A Climate Suitability Model for Olive Cultivation in Greece ^†

Abstract

To effectively adapt the agricultural sector to the threats posed by climate change, it is essential to provide tools to establish a link between climate conditions and crops. The olive is a significant crop in the Mediterranean area. Although highly acclimated, specific climatic and geomorphological conditions are required to achieve sufficient performance. By considering the already recorded impacts of extreme weather on the olive groves, a simple climate-suitability model is implemented to assess the feasibility of olive cultivation in diverse areas of Greece. By incorporating fundamental climatic factors (e.g., temperature, precipitation) and geomorphological elements (e.g., elevation, slope), the model generates a thematic map for Greece, allocating suitability scores corresponding to its suitability for olive farming in any area of interest. The model may be utilized as an adjustable tool for monitoring changes in climate suitability through different time scales.

1. Introduction

The olive tree, Olea (Olea europaea L.), constitutes the most extensive cultivation in Greece, which surpasses Spain and Italy in terms of production globally [1]. As such, oliviculture and its products comprise an integral developmental factor, essentially contributing to the country’s socio-economic prosperity while performing a vital ecological role and benefiting human health [2,3].

The olive’s developmental attributes are highly linked with fundamental climatic parameters representative of the Mediterranean-type climate [4]. Specific air temperature values may impede olive growth and limit productivity. The optimal growing season temperature range is approximately 20–30 °C, while extreme deviations (e.g., freezing temperatures below −10 °C in winter and peaking values of nearly 50 °C in hot and dry summers) may cause higher risks of infection phenomena, irreversible damage of the olive’s organs, and complete tree destruction and death. It is characteristic that in Greece, frost ranks first in the hierarchy of extreme phenomena accountable for significant olive crop production declines [5,6,7]. Precipitation also comprises an essential climatic parameter that exerts influence on the olive’s productivity dynamics [8]. However, a species of documented high resistance to water deficiency and increased production of the olive orchard coincide with incidents of high rainfall during specific months of the year [9].

The modeling of olive cultivation has drawn scientific attention in recent years given the extreme weather phenomena, which are gaining ground in terms of intensity and frequency owing to climate change and may seriously threaten the quality and quantity of production [4]. Some of the applications of modeling may include the identification of suitable areas for olive cultivation based on suitability maps involving pedoclimatic parameters [10], the monitoring of crop growth under different environmental conditions [11], and the forecasting of olive pest infestations [12].

Implementing several simulation models in Greek olive oil producing areas for several purposes has been documented. This involves, for example, the monitoring of pest and insect population dynamics [13], disease infection forecasting [14], plant stress detection [15], projections on water demands [16], and exploration of climate change impacts on production [17]. However, there is an absence of surveys relative to the climate suitability evaluation of the specific cultivation in individual regions of Greece and far more over the Greek Peninsula.

By accounting for the vulnerability of olive groves’ productive capacity owing to extreme weather events, as triggered by climate change, a simple climate-suitability model for the assessment of the olive cultivations’ sustainability in Greece is implemented. For the realization of this purpose, a conjunction between the geomorphological data of Greece (elements such as elevation and slope) and the required atmospheric conditions for the specific crop’s development and growth (such as temperature and precipitation) has been accomplished.

2. Materials and Methods

The study area is Greece (38.85° N 24.4° E), located in the southern part of the Balkan area, with a total surface of 131.957 km². Nearly 80% of this area is continental, while 20% is divided among ~3.000 islands (52 apo Athina).

A digital elevation model (DEM) with a spatial resolution of 250 m was applied to generate the necessary data for the area’s suitability assessment. From this dataset, spatial operations were performed to initiate digital data relative to the geomorphological indicators of aspect, slope, terrain roughness, and elevation [18,19,20]. A Corine Land Cover dataset was exploited to compare the present study’s olive cultivation suitability results with olive cultivation locations illustrated for the year 2018 (CLC, 2018).

From a climatic perspective, data from the WorldClim dataset were exploited. The spatial resolution is very high (~1 km), and this characteristic, along with the high reliability and the wide usability of the research community, was of utmost importance in our choice [20,21,22,23,24]. Spatial operations were conducted for the generation of digital data involving the climatic indicators of temperature (mean minimum values from November to March, mean January values, mean July values, and mean annual values), precipitation (annual precipitation), and frost days (annual number of frost days, spring frost days) [24]. Thus, a total of 11 parameters were utilized for the construction of the model. Every parameter has been reclassified to translate its value to a score. In case a parameter has a zero score in a pixel, this pixel is excluded from the suitability classification. So, the final map is the product of the aggregation of all score maps per pixel (Figure 1).

The R language was applied for the utility, management, analysis, and visualization of the overall applied geomorphological and climatic data, as it constitutes an appropriate tool for exploiting large volumes of data and creating maps and visualizations.

Comprehensive maps depicting the best distribution/scoring of olive cultivation from a climatic and geomorphological perspective and the conjunction of both elements are illustrated over the entire area without further interventions.

3. Results and Discussion

The resulting olive geomorphological suitability map over Greece is shown in Figure 2. The presented color scale depicts the geomorphological suitability scores (from a value of 0 (worst minimum score) to a value of 19 (optimal maximum score)). The geomorphological suitability of each point on the map is formed by combining the results obtained from each of the parameters (aspect, slope, terrain roughness, and elevation) for each point. The overall score of each point is obtained by adding up the individual scores of each point in the individual maps on all geomorphological indicators.

As illustrated, many points correspond to the optimal suitability scores for olive cultivation. However, there are also points that correspond to lower scores and zero scores, with the latter considered relative to locations unsuitable for olive cultivation regardless of other criteria. Overall, the geomorphology of Greece may be characterized as ideal for olive cultivation, except mainly for its mountainous areas (mountainous points), where most geomorphological parameters correspond to the lowest score. The olive tree appears to be optimally grown in most of northeastern Greece, in a significant part of central Greece, in most of the Peloponnese region, on many islands, and partly in the country’s western side.

The overall score of each point of the resulting final climate suitability map is shown in Figure 3. The mapping is obtained by adding up the individual scores of each point in the individual maps on all climatological indicators: maps of temperature parameters (mean minimum values from November to March, mean January values, mean July values, mean annual values) and of frost days (annual number of frost days, spring frost days). The resulting overall suitability map for olive cultivation in Greece is analyzed by a color scale corresponding to the aggregation of the climatic and geomorphological suitability.

As demonstrated, a substantial part of Greece is rated with zero, pinpointing thus many parts of the country as climatically unsuitable for olive cultivation. These parts include most areas of Northeastern and Central Greece and Central Peloponnese, especially those located in the continental and mountainous regions. The same situation results for the Attica region and in minor parts of various islands, where the zero score may be attributed to either low rainfall or high temperature or to a combination of both. However, many areas in Central and Southern Greece result as suitable for the olive grove, while in several others, although not corresponding to ideal conditions, the cultivation may be developed.

The final suitability map for olive cultivation in Greece results from combining the overall geomorphological and climatic score maps (Figure 2 and Figure 3, respectively) and is demonstrated in Figure 4. The final score of each point was obtained by adding its individual score derived from the geomorphological and climatic maps, except for the points that were rated as unsuitable at least in one of the two maps. The final suitability map with respect to all the parameters examined (geomorphological and climatic) is accompanied by a color scale depicting the respective climatic suitability score, ranging from the worst minimum score of 0 to the optimal maximum score of 97.

According to the resulting suitability map, a significant part of the country is identified as unsuitable for olive cultivation (score 0). This fact is mainly attributed to the prevailing climatic conditions and the mountainous terrain that characterizes most of these areas. The unsuitability arises throughout Greece, mainly in the country’s Northern and Central parts and mountainous regions. Several areas characterized by improved suitability scores are observed further south. Although the combination of both climatic and geomorphological parameters may form a prohibitive environment for oliviculture in a significant part of the investigated area (score of 0), it is demonstrated that good and high scores correspond to several places across the country. Thus, Greece partly appears to possess ideal conditions for olive growth, which documents the widespread appearance of oliviculture in spatially extensive areas. At this point, it is imperative to emphasize that these results are derived by considering only climate and geomorphology components without any other interventions (e.g., irrigation effects and assessments on the impacts of climate change).

To assess the performance of the applied model, a reverse process was conducted starting from locations identified as olive crops by the Corine Land Cover (CLC) dataset in Greece [25]. Figure 5 shows the distribution of suitability score values for the recorded olive crop positions.

Over 85% of the crop’s positions achieved a suitability score above 80, while less than 0.3% scored below 70. These results support the validity and soundness of the proposed model.

4. Conclusions

The conclusions deduced from the present investigation can be summarized as:

• Individually, the overall geomorphological and climate suitability for oliviculture is high in Greece. Overall, the olive suitability model may be characterized as efficient. The observed differentiations of the model-derived final suitability map from the recorded olive-growing areas over Greece may be justified by the application of limited climate and geomorphology components in the model. The present modeling procedure may serve as a tool for indicating suitable areas for the development of sustainable and productive olive culture. The model is defined by its simplicity, usability, and flexibility. As the modelling process is new, it requires evaluation and adjustments to improve accuracy. Additionally, incorporating environmental parameters affected by future climate change could generate an updated map of climatic suitability.