Climate Change and Crop Exposure to Adverse Weather: Changes to Frost Risk and Grapevine Flowering Conditions

The cultivation of grapevines in the UK and many other cool climate regions is expected to benefit from the higher growing season temperatures predicted under future climate scenarios. Yet the effects of climate change on the risk of adverse weather conditions or events at key stages of crop development are not always captured by aggregated measures of seasonal or yearly climates, or by downscaling techniques that assume climate variability will remain unchanged under future scenarios. Using fine resolution projections of future climate scenarios for south-west England and grapevine phenology models we explore how risks to cool-climate vineyard harvests vary under future climate conditions. Results indicate that the risk of adverse conditions during flowering declines under all future climate scenarios. In contrast, the risk of late spring frosts increases under many future climate projections due to advancement in the timing of budbreak. Estimates of frost risk, however, were highly sensitive to the choice of phenology model, and future frost exposure declined when budbreak was calculated using models that included a winter chill requirement for dormancy break. The lack of robust phenological models is a major source of uncertainty concerning the impacts of future climate change on the development of cool-climate viticulture in historically marginal climatic regions.     

Future scenarios for viticultural zoning in Europe: ensemble projections and uncertainties

Optimum climate conditions for grapevine growth are limited geographically and may be further challenged by a changing climate. Due to the importance of the winemaking sector in Europe, the assessment of future scenarios for European viticulture is of foremost relevance. A 16-member ensemble of model transient experiments (generated by the ENSEMBLES project) under a greenhouse gas emission scenario and for two future periods (2011–2040 and 2041–2070) is used in assessing climate change projections for six viticultural zoning indices. After model data calibration/validation using an observational gridded daily dataset, changes in their ensemble means and inter-annual variability are discussed, also taking into account the model uncertainties. Over southern Europe, the projected warming combined with severe dryness in the growing season is expected to have detrimental impacts on the grapevine development and wine quality, requiring measures to cope with heat and water stress. Furthermore, the expected warming and the maintenance of moderately wet growing seasons over most of the central European winemaking regions may require a selection of new grapevine varieties, as well as an enhancement of pest/disease control. New winemaking regions may arise over northern Europe and high altitude areas, when considering climatic factors only. An enhanced inter-annual variability is also projected over most of Europe. All these future changes pose new challenges for the European winemaking sector.     

Hotspots of climate change impacts in sub‐Saharan Africa and implications for adaptation and development

Development efforts for poverty reduction and food security in sub‐Saharan Africa will have to consider future climate change impacts. Large uncertainties in climate change impact assessments do not necessarily complicate, but can inform development strategies. The design of development strategies will need to consider the likelihood, strength, and interaction of climate change impacts across biosphere properties. We here explore the spread of climate change impact projections and develop a composite impact measure to identify hotspots of climate change impacts, addressing likelihood and strength of impacts. Overlapping impacts in different biosphere properties (e.g. flooding, yields) will not only claim additional capacity to respond, but will also narrow the options to respond and develop. Regions with severest projected climate change impacts often coincide with regions of high population density and poverty rates. Science and policy need to propose ways of preparing these areas for development under climate change impacts.     

Introduction: food crops in a changing climate

Changes in both the mean and the variability of climate, whether naturally forced, or due to human activities, pose a threat to crop production globally. This paper summarizes discussions of this issue at a meeting of the Royal Society in April 2005. Recent advances in understanding the sensitivity of crops to weather, climate and the levels of particular gases in the atmosphere indicate that the impact of these factors on crop yields and quality may be more severe than previously thought. There is increasing information on the importance to crop yields of extremes of temperature and rainfall at key stages of crop development. Agriculture will itself impact on the climate system and a greater understanding of these feedbacks is needed. Complex models are required to perform simulations of climate variability and change, together with predictions of how crops will respond to different climate variables. Variability of climate, such as that associated with El Ni?o events, has large impacts on crop production. If skilful predictions of the probability of such events occurring can be made a season or more in advance, then agricultural and other societal responses can be made. The development of strategies to adapt to variations in the current climate may also build resilience to changes in future climate. Africa will be the part of the world that is most vulnerable to climate variability and change, but knowledge of how to use climate information and the regional impacts of climate variability and change in Africa is rudimentary. In order to develop appropriate adaptation strategies globally, predictions about changes in the quantity and quality of food crops need to be considered in the context of the entire food chain from production to distribution, access and utilization. Recommendations for future research priorities are given.     

Crop production structure and stability under climate change in South America

Southern South America is expected to play an increasingly important role in global food production, but climate change could seriously threaten it. Here we have analysed long‐term historical data for major crops (rice, oats, barley, sunflower, soybean, sorghum, wheat, maize) at subnational scale to (a) look for common features among crop yield dynamics, evaluating their structure and implications for the persistence of that crop; (b) address complex crop responses to changes in environmental growing conditions; and (c) identify climate impact hotspots that are crucial for adaptation and mitigation. We have proposed a novel methodological approach based on dynamics systems in order to understand the processes behind annual crop yield fluctuations. We report the results of general patterns in the internal process (biophysical adjustments by rapid negative feedbacks) regulating crop production and analyse how it influences crop persistence and yield ceilings. The structure of a crop yield dynamic system defines its behaviour, but climate variations could displace it from yield equilibrium and affect its stability. Our findings suggest that weather conditions have a stronger impact on yield growth at high rather than at low yield levels (non‐additive impacts). This allows agriculture management to be refined and applied more efficiently, weakening the relationship between crop productivity and climate change and predicting the response of crop production to yield‐improvement strategies. We have identified those crops and regions which are most vulnerable to the current climate change trends in southern South American agroecosystems. Our results allow us to point to new ways to enhance self‐regulatory success, maximising the efficiency of crop production and reducing climate impacts. We have discussed important implications for crop management and climate change mitigation in an area where agriculture plays a key role in its socioeconomic and ecologic dimensions.     

Applying climate change refugia to forest management and old-growth restoration

Recent studies highlight the potential of climate change refugia (CCR) to support the persistence of biodiversity in regions that may otherwise become unsuitable with climate change. However, a key challenge in using CCR for climate resilient management lies in how CCR may intersect with existing forest management strategies, and subsequently influence how landscapes buffer species from negative impacts of warming climate. We address this challenge in temperate coastal forests of the Pacific Northwestern United States, where declines in the extent of late-successional forests have prompted efforts to restore old-growth forest structure. One common approach for doing so involves selectively thinning forest stands to enhance structural complexity. However, dense canopy is a key forest feature moderating understory microclimate and potentially buffering organisms from climate change impacts, raising the possibility that approaches for managing forests for old-growth structure may reduce the extent and number of CCR. We used remotely sensed vegetation indices to identify CCR in an experimental forest with control and thinned (restoration) treatments, and explored the influence of biophysical variables on buffering capacity. We found that remotely sensed vegetation indices commonly used to identify CCR were associated with understory temperature and plant community composition, and thus captured aspects of landscape buffering that might instill climate resilience and be of interest to management. We then examined the interaction between current restoration strategies and CCR, and found that selective thinning for promoting old-growth structure had only very minor, if any, effects on climatic buffering. In all, our study demonstrates that forest management approaches aimed at restoring old-growth structure through targeted thinning do not greatly decrease buffering capacity, despite a known link between dense canopy and CCR. More broadly, this study illustrates the value of using remote sensing approaches to identify CCR, facilitating the integration of climate change adaptation with other forest management approaches.     

Ecosystem feedbacks constrain the effect of day-to-day weather variability on land–atmosphere carbon exchange

Whole-ecosystem interactions and feedbacks constrain ecosystem responses to environmental change. The effects of these constraints on responses to climate trends and extreme weather events have been well studied. Here we examine how these constraints respond to changes in day-to-day weather variability without changing the long-term mean weather. Although environmental variability is recognized as a critical factor affecting ecological function, the effects of climate change on day-to-day weather variability and the resultant impacts on ecosystem function are still poorly understood. Changes in weather variability can alter the mean rates of individual ecological processes because many processes respond non-linearly to environmental drivers. We assessed how these individual-process responses to changes in day-to-day weather variability interact with one another at an ecosystem level. We examine responses of arctic tundra to changes in weather variability using stochastic simulations of daily temperature, precipitation, and light to drive a biogeochemical model. Changes in weather variability altered ecosystem carbon, nitrogen, and phosphorus stocks and cycling rates in our model. However, responses of some processes (e.g., respiration) were inconsistent with expectations because ecosystem feedbacks can moderate, or even reverse, direct process responses to weather variability. More weather variability led to greater carbon losses from land to atmosphere; less variability led to higher carbon sequestration on land. The magnitude of modeled ecosystem response to weather variability was comparable to that predicted for the effects of climate mean trends by the end of the century.     

Cutting the Gordian Knot of abiotic stress in grapevine: From the test tube to climate change adaptation

In Mediterranean climate areas, the available scenarios for climate change suggest an increase in the frequency of heat waves and severe drought in summer. Grapevine (Vitis vinifera L.) is a traditional Mediterranean species and is the most valuable fruit crop in the world. Currently, viticulture must adjust to impending climate changes that are already pushing vine‐growers toward the use of irrigation, with the concomitant losses in wine quality, and researchers to study tolerance to stress in existing genotypes. The viticulture and winemaking worlds are in demand to understand the physiological potential of the available genotypes to respond to climate changes. In this review, we will focus on the cross‐talk between common abiotic stresses that currently affect grapevine productivity and that are prone to affect it deeper in the future. We will discuss results obtained under three experimental stress conditions and that call for specific responses: (1) acclimatization of in vitro plantlets, (2) stress combinations in controlled conditions for research purposes, (3) extreme events in the field that, driven by climate changes, are pushing Mediterranean species to the limit. The different levels of tolerance to stress put in evidence by the plasticity of phenotypic and genotypic response mechanisms, will be addressed. This information is relevant to understand varietal adaptation to impending climate changes and to assist vine growers in choosing genotypes and viticulture practices.     

The role of natural regeneration to ecosystem services provision and habitat availability: a case study in the Brazilian Atlantic Forest

Natural regeneration provides multiple benefits to nature and human societies, and can play a major role in global and national restoration targets. However, these benefits are context specific and impacted by both biophysical and socioeconomic heterogeneity across landscapes. Here, we investigate the benefits of natural regeneration for climate change mitigation, sediment retention and biodiversity conservation in a spatially explicit way at very high resolution for a region within the global biodiversity hotspot of the Atlantic Forest. We classified current land‐use cover in the region and simulated a natural regeneration scenario in abandoned pasturelands, areas where potential conflicts with agricultural production would be minimized and where some early stage regeneration is already occurring. We then modeled changes in biophysical functions for climate change mitigation and sediment retention, and performed an economic valuation of both ecosystem services. We also modeled how land‐use changes affect habitat availability for species. We found that natural regeneration can provide significant ecological and social benefits. Economic values of climate change mitigation and sediment retention alone could completely compensate for the opportunity costs of agricultural production over 20 yr. Habitat availability is improved for three species with different dispersal abilities, although by different magnitudes. Improving the understanding of how costs and benefits of natural regeneration are distributed can be useful to design incentive structures that bring farmers’ decision making more in line with societal benefits. This alignment is crucial for natural regeneration to fulfill its potential as a large‐scale solution for pressing local and global environmental challenges.     

Combining field experiments and predictive models to assess potential for increased plant diversity to climate‐proof intensive agriculture

Agricultural production systems face increasing threats from more frequent and extreme weather fluctuations associated with global climate change. While there is mounting evidence that increased plant community diversity can reduce the variability of ecosystem functions (such as primary productivity) in the face of environmental fluctuation, there has been little work testing whether this is true for intensively managed agricultural systems. Using statistical modeling techniques to fit environment–productivity relationships offers an efficient means of leveraging hard‐won experimental data to compare the potential variability of different mixtures across a wide range of environmental contexts. We used data from two multiyear field experiments to fit climate–soil–productivity models for two pasture mixtures under intensive grazing—one composed of two drought‐sensitive species (standard), and an eight‐species mixture including several drought‐resistant species (complex). We then used these models to undertake a scoping study estimating the mean and coefficient of variation (CV) of annual productivity for long‐term climate data covering all New Zealand on soils with low, medium, or high water‐holding capacity. Our results suggest that the complex mixture is likely to have consistently lower CV in productivity, irrespective of soil type or climate regime. Predicted differences in mean annual productivity between mixtures were strongly influenced by soil type and were closely linked to mean annual soil water availability across all soil types. Differences in the CV of productivity were only strongly related to interannual variance in water availability for the lowest water‐holding capacity soil. Our results show that there is considerable scope for mixtures including drought‐tolerant species to enhance certainty in intensive pastoral systems. This provides justification for investing resources in a large‐scale distributed experiment involving many sites under different environmental contexts to confirm these findings.     

Nice weather for bettongs: using weather events,not climate means,in species distribution models

Current applications of species distribution models (SDM) are typically static, in that they are based on correlations between where a species has been observed (ignoring the date of the observation) and environmental features, such as long‐term climate means, that are assumed to be constant for each site. Because of this SDMs do not account for temporal variation in the distribution of suitable habitat across the range of a species. Here, we demonstrate the temporal variability in the potential geographic distributions of an endangered marsupial, the northern bettong Bettongia tropica as a case study. Models of the species distribution using temporally matched observations of the species with weather data (including extreme weather events) at the time of species observations, were better able to define habitat suitability, identify range edges and uncover competitive interactions than models based on static long‐term climate means. Droughts and variable temperature are implicated in low densities and local extinctions of northern bettong populations close to range edges. Further, we show how variable weather can influence the results of competition with the common rufous bettong Aepyprymnus rufescens. Because traditional SDMs do not account for temporal variability of suitable habitat, static SDMs may underestimate the impacts of climate change particularly as the incidence of extreme weather events is likely to rise.     

The agricultural consequences of colonial contacts on the Iberian Peninsula in the first millennium <Emphasis Type="SmallCaps">b</Emphasis>.<Emphasis Type="SmallCaps">c</Emphasis>

The Iron Age archaeobotanical record on the Iberian Peninsula shows how the Phoenician and Greek colonisers caused the indigenous Iberians to change the management of the agricultural resources and the crops which they grew. These colonisers also brought about the development of viticulture and olive cultivation. The importance of agricultural products in the trade network which was stimulated by the colonisers may have encouraged new farming systems, as well as surplus capacity in the native agriculture in the region.     

The overlooked spatial dimension of climate‐smart agriculture

Climate‐smart agriculture (CSA) and sustainable intensification (SI) are widely claimed to be high‐potential solutions to address the interlinked challenges of food security and climate change. Operationalization of these promising concepts is still lacking and potential trade‐offs are often not considered in the current continental‐ to global‐scale assessments. Here we discuss the effect of spatial variability in the context of the implementation of climate‐smart practices on two central indicators, namely yield development and carbon sequestration, considering biophysical limitations of suggested benefits, socioeconomic and institutional barriers to adoption, and feedback mechanisms across scales. We substantiate our arguments by an illustrative analysis using the example of a hypothetical large‐scale adoption of conservation agriculture (CA) in sub‐Saharan Africa. We argue that, up to now, large‐scale assessments widely neglect the spatially variable effects of climate‐smart practices, leading to inflated statements about co‐benefits of agricultural production and climate change mitigation potentials. There is an urgent need to account for spatial variability in assessments of climate‐smart practices and target those locations where synergies in land functions can be maximized in order to meet the global targets. Therefore, we call for more attention toward spatial planning and landscape optimization approaches in the operationalization of CSA and SI to navigate potential trade‐offs.     

Why decadal to century timescale palaeoclimate data are needed to explain present‐day patterns of biological diversity and change

The current distribution of species, environmental conditions and their interactions represent only one snapshot of a planet that is continuously changing, in part due to human influences. To distinguish human impacts from natural factors, the magnitude and pace of climate shifts, since the Last Glacial Maximum, are often used to determine whether patterns of diversity today are artefacts of past climate change. In the absence of high‐temporal resolution palaeoclimate reconstructions, this is generally done by assuming that past climate change occurred at a linear pace between widely spaced (usually, ≥1,000 years) climate snapshots. We show here that this is a flawed assumption because regional climates have changed significantly across decades and centuries during glacial–interglacial cycles, likely causing rapid regional replacement of biota. We demonstrate how recent atmosphere‐ocean general circulation model (AOGCM) simulations of the climate of the past 21,000 years can provide credible estimates of the details of climate change on decadal to centennial timescales, showing that these details differ radically from what might be inferred from longer timescale information. High‐temporal resolution information can provide more meaningful estimates of the magnitude and pace of climate shifts, the location and timing of drivers of physiological stress, and the extent of novel climates. They also produce new opportunities to directly investigate whether short‐term climate variability is more important in shaping biodiversity patterns rather than gradual changes in long‐term climatic means. Together, these more accurate measures of past climate instability are likely to bring about a better understanding of the role of palaeoclimatic change and variability in shaping current macroecological patterns in many regions of the world.     

Climate change and annual survival in a temperate passerine: partitioning seasonal effects and predicting future patterns

Predicting climate change impacts on population size requires detailed understanding of how climate influences key demographic rates, such as survival. This knowledge is frequently unavailable, even in well‐studied taxa such as birds. In temperate regions, most research into climatic effects on annual survival in resident passerines has focussed on winter temperature. Few studies have investigated potential precipitation effects and most assume little impact of breeding season weather. We use a 19‐year capture–mark–recapture study to provide a rare empirical analysis of how variation in temperature and precipitation throughout the entire year influences adult annual survival in a temperate passerine, the long‐tailed tit Aegithalos caudatus. We use model averaging to predict longer‐term historical survival rates, and future survival until the year 2100. Our model explains 73% of the interannual variation in survival rates. In contrast to current theory, we find a strong precipitation effect and no effect of variation in winter weather on adult annual survival, which is correlated most strongly to breeding season (spring) weather. Warm springs and autumns increase annual survival, but wet springs reduce survival and alter the form of the relationship between spring temperature and annual survival. There is little evidence for density dependence across the observed variation in population size. Using our model to estimate historical survival rates indicates that recent spring warming has led to an upward trend in survival rates, which has probably contributed to the observed long‐term increase in the UK long‐tailed tit population. Future climate change is predicted to further increase survival, under a broad range of carbon emissions scenarios and probabilistic climate change outcomes, even if precipitation increases substantially. We demonstrate the importance of considering weather over the entire annual cycle, and of considering precipitation and temperature in combination, in order to develop robust predictive models of demographic responses to climate change. Synthesis Prediction of climate change impacts demands understanding of how climate influences key demographic rates. In our 19‐year mark‐recapture study of long‐tailed tits Aegithalos caudatus, weather explained 73% of the inter‐annual variation in adult survival; warm springs and autumns increased survival, wet springs reduced survival, but winter weather had little effect. Robust predictions thus require consideration of the entire annual cycle and should not focus solely on temperature. Unexpectedly, survival appeared not to be strongly density‐dependent, so we use historical climate data to infer that recent climate change has enhanced survival over the four decades in which the UK long‐tailed tit population has more than doubled. Furthermore, survival rates in this species are predicted to further increase under a wide range of future climate scenarios.     

Impacts of climate change on national biodiversity population trends

Climate change has had well‐documented impacts on the distribution and phenology of species across many taxa, but impacts on species’ abundance, which relates closely to extinction risk and ecosystem function, have not been assessed across taxa. In the most comprehensive multi‐taxa comparison to date, we modelled variation in national population indices of 501 mammal, bird, aphid, butterfly and moth species as a function of annual variation in weather variables, which through time allowed us to identify a component of species’ population growth that can be associated with post‐1970s climate trends. We found evidence that these climate trends have significantly affected population trends of 15.8% of species, including eight with extreme (> 30% decline per decade) negative trends consistent with detrimental impacts of climate change. The modelled effect of climate change could explain 48% of the significant across‐species population decline in moths and 63% of the population increase in winged aphids. The other taxa did not have significant across‐species population trends or consistent climate change responses. Population declines in species of conservation concern were linked to both climatic and non‐climatic factors respectively accounting for 42 and 58% of the decline. Evident differential impacts of climate change between trophic levels may signal the potential for future ecosystem disruption. Climate change has therefore already driven large‐scale population changes of some species, had significant impacts on the overall abundance of some key invertebrate groups and may already have altered biological communities and ecosystems in Great Britain.     

Priority threat management of invasive animals to protect biodiversity under climate change

Climate change is a major threat to global biodiversity, and its impacts can act synergistically to heighten the severity of other threats. Most research on projecting species range shifts under climate change has not been translated to informing priority management strategies on the ground. We develop a prioritization framework to assess strategies for managing threats to biodiversity under climate change and apply it to the management of invasive animal species across one‐sixth of the Australian continent, the Lake Eyre Basin. We collected information from key stakeholders and experts on the impacts of invasive animals on 148 of the region's most threatened species and 11 potential strategies. Assisted by models of current distributions of threatened species and their projected distributions, experts estimated the cost, feasibility, and potential benefits of each strategy for improving the persistence of threatened species with and without climate change. We discover that the relative cost‐effectiveness of invasive animal control strategies is robust to climate change, with the management of feral pigs being the highest priority for conserving threatened species overall. Complementary sets of strategies to protect as many threatened species as possible under limited budgets change when climate change is considered, with additional strategies required to avoid impending extinctions from the region. Overall, we find that the ranking of strategies by cost‐effectiveness was relatively unaffected by including climate change into decision‐making, even though the benefits of the strategies were lower. Future climate conditions and impacts on range shifts become most important to consider when designing comprehensive management plans for the control of invasive animals under limited budgets to maximize the number of threatened species that can be protected.     

Weather patterns, food security and humanitarian response in sub-Saharan Africa

Although considerable achievements in the global reduction of hunger and poverty have been made, progress in Africa so far has been very limited. At present, a third of the African population faces widespread hunger and chronic malnutrition and is exposed to a constant threat of acute food crisis and famine. The most affected are rural households whose livelihood is heavily dependent on traditional rainfed agriculture. Rainfall plays a major role in determining agricultural production and hence the economic and social well being of rural communities. The rainfall pattern in sub-Saharan Africa is influenced by large-scale intra-seasonal and inter-annual climate variability including occasional El Ni?o events in the tropical Pacific resulting in frequent extreme weather event such as droughts and floods that reduce agricultural outputs resulting in severe food shortages. Households and communities facing acute food shortages are forced to adopt coping strategies to meet the immediate food requirements of their families. These extreme responses may have adverse long-term, impacts on households' ability to have sustainable access to food as well as the environment. The HIV/AIDS crisis has also had adverse impacts on food production activities on the continent. In the absence of safety nets and appropriate financial support mechanisms, humanitarian aid is required to enable households effectively cope with emergencies and manage their limited resources more efficiently. Timely and appropriate humanitarian aid will provide households with opportunities to engage in productive and sustainable livelihood strategies. Investments in poverty reduction efforts would have better impact if complemented with timely and predictable response mechanisms that would ensure the protection of livelihoods during crisis periods whether weather or conflict-related. With an improved understanding of climate variability including El Ni?o, the implications of weather patterns for the food security and vulnerability of rural communities have become more predictable and can be monitored effectively. The purpose of this paper is to investigate how current advances in the understanding of climate variability, weather patterns and food security could contribute to improved humanitarian decision-making. The paper will propose new approaches for triggering humanitarian responses to weather-induced food crises.     

Multi-agent modelling of climate outlooks and food security on a community garden scheme in Limpopo, South Africa

Seasonal climate outlooks provide one tool to help decision-makers allocate resources in anticipation of poor, fair or good seasons. The aim of the 'Climate Outlooks and Agent-Based Simulation of Adaptation in South Africa' project has been to investigate whether individuals, who adapt gradually to annual climate variability, are better equipped to respond to longer-term climate variability and change in a sustainable manner. Seasonal climate outlooks provide information on expected annual rainfall and thus can be used to adjust seasonal agricultural strategies to respond to expected climate conditions. A case study of smallholder farmers in a village in Vhembe district, Limpopo Province, South Africa has been used to examine how such climate outlooks might influence agricultural strategies and how this climate information can be improved to be more useful to farmers. Empirical field data has been collected using surveys, participatory approaches and computer-based knowledge elicitation tools to investigate the drivers of decision-making with a focus on the role of climate, market and livelihood needs. This data is used in an agent-based social simulation which incorporates household agents with varying adaptation options which result in differing impacts on crop yields and thus food security, as a result of using or ignoring the seasonal outlook. Key variables are the skill of the forecast, the social communication of the forecast and the range of available household and community-based risk coping strategies. This research provides a novel approach for exploring adaptation within the context of climate change.     

Climate-Induced Changes in Grapevine Yield and Must Sugar Content in Franconia (Germany) between 1805 and 2010

When attempting to estimate the impacts of future climate change it is important to reflect on information gathered during the past. Understanding historical trends may also aid in the assessment of likely future agricultural and horticultural changes. The timing of agricultural activities, such as grape harvest dates, is known to be influenced by climate and weather. However, fewer studies have been carried out on grapevine yield and quality. In this paper an analysis is undertaken of long-term data from the period 1805–2010 on grapevine yield (hl/ha) and must sugar content (°Oe) and their relation to temperature. Monthly mean temperatures were obtained for the same time period. Multiple regression was used to relate the viticulture variables to temperature, and long-term trends were calculated. Overall, the observed trends over time are compatible with results from other long term studies. The findings confirm a relationship between yield, must sugar content and temperature data; increased temperatures were associated with higher yields and higher must sugar content. However, the potential increase in yield is currently limited by legislation, while must sugar content is likely to further increase with rising temperatures.