between 12 and 27% of the variation. Data on chilling requirements should always be amended with information on the location and experimental conditions of the study in which they were determined, ideally including site-specific conversion factors between winter chill models. This would greatly facilitate the transfer of such information across growing regions, and help prepare growers for the impact of climate change.

Winter and spring warming result in delayed spring phenology on the Tibetan Plateau.

Climate change has caused advances in spring phases of many plant species. Theoretically, however, strong warming in winter could slow the fulfillment of chilling requirements, which may delay spring phenology. This phenomenon should be particularly pronounced in regions that are experiencing rapid temperature increases and are characterized by highly temperature-responsive vegetation. To test this hypothesis, we used the Normalized Difference Vegetation Index ratio method to determine the beginning, end, and length of the growing season of meadow and steppe vegetation of the Tibetan Plateau in Western China between 1982 and 2006. We then correlated observed phenological dates with monthly temperatures for the entire period on record. For both vegetation types, spring phenology initially advanced, but started retreating in the mid-1990s in spite of continued warming. Together with an advancing end of the growing season for steppe vegetation, this led to a shortening of the growing period. Partial least-squares regression indicated that temperatures in both winter and spring had strong effects on spring phenology. Although warm springs led to an advance of the growing season, warm conditions in winter caused a delay of the spring phases. This delay appeared to be related to later fulfillment of chilling requirements. Because most plants from temperate and cold climates experience a period of dormancy in winter, it seems likely that similar effects occur in other environments. Continued warming may strengthen this effect and attenuate or even reverse the advancing trend in spring phenology that has dominated climate-change responses of plants thus far.