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Article

Horticultural Farmers’ Perceived Risk of Climate Change in Adriatic Croatia

by
Milan Oplanić
1,
Ana Čehić Marić
1,
Smiljana Goreta Ban
2,
Tajana Čop
3,* and
Mario Njavro
3
1
Department of Economics and Agricultural Development, Institute of Agriculture and Tourism, 52440 Poreč, Croatia
2
Department of Agriculture and Nutrition, Institute of Agriculture and Tourism, 52440 Poreč, Croatia
3
Department of Management and Rural Entrepreneurship, Faculty of Agriculture, University of Zagreb, 10000 Zagreb, Croatia
*
Author to whom correspondence should be addressed.
Sustainability 2023, 15(1), 539; https://doi.org/10.3390/su15010539
Submission received: 24 October 2022 / Revised: 16 December 2022 / Accepted: 22 December 2022 / Published: 28 December 2022
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Abstract

:
Parts of the Mediterranean, including Adriatic Croatia, are becoming more exposed to climate risk. Changes in precipitation, temperature, and the occurrence of extreme weather events are increasingly significant. The paper aimed to identify the level of the perceived risk of climate change on the sample of horticultural farmers in the Adriatic Croatia. Furthermore, the paper aimed to research which risk management strategies are preferable to producers to reduce the impact of climate change on agricultural production. The survey was conducted among horticultural farmers in Adriatic Croatia (Mediterranean). The method used in the paper was cluster analysis, and the farmers’ readiness to apply climate risk management strategies was additionally examined using ANOVA and the HSD Tukey test. The main results showed that on the sample of 275 horticultural farmers, 57.81% were climate sceptics. In contrast, the climate aware farmers were more ready to apply measures to adapt production strategies and risk reduction measures in response to a changing climate. Finally, the limitations of the research and future research are discussed in this paper.

1. Introduction

Climate change (CC) impacts agricultural production, considering that climate conditions determine farming activities [1]. In agriculture, CC may cause significant damage that is hard to prevent [2,3]. Few papers have emphasized the increased impact of CC on the south of Europe and the Mediterranean [4,5,6]. Climate change, in general, represents a change in the average conditions such as temperature and rainfall. In the Mediterranean, climate change occurs as a decrement in precipitation, temperature increment, and the occurrence of pests, diseases, and weather and climate extreme events (drought, hail, frost, floods, storm, fire), and has impacts on agricultural production (e.g., yield reduction [7]). In addition, the consequences of CC such as the variability of food prices, food security, land use, and increasing uncertainty for farmers’ businesses [8] are seen in the past and present, and are expected to have a high impact in the future [9]. Abbass et al. found that climate change will globally affect crop productivity dramatically in the next few decades [10].
In Croatia, research has shown that an increase in air temperatures up to 2070 is expected. For example, up to 2070, the winter temperature will increase up to 1.6 °C in the Adriatic area, and in summer up to 3 °C [11,12]. On the other hand, precipitation is expected to decrease during the summer in Adriatic Croatia.
Adriatic Croatia (AC) is part of the Mediterranean region that is more exposed to climate change than Continental Croatia [13]. In Croatia, there are more than 1.4 million hectares of utilized agricultural areas (UAA), 58% is arable land, 37% is permanent grassland, while that under permanent crops (horticulture—vineyards, orchards, and olive groves) is only 5.24%. In Adriatic Croatia, there are 441 thousand hectares of UAA. If we consider horticultural production in Croatia, permanent crops (vineyards, orchards, olive) are 5%; in AC, 8.41%, and areas under vegetables are only (1678 ha) 0.11% of UAA or 0.12% in AC. Despite the favorable agroecological conditions, Croatian horticultural production has low level of self-sufficiency, low added value, low competitiveness, and the low willingness of the producers to cooperate, which consequently limits its market access [14].
It is predicted that frost, hail and an increasingly frequent occurrence of drought will have the greatest impact on horticultural production sector in Croatia [15]. Oplanić et al. found that farmers in Croatia primarily perceive a decrease in precipitation and drought as an obstacle in their production [16]. It was shown that the occurrence of hail affected the reduction of grape yield by 40–50% [17], whereas olive yield was decreased by 7% due to rainfall decrease [18].
Climate change causes significant economic losses worldwide. From 1980 to 2020, economic losses from weather and climate-related extremes were around EUR 450–520 billion among EEA countries (EU member states plus Iceland, Liechtenstein, and Norway), and only between one-quarter and one-third of these losses were insured [19]. For example, in Europe in 2003, economic losses were USD 12 billion only in agriculture caused by heatwaves [20]. The average reported damage (2013 to 2019) in Croatia in agriculture amounted to EUR 150 million, while the most significant damage was recorded in 2017 at EUR 314 million [21]. Croatia has the lowest value of insured economic losses (0.5–1.5%) among EEA member countries [19].
Some research has shown that farmers are aware of CC and its impact on farm production and business [22]. Farmers in Italy, Germany, and France face the impact of CC on the production aspect, the quality and quantity of grapes as well as disease occurrence (e.g., [23]) which also affects the financial side of production (production costs, revenue, income/profit) [24]. In general, 75% of the maize farmers in Ethiopia experienced CC on their crops and were aware of CC [25]. On the other hand, farmers in Bangladesh had a moderate perception of CC vulnerability [26]. On the other hand, horticultural farmers in Ghana showed high vulnerability to CC, and coastal areas in Ghana are more exposed to CC vulnerability than areas not in the coastal part [27]. Otherwise, farmers in Denmark are not concerned about the impacts of CC. However, research has shown that if a farmer is more concerned about CC, farmers are also eager to adapt to CC using adaptation strategies [28]. In Italy, 84% of horticultural farmers indicated that seasons have changed, the temperature has increased, droughts are frequent, and unusual rainy events have occurred in the last 20 years, indicating that such changes are difficult to predict [1]. Nguyen et al. found that horticultural farmers in Italy believe that CC lead to crop damage from heat waves, production losses, diseases, increased water use, and higher costs (costs of management, pesticide, production inputs, labor, and irrigation costs).
To manage risks, farmers can use on-farm strategies and risk transfer strategies (common referred to as ex-ante strategies) or ex-post strategies. On-farm strategies include product or revenue diversification, infrastructure or storage capacities investment, production technology, cooperation, or simply gathering information, knowledge, and consulting. From risk transfer strategies, farmers can apply for agricultural insurance, asset insurance, negotiate contract production, or apply hedging as a financial instrument [29].
Abbass et al. summarized the mitigation and adaptation strategies [10]. Adaptation strategies include agroforestry, sustainable practices, education, and water conservation. Mitigation strategies include mixed-cropping and intercropping, reduced soil tillage, terracing, contouring, and tolerant crop cultivars. In addition, mix production (livestock and crop production) is considered as a mitigation and adaptation strategy [10].
To cope with the risks of CC, horticultural farmers in Italy (as part of the Mediterranean region) have adopted new agronomic practices, diversified crops, worked on improving irrigation systems, and, not less importantly, followed the daily weather forecasts. Furthermore, in the future, horticultural farmers plan to ensure sustainable water use at their farms and interact with advisors and colleagues using social networks (e.g., [1]). Furthermore, wine farms can use a decision support system to help decrease the economic damage from climate change [30]. In addition, Malhi et al. concluded that applying water-, nutrient-, weather-, carbon-, and knowledge-smart activities could minimize the negative impact of climate change on agricultural production [31].
To further manage the risks, the European Commission (EC) has introduced three instruments for risk management in agriculture: subsidized agricultural insurance, mutual funds, and an income stabilization tool. So far, subsidized agricultural insurance is applied among all member states, while the income stabilization tool is introduced in Italy [32]. Previous experiences of mutual funds can be seen in the Netherlands, Romania, Italy, and France [33,34,35].
The literature shows fewer papers that have researched the farmers’ perceptions of CC in (Mediterranean) Europe e.g., [1,23] and there are no papers that examine farmers’ perceptions of CC in Croatia (in the horticultural sector). Therefore, this paper provides valuable information for boosting knowledge about the perception of the farmers on climate change and the design and updating of agricultural policies and programs in climate change adaptation and mitigation [36].
The paper aimed to identify the perceived risk of climate change on a relevant sample of farmers in the Adriatic Croatia and detect which risk management strategies are preferable to producers to reduce the impact of climate change on agricultural production. The authors use the term risk management strategies in the paper as a common name for adaptation measures and risk reduction measures.
The rest of this paper is organized as follows. Section 2 provides a description of the study area and the methodological approaches; Section 3 presents and discusses the empirical results; while Section 4 summarizes and emphasizes the main conclusions of the paper.

2. Materials and Methods

The research was conducted in Adriatic Croatia. In this region, the consequences of climate change are more pronounced, and most of the region’s territory has a typical Mediterranean climate. Adriatic Croatia is one of four NUTS—two classification regions and includes seven counties. The survey was conducted within the area of six counties. Lika-Senj county was excluded from the survey, as there is very little horticultural production there, mainly due to harsh (mountain) climate, which prevents the propagation of olives, grapevines, and most vegetable crops, which are the subject of the survey. The number of farms and territorial distribution is shown in Table 1.
According to the data in Table 1, it is evident that there were differences in the number and size of the agricultural holdings in the researched area. The researched area has some differences in the pedo-climatic conditions, which also explains the difference in the structure of production in each county. Figure 1 shows a map of the researched counties (left) and the distribution of surveyed farmers across Adriatic Croatia (right).
The data collection took place between October 2020 and June 2021. It should be noted that data collection was hampered due to the situation with the COVID-19 pandemic, where interpersonal contacts were significantly reduced, and it was not possible to conduct a face to face survey on the sample of farmers. For data collection, an online questionnaire was used. This method of data collection automatically excluded producers who do not have access to the Internet. Producer contacts were found through multiple sources (list of producers at the Paying Agency for Agriculture and Rural Development, producers listed at different agricultural associations, etc.). In addition, each farmer was contacted and informed by telephone about the research being conducted. Upon their consent, an email containing a questionnaire in Microsoft Forms was promptly sent. Respondents were guaranteed anonymity, and it was not possible to connect answers with the identity of a particular farmer. The length of the online questionnaire was 10 min. The planned number of collected questionnaires per county followed the structure of the producers’ population, as shown in Table 1.
The questionnaire consisted of several sets of questions including questions about the perceived risk of the impact of climate change on businesses, questions about climate change adaptation measures as well as questions relating to the socio-demographic and economic characteristics of the respondents. Arbuckle et al.’s research was used as a basis for the perceived risk statements, which were additionally modified for this study [43]. The statements were assessed on a Likert scale from 1 (complete disagreement with the statement) to 5 (complete agreement with the statement). This is a psychometric scale commonly used in questionnaires and is the most frequent used scale in survey research. At the end, a total of 275 fully completed questionnaires were collected.

Data Analysis

Following the data collection process, data analysis was performed. The data were processed using SPSS package version 26. First, the data were described through descriptive statistics or frequencies, after which a ‘two-step cluster analysis‘ was carried out on a set of perceived risk statements on the impact and consequences of climate change with the addition of the socio-demographic characteristics of the respondent. The use of two-step cluster analysis sought to identify characteristic clusters in light of the perceived risk of climate change. Two-step cluster analysis was preferred because it enables the analysis of categorical and continuous variables together [44,45]. Once the clusters were identified, the willingness to apply specific climate change adaptation measures was verified by applying ANOVA and the HSD Tukey test.

3. Results and Discussion

According to the data collected, the sample of producers was dominated by older (52–65), males, who had completed non-agricultural secondary studies. For a majority of the interviewed farmers, agriculture was a complementary source of income in the household. Generally, slightly more respondents came from Split-Dalmatia County (32%) and were chiefly involved in olive growing (Table 2).
The participants of this study had a relatively neutral perceived risk toward the impact and consequences of climate change and the robustness of the scale was good with a medium Cronbach’s alpha (Table 3).
Two-step cluster analysis of a set of questions on perceived risk spawned two clusters (Table 4).
Cluster description:
Cluster 1, Climate sceptics
(N = 159, 57.81%)
Climate sceptics is a slightly larger cluster including respondents who have a low level of concern about the potential risk that climate change can cause to their businesses. They do not consider the individual adaptation measures for their businesses such as measures to adapt the production structure and risk reduction measures to be significant.		Cluster 2, Climate aware
(N = 116, 42.19%)
Climate aware consists of a smaller cluster, which brings together respondents who perceive climate change and recognize the potential risk they may pose to their businesses. Adaptation measures such as measures to adapt the production structure and risk reduction measures are considered important in their case.
In terms of socio-demographic characteristics, these consist mainly of older respondents—above the age of 61, who are predominantly male, with non-agricultural secondary education. Agricultural production to them is a complementary source of revenue, largely in the form of vegetable production.This cluster includes slightly younger respondents, featuring predominantly males, with non-agricultural higher education, whilst agricultural production is considered a complementary source of revenue, largely in the form of growing perennial olive crops and grape growers.
It is important to know which adaptation measures producers are inclined to take in mitigating the consequences of climate change. The proposed measures were divided into three categories: production structure adaptation measures, production technology adaptation measures, and risk mitigation measures. Production structure adaptation measures refer to measures related to production itself such as a shift to varieties that are more tolerant to drought, frost and shift to new cropping areas, changing the production structure, targeting organic production, etc. On the other hand, production technology adaptation measures are measures related to agricultural technology and tillage. Risk mitigation measures are risk reduction measures in the form of crop insurance, the establishment of a public hail damage prevention system and low temperature damage prevention system. Figure 2, Figure 3 and Figure 4 show the ratings or the importance of individual sets of measures for producers.
The farmers have highlighted the shift to organic production as the most important production structure adaptation measure, while the shift to new cropping area was evaluated as the least important measure (Figure 2).
Of the proposed production technology adaptation measures the best rating was observed for the application of irrigation, and the least rated was the increased use of pesticides (Figure 3).
When the importance of risk mitigation measures was questioned the famers consider almost all mitigation measures important to adapt to climate change (>3.6 score), except the score for more frequent crop and asset insurance (3.2) (Figure 4).
The following tables (Table 5 and Table 6) verify the existence of differences between the two clusters identified and the application of the proposed climate change adaptation measures, namely, the application of production structure adaptation measures, production technology adaptation measures, and risk mitigation measures. The difference between the two clusters was checked using the ANOVA test.
The scores in the Table 5 show that the climate aware cluster was more inclined to apply measures to adapt the production structure than climate sceptics, according to almost all statements except the statement Targeting organic production, where no difference between the two clusters was identified.
No difference between the two clusters was identified in the production technology adjustment measures.
Based on the results of this survey, it seems that the respondents are relatively neutral about the impact and consequences of climate change. The respondents were only more concerned with the statement that climate change presents a significant problem for the regular activity (mean 3.62) of their farm business. Farmers least agreed with the statement that climate change is increasing yearly (mean 3.33) and cause frequent and severe damage to the farm business (mean 3.44). Three-quarters of farmers in Finland agreed that climate change threatened agriculture worldwide [36]. Ozor and Cynthia concluded that climate change resulted in different problems (e.g., problems linked to the sustainability of the environment, resource management, and problems in population and food consumption) [47].
In the proposed research, farmers from the Adriatic Croatia are likely to be climate sceptics, which is similar to Islam et al. [48], who researched that Scottish dairy farmers were climate sceptics. For comparison, De Jalon et al. stated that climate-aware farmers prevailed, and only 5% of farmers were climate sceptics in Makueni County in Kenya [49]. Additionally, farmers in Sahel and Finland were also climate aware [36,50]. A research gap was found in a comparison of our results (horticultural farmers—climate aware/sceptics) with previous papers that had researched horticultural farmers that was scarce, especially in the Mediterranean region.
In the case of risk management strategies, a slightly higher number of climate aware farmers showed a tendency for strategies in general compared to the climate sceptics. In contrast, no differences were found between the two clusters for some strategies. Climate-aware farmers were more willing to apply strategies related to production structure as an adaptation on the farm. Production structure means sowing resistant crops, choosing new cropping areas, implementing organic agriculture, and increasing production areas. A few studies have concluded that organic producers are more climate aware and ready to adapt to CC by implementing organic practices [51,52,53]. However, we cannot claim a statistically significant difference between clusters in this research. Fachrista et al. concluded that horticultural (vegetable) farmers preferred implementing mixed cropping, crop rotation, and mulch [52]. Rijal et al. highlighted that Nepalese farmers considered important livelihoods and income diversification and agricultural practices [54]. Furthermore, Marie et al. concluded that farmers in Ethiopia applied mixed farming, mixed cropping, changing sowing period, irrigation, drought-resistant crop varieties, and conservation techniques as well as shifting to non-farm income activities [55]. Sorvali confirmed that adaptation process is carried out on the farm and primarily represented the maintenance of good soil health, while mitigation was more linked with changes in agricultural policies [36].
If we consider risk reduction measures, the climate-aware respondents applied and preferred public irrigation and drainage systems, crop and assets insurance, subsidized insurance policies, and timely information about climate change. Climate-aware farmers applied agricultural and asset insurance rather than the climate sceptics and preferred more favorable insurance policies. For example, Nnadi et al. concluded that insurance, as well as, other risk transfer strategies could help farmers to manage climate risks [56]. Specifically, it should strive for modern agriculture that needs to be climate smart (climate smart agriculture—CSA), which links sustainable development, climate change adaptability, and mitigation and decreases greenhouse gas emissions from agriculture [16].

4. Conclusions

With a study in the Adriatic Croatia (Mediterranean region), the paper has provided new findings to the scarce literature that researched and compared two clusters (climate sceptics and climate aware) and their readiness to apply different strategies to cope with climate change in Adriatic Croatia. Cluster analysis was applied, while readiness to apply strategies among clusters was analyzed using ANOVA and the Tukey test.
From the completed analyses, it can be concluded that in the sample, farmers were primarily male, older farmers who completed non-agricultural secondary schools. The most significant share of farmers was olive growers in Adriatic Croatia, which represented the highest share (33.3%) of total farms, which as mentioned, follows the distribution in the population. In the sample, farmers mostly agreed that climate change presents a problem for regular activity on the farm. Nevertheless, farmers were neutral to the statement that climate change increases risk in the farm business. In addition, the paper differed farmers into two clusters: climate sceptics and climate-aware farmers. More than half of the sample (57%) stated themselves to be climate sceptics.
One of the limitations of this research was only having a sample from the Adriatic Croatia. Even though we researched farmers from the Adriatic Croatia who were more exposed to climate change and weather events, we cannot neglect farmers from the Continental region. Therefore, future research can incorporate climate-perceived risk and adaptation strategies from farmers in the Continental region.
The results of the study can be used by agricultural extension services, for example, to increase farmer’s awareness about climate change and potential economic losses on the farm. They can help farmers e.g. with timely information to adapt more quickly to the changes and to build up resilience of their farms. The results can help policy makers adopt and develop adaptation and mitigation strategies such as access to climatic information and information needed for business decisions (weather alert, price variability), and development of public drainage and irrigation systems.
To better design and develop mitigation and adaptation strategies for farmers, the first step needs to be understanding the farmers’ behavior. Behavioral economics can be used and applied in future research to assume the farmers’ behavior and what affects the farmers’ choice of adaptation or mitigation strategy. Čop and Njavro stated that a discrete choice experiment as the experimental method can be used to examine the farmers’ willingness to accept new innovative risk management strategies from the European Commission (e.g., mutual funds and income stabilization tool schemes) [57]. In support of the above-mentioned, Giampietri et al. stated that previous experience in applying for insurance could lead to the more straightforward application of new risk management instruments to better cope with climate risks [58].

Author Contributions

All authors worked collectively and significantly contributed to this work. Subsequently, each author handled a certain section of the article. M.N. and T.Č. wrote the Introduction, the Methodology was written by A.Č.M., M.O. and S.G.B., the data analysis was performed by A.Č.M., the Results and Discussion was written by A.Č.M., M.O., T.Č., and M.N., and the Conclusions was written by M.N., M.O., T.Č. and A.Č.M. All authors have read and agreed to the published version of the manuscript.

Funding

This work was funded by the Croatian European regional fund under a specific scheme to strengthen applied research in proposing actions for climate change adaptation (Project No. KK.05.1.1.02.0005).

Institutional Review Board Statement

Approval for the study was not required in accordance with local legislation.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data presented in this study are available within the article.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Nguyen, T.P.L.; Seddaiu, G.; Virdis, S.G.P.; Tidore, C.; Pasqui, M.; Roggero, P.P. Perceiving to learn or learning to perceive? Understanding farmers’ perceptions and adaptation to climate uncertainties. Agric. Syst. 2016, 143, 205–216. [Google Scholar] [CrossRef]
  2. Engler, A.; Rotman, M.L.; Poortvliet, P.M. Farmers’ perceived vulnerability and proactive versus reactive climate change adaptation in chile’s maule region. Sustainability 2021, 13, 9907. [Google Scholar] [CrossRef]
  3. Ortiz-Bobea, A.; Ault, T.R.; Carrillo, C.M.; Chambers, R.G.; Lobell, D.B. Anthropogenic climate change has slowed global agricultural productivity growth. Nat. Clim. Chang. 2021, 11, 306–312. [Google Scholar] [CrossRef]
  4. EEA. EEA Report of Climate Change Adaptation in the Agriculture Sector in Europe No 4. Luxembourg: EEA 2019. Available online: https://www.eea.europa.eu/publications/cc-adaptation-agriculture (accessed on 27 July 2021).
  5. Carraro, C.; Sgobbi, A. Climate Change Impacts and Adaptation Strategies in Italy: An Economic Assessment; 6. Nota di Lavoro; Fondazione Eni Enrico Mattei (FEEM): Milano, Italy, 2008. [Google Scholar]
  6. Giorgi, F.; Lionello, P. Climate change projections for the Mediterranean region. Glob. Planet. Chang. 2008, 63, 90–104. [Google Scholar] [CrossRef]
  7. World Bank. Agriculture and Rural Development Strategy (STARS RAS). Accompanying Document Assessment of Agro-Ecological Zoning and Climate Change; Ministry of Agriculture: Zagreb, Croatia, 2020; Available online: https://poljoprivreda2020.hr/wp-content/uploads/2020/06/Procjena-agroekolo%C5%a1kog-zoniranja-i-klimatskih-promjena.pdf (accessed on 8 September 2022).
  8. Roco, L.; Engler, A.; Bravo-Ureta, B.E.; Jara-Rojas, R. Farmers’ perception of climate change in Mediterranean Chile. Reg. Environ. Chang. 2015, 15, 867–879. [Google Scholar] [CrossRef]
  9. Mccarl, B.A.; Hertel, T.W. Climate Change as an Agricultural Economics Research Topic. Appl. Econ. Perspect. Policy 2018, 40, 60–78. [Google Scholar] [CrossRef]
  10. Abbass, K.; Qasim, M.Z.; Song, H.; Murshed, M.; Mahmood, H.; Younis, I. A review of the global climate change impacts, adaptation, and sustainable mitigation measures. Environ. Sci. Pollut. Res. 2022, 29, 42539–42559. [Google Scholar] [CrossRef]
  11. Branković; Č Klima i klimatske promjene. Mat. Fizički List 2014, 64, 152–162.
  12. Državni Hidrometeorološki Zavod. Buduće Klimatske Promjene. Klima I Klimatske Promjene. 2018. Available online: http://meteo.hr/klima.php?Section=klima_modeli&param=klima_promjene (accessed on 13 March 2019).
  13. Moatti, J.-P.; Thiébault, S. The Mediterranean Region under Climate Change: A Scientific Update; Abridged English/French Version; Allenvi: Marseille, France, 2016. [Google Scholar]
  14. Čop, T.; Njavro, M. Income risk and income stabilization tool in Croatian horticulture. J. Cent. Eur. Agric. 2022, 23, 464–476. [Google Scholar] [CrossRef]
  15. Ministarstvo Zaštite Okoliša I Energetike. Nacrt Strategije Prilagodbe Klimatskim Promjenama U Republici Hrvatskoj Za Razdoblje Do 2040. Godine S Pogledom Na 2070. Godinu (Bijela knjiga). Jačanje Kapaciteta Ministarstva Zaštite Okoliša I Energetike Za Prilagodbu Klimatskim Promjenama Te Priprema Nacrta Strategije Prilagodbe Klimatskim Promjenama. 2017. Available online: http://www.mzoe.hr/doc/nacrt_strategije_1.pdf (accessed on 13 March 2019).
  16. Oplanić, M.; Njavro, M.; Čehić, A.; Težak Damijanić, A.; Čop, T.; Begić, M.; Ban, S.G. Društveno-Ekonomski Čimbenici Prilagodbe I Jačanja Otpornosti Poljoprivrednog Sektora Na Klimatske Promjene; Institut Za Poljoprivredu I Turizam: Poreč, Hrvatska, 2022. [Google Scholar]
  17. Čop, T.; Čehić, A.; Njavro, M. Income Stabilization Tool in Viticulture–Risk Management Innovation: The case of the Istria County. J. Cent. Eur. Agric. 2020, 21, 686–696. [Google Scholar] [CrossRef]
  18. Bisbis, M.B.; Gruda, N.; Blanke, M. Potential impacts of climate change on vegetable production and product quality–A review. J. Clean. Prod. 2018, 170, 1602–1620. [Google Scholar] [CrossRef]
  19. European Environment Agency—EEA. Economic Losses and Fatalities from Weather- and Climate-Related Events in Europe; Briefing No.; European Environment Agency: Copenhagen, Denmark, 2022; ISSN 2467-3196. [CrossRef]
  20. Global Humanitarian Forum Geneva. The Anatomy of A Silent Crisis. Forum 2009: Climate Change, Global Humanitarian Forum. 2009. Available online: https://www.preventionweb.net/files/9668_humanimpactreport1.pdf (accessed on 8 September 2022).
  21. Ministry of Finance. Reported Damages by Types of Natural Disasters by Counties; Ministry of Finance: Zagreb, Croatia, 2020. Available online: https://mfin.gov.hr/istaknute-teme/koncesije-idrzavne-potpore/prirodne-nepogode/prijavljene-stete-po-vrstama-prirodnihnepogoda-po-zupanijama/3050 (accessed on 29 July 2021).
  22. Belay, A.; Recha, J.W.; Woldeamanuel, T.; Morton, J.F. Smallholder farmers’ adaptation to climate change and determinants of their adaptation decisions in the Central Rift Valley of Ethiopia. Agric. Food Secur. 2017, 6, 1–13. [Google Scholar] [CrossRef] [Green Version]
  23. Battaglini, A.; Barbeau, G.; Bindi, M.; Badeck, F.W. European winegrowers’ perceptions of climate change impact and options for adaptation. Reg. Environ. Chang. 2009, 9, 61–73. [Google Scholar] [CrossRef]
  24. Pomarici, E.; Seccia, A. Economic and Social Impacts of Climate Change on Wine Production. In Reference Module in Food Sciences; Elsevier: Amsterdam, The Netherlands, 2015; pp. 1–8. [Google Scholar] [CrossRef]
  25. Teshome, H.; Tesfaye, K.; Dechassa, N.; Tana, T.; Huber, M. Smallholder farmers’ perceptions of climate change and adaptation practices for maize production in Eastern Ethiopia. Sustainability 2021, 13, 9622. [Google Scholar] [CrossRef]
  26. Hasan, M.K.; Kumar, L. Comparison between meteorological data and farmer perceptions of climate change and vulnerability in relation to adaptation. J. Environ. Manag. 2019, 237, 54–62. [Google Scholar] [CrossRef]
  27. Williams, P.A.; Crespo, O.; Abu, M. Assessing vulnerability of horticultural smallholders’ to climate variability in Ghana: Applying the livelihood vulnerability approach. Environ. Dev. Sustain. 2020, 22, 2321–2342. [Google Scholar] [CrossRef]
  28. Woods, B.A.; Nielsen, H.Ø.; Pedersen, A.B.; Kristofersson, D. Farmers’ perceptions of climate change and their likely responses in Danish agriculture. Land Use Policy 2017, 65, 109–120. [Google Scholar] [CrossRef]
  29. Njavro, M.; Čop, T. Upravljanje Rizikom U Poljoprivredi. Mate d.o.o.: Zagreb, Croatia, 2021. [Google Scholar]
  30. Sacchelli, S.; Fabbrizzi, S.; Bertocci, M.; Marone, E.; Menghini, S.; Bernetti, I. A mix-method model for adaptation to climate change in the agricultural sector: A case study for Italian wine farms. J. Clean. Prod. 2017, 166, 891–900. [Google Scholar] [CrossRef] [Green Version]
  31. Malhi, G.S.; Kaur, M.; Kaushik, P. Impact of climate change on agriculture and its mitigation strategies: A review. Sustainability 2021, 13, 1318. [Google Scholar] [CrossRef]
  32. Rippo, R.; Cerroni, S. Farmers’ participation in the Income Stabilisation Tool: Evidence from the apple sector in Italy. J. Agric. Econ. 2022, 1–22. [Google Scholar] [CrossRef]
  33. Meuwissen, M.P.; Assefa, T.T.; van Asseldonk, M.A. Supporting Insurance in European Agriculture: Experience of Mutuals in the Netherlands. EuroChoices 2013, 12, 10–16. [Google Scholar] [CrossRef]
  34. Bergevoet, R. Annex 3-Case study 3, Consequential losses due to sanitary risks in the livestock sector: From insurance to mutual funds. In Study on Risk Management in EU Agriculture; Ecorys, Wageningen Economic Research; European Commission: Brussels, Belgium, 2017. [Google Scholar]
  35. Cordier, J. Annex 5-Case study 5 Critical issues for the implementation of a mutual fund compensating for production loss under Article 38 of Reg. (EU) No. 1305/2013. In Study on Risk Management in EU Agriculture; Ecorys, Wageningen Economic Research; European Commission: Brussels, Belgium, 2017. [Google Scholar]
  36. Sorvali, J.; Kaseva, J.; Peltonen-Sainio, P. Farmer views on climate change—A longitudinal study of threats, opportunities and action. Clim. Chang. 2021, 164, 1–19. [Google Scholar] [CrossRef]
  37. APPRRR—Agencija Za Plaćanja U Poljoprivredi, Ribarstvu I Ruralnom Razvoju. Arkod. Prikaz Broja, Površine ARKOD-a i Broja PG-a s Obzirom na Veličinu i Sjedište PG-a. 2020. Available online: https://www.apprrr.hr/arkod/ (accessed on 31 December 2020).
  38. APPRRR—Agencija Za Plaćanja U Poljoprivredi, Ribarstvu I Ruralnom Razvoju. Upisnik Poljoprivrednika. Upisnik poljoprivrednika_broj PG-a. 2020. Available online: https://www.apprrr.hr/upisnik-poljoprivrednika/ (accessed on 31 December 2020).
  39. Ministarstvo Poljoprivrede. Sustav Poljoprivrednih Knjigovodstvenih Podataka FADN Baza. 2018. Available online: https://www.fadn.hr/ (accessed on 12 October 2022).
  40. Ministarstvo Poljoprivrede. Više Od Farme. Nacrt Strategije Poljoprivrede Hrvatska 2020–2030. 2020. Available online: https://poljoprivreda.gov.hr/userdocsimages/dokumenti/novosti/Nacrt_strategije_poljoprivrede_2020_2030_.pdf (accessed on 12 October 2022).
  41. Wikipedia. NUTS Statistical Regions of Croatia. 2022. Available online: https://en.wikipedia.org/wiki/NUTS_statistical_regions_of_Croatia (accessed on 20 December 2022).
  42. Office, Excel Function; Microsoft: Redmond, WA, USA, 2022.
  43. Arbuckle, J.G., Jr.; Morton, L.W.; Hobbs, J. Understanding Farmer Perspectives on Climate Change Adaptation and Mitigation: The Roles of Trust in Sources of Climate Information, Climate Change Beliefs, and Perceived Risk. Environ. Behav. 2015, 47, 205–234. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  44. Chiu, T.; Fang, D.-P.; Chen, J.; Wang, Y.; Jeris, C. A robust and scalable clustering algorithm for mixed type attributes in large database environment. In Proceedings of the 7th ACM SIGKDDD International Conference on Knowledge Discovery and Data Mining, ACM SIGKDDD, San Francisco, CA, USA, 26–29 August 2001; pp. 263–268. [Google Scholar]
  45. Norusis, M.J. SPSS 15.0 Advanced Statistical Procedures Companion; Prentice Hall: Chicago, IL, USA, 2017. [Google Scholar]
  46. Hair, J.; Black, W.; Babin, B.; Anderson, R. Multivariate Data Analysis; Pearson: Hoboken, NJ, USA, 2015. [Google Scholar]
  47. Ozor, N.; Cynthia, N. Difficulties in adaptation to climate change by farmers in Enugu State, Nigeria. J. Agric. Ext. 2010, 14, 106–122. [Google Scholar] [CrossRef] [Green Version]
  48. Islam, M.M.; Barnes, A.P.; Toma, L. An investigation into climate change scepticism among farmers’. J. Environ. Psychol. 2013, 34, 137–150. [Google Scholar] [CrossRef]
  49. García de Jalón, S.; Silvestri, S.; Granados, A.; Iglesias, A. Behavioural barriers in response to climate change in agricultural communities: An example from Kenya. Reg. Environ. Chang. 2015, 15, 851–865. [Google Scholar] [CrossRef]
  50. Mertz, O.; Mbow, C.; Reenberg, A.; Diouf, A. Farmers’ perceptions of climate change and agricultural adaptation strategies in rural Sahel. Environ. Manag. 2009, 43, 804–816. [Google Scholar] [CrossRef]
  51. Čop, T.; Čehić, A.; Njavro, M.; Begić, M.; Goreta Ban, S.; Juračak, J.; Oplanić, M. Percepcija nositelja poljoprivrednih gospodarstava o utjecaju i posljedicama klimatskih promjena. In Proceedings of the Zbornik Radova 56. Hrvatski I 16. Međunarodni Simpozij Agronoma, Vodice, Croatia, 5–10 September 2021; pp. 177–181. [Google Scholar]
  52. Fachrista, I.A.; Suryantini, A. Perception of climate change and barriers to adaptation among organic vegetable farmers in Central Java, Indonesia. Eur. Asian J. Biosci. 2019, 13, 1727–1735. [Google Scholar]
  53. Pesci, S. Getting Smart about Agriculture: Climate Change Adaptation and Mitigation in Volusia County Farms. Ph.D. Thesis, Stetson University, DeLand, FL, USA, 2014. [Google Scholar]
  54. Rijal, S.; Gentle, P.; Khanal, U.; Wilson, C.; Rimal, B. A systematic review of Nepalese farmers’ climate change adaptation strategies. Clim. Policy 2022, 22, 132–146. [Google Scholar] [CrossRef]
  55. Marie, M.; Yirga, F.; Haile, M.; Tquabo, F. Farmers’ choices and factors affecting adoption of climate change adaptation strategies: Evidence from northwestern Ethiopia. Heliyon 2020, 6, e03867. [Google Scholar] [CrossRef]
  56. Nnadi, F.N.; Chikaire, J.; Echetama, J.A.; Ihenacho, R.A.; Umunnakwe, P.C.; Utazi, C.O. Agricultural insurance: A strategic tool for climate change adaptation in the agricultural sector. Net J. Agric. Sci. 2013, 1, 1–9. [Google Scholar]
  57. Čop, T.; Njavro, M. Application of Discrete Choice Experiment in Agricultural Risk Management: A Review. Sustainability 2022, 14, 10609. [Google Scholar] [CrossRef]
  58. Giampietri, E.; Yu, X.; Trestini, S. The role of trust and perceived barriers on farmer’s intention to adopt risk management tools. Bio-Based Appl. Econ. J. 2020, 9, 1–24. [Google Scholar]
Sustainability 15 00539 g001 550
Figure 1. Map of sampling location (on the left) and surveyed farmers (on the right, colour intensity denotes number of farms surveyed). NUTS—2: Four regions (non-administrative). Adriatic Croatia (light blue), Pannonian Croatia (green), Northern Croatia (orange), City of Zagreb (purple). Source: Authors according to [41,42].
Figure 1. Map of sampling location (on the left) and surveyed farmers (on the right, colour intensity denotes number of farms surveyed). NUTS—2: Four regions (non-administrative). Adriatic Croatia (light blue), Pannonian Croatia (green), Northern Croatia (orange), City of Zagreb (purple). Source: Authors according to [41,42].
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Figure 2. The importance of the production structure adaptation measures.
Figure 2. The importance of the production structure adaptation measures.
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Figure 3. The importance of the production technology adaptation measures.
Figure 3. The importance of the production technology adaptation measures.
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Figure 4. The importance of the risk mitigation measures.
Figure 4. The importance of the risk mitigation measures.
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Table
Table 1. Structure of the farms and horticultural production in the researched area.
Table 1. Structure of the farms and horticultural production in the researched area.
Adriatic CroatiaCounty of IstriaCounty of Primorje-Gorski KotarCounty of ZadarCounty of Šibenik-KninCounty of Split-DalmatiaCounty of Dubrovnik-Neretva
Total number of agricultural households41.2606.0633.2457.7795.07111.3257.777
Total utilized agricultural area (ha)133.59325.02015.62138.46423.22221.5849.682
Total number of farms with vegetable production13.4013.8285494.0487622.4431.771
Total area under vegetables (ha)3.8851.3871161.371141502367
Average farm area under vegetables (ha)0.290.360.210.340.190.210.21
Total number of farms with viticultural production9.2951.9501862.0531.3671.7571.982
Total area under vineyards (ha)9.1402.9281941.4479051.5742.092
Average farm area under vineyards (ha)0.981.501.040.700.660.141.06
Total number of farms with olives production13.7242.3555043.5012.1282.6762.560
Total area under olive grove (ha)17.5353.8346933.2872.5874.5832.551
Average farm area under olive (ha)1.281.631.380.941.221.711.00
Source: APPRRR, 2020a,b [37,38]; Ministarstvo poljoprivrede, 2018 [39]; Ministarstvo poljoprivrede, 2020 [40].
Table
Table 2. Socio-demographic characteristics of the farmers.
Table 2. Socio-demographic characteristics of the farmers.
Characteristics Percent of Total (%)
GenderFemale18.2%
Male75.8%
Prefer not to say 3.3%
Age (Median)0–4016.4%
41–5118.9%
52–6544.4%
Older than 6520.4%
Education level (Median)Primary school16.4%
Secondary school58.2%
University—
undergraduate study		12.7%
University—
postgraduate study		10.2%
PhD2.5%
Education in field of agriculture (Median)Yes18.9%
No81.1%
Revenue from agriculture in total household revenue (Median)Only revenue from agriculture 14.9%
More than 50% of total household revenue25.5%
Lower than 50% of total household revenue59.6%
Farm location (Median)Istria County14.5%
Primorje-Gorski Kotar County6.9%
Zadar County23.3%
Šibenik-Knin County9.5%
Split-Dalmatia County32.0%
Dubrovnik-Neretva County12.7%
Dominant type of plant production (Median)Olive trees50.2%
Vineyards29.3%
Vegetables20.5%
Table
Table 3. Perceived risk toward the impact and consequences of climate change.
Table 3. Perceived risk toward the impact and consequences of climate change.
Perceived RiskMeanSDMINMAX
Climate change presents a major problem for the regular activity of my business.3.620.86915
I believe extreme weather events will increasingly affect my business.3.491.04815
I need to adapt my business continuously to the current climate change.3.470.96015
Extreme weather events cause frequent and severe damage to my business.3.440.91615
Due to climate change, the risk to my business is increasing every year.3.331.00915
Cronbach’s alpha = 0.702
Values and interpretation of Cronbach alpha coefficient: <0.6—weak, 0.6 < 0.7—moderate, 0.7 < 0.8—good, 0.8 < 0.9—very good, 0.9 and more—excellent: Hair et al. (2015) [46].
Table
Table 4. Clusters identified by the perceived risk of climate change.
Table 4. Clusters identified by the perceived risk of climate change.
Perceived Risk—ItemsCluster 1
Climate Sceptics
(N = 159, 57.81%)		Cluster 2
Climate Aware
(N = 116, 42.19%)		F—Value
Climate change presents a major problem for the regular activity of my business.−0.551127
(M = 3.30)		0.997363
(M = 4.04)		98.371 **
Extreme weather events cause frequent and severe damage to my business.−0.497461
(M = 3.08)		0.623947
(M = 3.94)		106.662 **
Due to climate change, the risk to my business is increasing every year.−0.823677
(M = 2.87)		0.055069
(M = 3.98)		94.452 **
I need to adapt my business continuously to current climate change.−0.641792
(M = 2.98)		0.421792
(M = 4.13)		101.932 **
I believe extreme weather events will increasingly affect my business.−0.008902
(M = 2.95)		0.178462
(M = 4.23)		89.851 **
** 0.001
Table
Table 5. Comparison of perception on application of the production structure adaptation measures between two clusters.
Table 5. Comparison of perception on application of the production structure adaptation measures between two clusters.
StrategyCluster 1
Climate Sceptics		Cluster 2
Climate Aware		F—Value
Changing the production structure towards supporting crops better resistant to drought, freezing, lodging, etc.3.383.737.964 **
Shift to varieties with better drought, frost, and lodging resistance...(albeit they may have lower yields)3.583.783.175 *
Crossbreeding crops3.363.614.115 *
Shift to new cropping area (e.g., replanting)3.033.377.216 **
Increase in production area3.403.788.354 **
Targeting organic production3.874.072.248 ns
ns—non-significant, * 0.050, ** 0.001.
Table
Table 6. Comparison of perception on application of the risk reduction measures between clusters.
Table 6. Comparison of perception on application of the risk reduction measures between clusters.
StrategyCluster 1
Climate Sceptics 		Cluster 2
Climate Aware		F—Value
More frequent and greater crop and asset insurance3.323.553.447 *
Public co-financing of insurance premiums3.523.681.630 ns
Access to more favorable insurance policies for farmers3.423.8510.195 **
Timely communication on climate change3.714.026.601 **
Construction of public irrigation systems3.783.983.073 *
Construction of public drainage systems3.724.026.759 **
Establishment of a public hail damage prevention system3.823.850.071 ns
Establishment of a public low temperature damage prevention system3.823.920.775 ns
ns—non-significant, * 0.050, ** 0.001.
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Oplanić, M.; Marić, A.Č.; Goreta Ban, S.; Čop, T.; Njavro, M. Horticultural Farmers’ Perceived Risk of Climate Change in Adriatic Croatia. Sustainability 2023, 15, 539. https://doi.org/10.3390/su15010539

AMA Style

Oplanić M, Marić AČ, Goreta Ban S, Čop T, Njavro M. Horticultural Farmers’ Perceived Risk of Climate Change in Adriatic Croatia. Sustainability. 2023; 15(1):539. https://doi.org/10.3390/su15010539

Chicago/Turabian Style

Oplanić, Milan, Ana Čehić Marić, Smiljana Goreta Ban, Tajana Čop, and Mario Njavro. 2023. "Horticultural Farmers’ Perceived Risk of Climate Change in Adriatic Croatia" Sustainability 15, no. 1: 539. https://doi.org/10.3390/su15010539

APA Style

Oplanić, M., Marić, A. Č., Goreta Ban, S., Čop, T., & Njavro, M. (2023). Horticultural Farmers’ Perceived Risk of Climate Change in Adriatic Croatia. Sustainability, 15(1), 539. https://doi.org/10.3390/su15010539

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