Future Scenarios for Olive Tree and Grapevine Potential Yields in the World Heritage Côa Region, Portugal

Abstract

In the World Heritage Côa region, in northern Portugal, agriculture has crucial economic, social and cultural importance. Vineyards and olive groves are part of the economic base of this region, contributing to the regional commercial budget and the livelihood of its residents. Climate change is expected to have significant impacts on these crops, where climatic conditions are already very warm and dry, posing a key threat to the olive oil and winemaking sectors. The present study analyzes the impact of climate change on the potential yield of these two crops over the Côa region. For this purpose, two crop models were initialized and ran with state-of-the art spatial datasets for climate, soil, terrain, and plant data. As outputs of the crop models, potential yields of grapevines and olive trees were obtained for the recent-past (1981–2005) and for the future (2041–2070), under two climatic scenarios (RCP4.5 and RCP8.5). Results (potential yield) were then normalized, taking into account the recent-past maximum yields and divided into four classes (low, low-moderate, moderate-high, and high). For the recent-past, the results of the crop models present a high agreement with the current location of vineyards and olive groves. For the future, two different types of impacts (positive and negative) are found for the two crops. For olive trees, the results show promising future improvements in possible expansion areas within the Côa region. However, for grapevines, the results show a decrease in potential yields throughout the region, including a strong shift of producing moderate zones to low potentials. Nonetheless, these results also suggest that the negative impacts of climate change can be alleviated by the application of suitable adaptation measures, based on changing certain management practices, even in the more severe future scenario. Therefore, these measures should be carefully planned and implemented in a timely fashion by farmers.

Grapevine Sugar Concentration Model (GSCM): A Decision Support Tool for the Douro Superior Winemaking Region

“…The DS winemaking region is located in a "climate change hotspot", meaning that the impacts of climate change in this region may be particularly severe [42]. Current studies indicate that this particular sub-region of the Douro PDO may be negatively affected in terms of viticultural productivity [43], particularly due to the increase in extreme weather events [42,44]. In effect, climate change impacts on viticulture are already being reported in different regions worldwide, such as the shift in phenology, higher sugar concentration, and late spring frost problems [45][46][47][48][49].…”

“…In effect, climate change impacts on viticulture are already being reported in different regions worldwide, such as the shift in phenology, higher sugar concentration, and late spring frost problems [45][46][47][48][49]. Although the grapevine is a very resilient species to adverse climatic conditions, future climates may threaten the winemaking economic revenue in this region [43]. Grapevine phenology is being increasingly modified by higher temperatures in DS, enhancing the need for adaptation strategies, in both the short [17] and long term [18].…”

Determining the Climatic Drivers for Wine Production in the Côa Region (Portugal) Using a Machine Learning Approach

“…Under climate change, the projected future warming and drying in the Côa [5] may bring further challenges to local winemakers, which further highlights the need to use advanced tools to forecast crop production, or in this case, WP. In effect, several studies suggest that the winemaking industry should focus on minimizing the impact of yearly yield fluctuations and optimizing production [52].…”

“…It is widely acknowledged that climatic factors exert a significant influence on grapevine physiology, phenology, and productivity, profoundly shaping the agricultural suitability of a given winemaking region [3,4]. Considering the unique climatic conditions in the area, characterized by warm, dry summers and wet, moderately cold winters typical of Mediterranean-like climates, grapevines tend to thrive in this environment [5]. The complex interplay of climatic factors on grape yields remains an area of ongoing research with numerous challenges and uncertainties [6].…”

Pollen- and Weather-Based Machine Learning Models for Estimating Regional Olive Production

“…However, although pollen is important from the point of view of forecasting production, it cannot be the only factor considered since there are other external factors that can condition production both in terms of quality and quantity, such as atmospheric and physiological conditions arising from lack of water and extreme temperatures, as well as the occurrence of phytopathological problems [26,29,34,37]. Hence, forecasting olive production remains of key importance, particularly under the predicted climate change challenges for this sector [38,39].…”