1. Introduction
Oilseed rape is the third most important source of both vegetable oil (after soybean and oil palm) [
1] and oil meal (after soybean and cotton) in the world [
2]. Over the last 20 years, the worldwide production of this crop has doubled from 36,019,847 to 71,333,435 tons [
3]. The main producers of oilseed rape are China (17% of the global output), Canada (16%), India (12%), Australia (5.5%), Germany (4.1%), France (3.8%), Poland (3.5%), Ukraine (3.4%), and the Russian Federation (3.2%). The differences between the highest and the lowest oilseed rape yields registered in the years 2017–2021 for the leading producers of this crop are as follows: 39% (Australia), 35% (Canada), 25% (Russian Federation), 22% (France), 21% (Ukraine), 19% (Poland and Germany), and 14% (India). The principal reasons for variability in the crop yield, besides the yield potential of a cultivar, are the meteorological conditions and pests [
4,
5].
One of the most destructive and harmful diseases of oilseed rape is Sclerotinia stem rot, which is caused by
Sclerotinia sclerotiorum [
6]. Among the 10 most significant biotic threats to oilseed rape cultivation, this pathogen holds first place in China and second in Australia, Europe, and Canada [
7].
Yield losses due to Sclerotinia stem rot have been reported to be as high as 80% in China [
8] and 75% in Nepal [
9]. In the United Kingdom, oilseed rape infestation by
S. sclerotiorum results in a 50% yield loss [
10], while in Germany, it results in a 20–30% yield loss [
11]. In Saskatchewan, Canada, and in Minnesota and North Dakota, USA, in 1991–1997, yield losses due to Sclerotinia stem rot ranged from 11.4 to 14.9%, ref. [
12], 11.2 to 13.2%, and 5 to 13% [
13], respectively.
Also, in Poland, along with Phoma lingam and clubroot, Sclerotinia stem rot is considered to be among the most dangerous oilseed rape diseases [
14]. According to Starzycki and Starzycka, this disease occurs in Poland every year to a greater or lesser extent [
15]. In an experiment conducted in the years of 2005–2009 focusing on oilseed rape infestation by
S. sclerotiorum, Jajor et al. registered 3–27% of the surveyed plants as having symptoms of the disease [
16]. Great diversity in the number of oilseed rape plants infested with
S. sclerotiorum was found by Kaczmarek et al. and Bracharczyk et al., who, in the years of 2010–2011, observed that 2–34% and 25–50% of plants, respectively, had Sclerotinia stem rot [
17,
18]. The importance of this disease is even better characterized by the results of research on its impact on the yield of oilseed rape. In a study on the optimization of the dates of fungicidal treatments against Sclerotinia stem rot in oilseed rape, Bracharczyk et al. [
18] recorded yield losses of 6% and 19%, depending on the year. High yield losses of oilseed rape caused by
S. sclerotiorum were also registered by Jajor et al. [
16]. While examining the impacts of fungicide protection and meteorological conditions on the infection of oilseed rape cultivars by
S. sclerotiorum, the authors observed yield losses of up to 15%. According to Starzycki and Starzycka, yield losses may even exceed 30% under conditions that are extremely favorable for the development of the pathogen [
15].
S. sclerotiorum survives in the soil as sclerotia from previous epidemics [
19]. Sclerotia germinate either myceliogenically, by producing mycelia, or carpogenically, by producing apothecia, which, in turn, release ascospores [
20]. The infection of oilseed rape leaves by
S. sclerotiorum occurs primarily as a result of ascospore germination on petals, through which the mycelium of the pathogen penetrates into the leaf tissue [
21,
22]. When ascospores come into direct contact with leaf tissue, they either do not germinate [
22] or their ability to germinate is strongly reduced [
23]. A strong correlation between petal infestation and disease incidence explains why the flowering period of oilseed rape is critical for the epidemiology of Sclerotinia stem rot [
22,
24].
The development of this disease is also affected by meteorological factors, among which air temperature, in addition to air humidity, is commonly considered to be a major determinant of Sclerotinia stem rot risk [
25,
26,
27]. Knowledge about the relationship between temperature and pathogen development is widely used to predict the disease threat to crops as a result of climate change [
28,
29,
30].
According to the Synthesis Report of the IPCC, in the first two decades of the 21st century, the global surface temperature was 0.99 °C higher than in 1850–1900, and it has increased faster since 1970 than in any other 50-year period over at least the last 2000 years [
31]. Depending on the scenario, in 2081–2100, the Earth’s surface temperature is very likely to have increased by an average of 1.4 °C to 4.4 °C compared to that in 1850–1900.
Such changes in temperature could profoundly alter pathogen threats to crops in the future [
32,
33,
34]. The status of crop diseases may be affected by climate change directly or indirectly [
35]. The direct impact of climate change results from the immediate reactions of living organisms to changed meteorological conditions, while the indirect results come from changes in the compositions, structures, and functions of ecosystems triggered by changes in meteorological variables [
36].
In the present article, a direct impact (DI) is a relationship between temperature and
S. sclerotiorum development, while an indirect impact (II) represents the influence of temperature on the development of oilseed rape—the
S. sclerotiorum’s host crop. The complex nature of the influence of climate change on crop disease development makes it difficult to precisely define relationships between DIs and IIs. For this reason, despite the general agreement on the distinction between these two methods of climate change impacts, it is not easy to find articles that deal with plant disease in which the relationships between the DI and II are expressed in numbers. Among the crops most often taken into account, in the last twenty years, the studies describing pathogen responses to climate change on the basis of simulation results have mostly included wheat, followed by rice, grapevine, and potato, whereas oilseed rape is under-represented [
37].
The present work intends to fill the gap in information about the relationships between S. sclerotiorum and oilseed rape development under climate change conditions. We are especially interested in the relationships between the DI and II of climate change at the level of Sclerotinia stem rot risk. Our earlier studies indicated the superiority of the II over the DI in determining the fatty acid composition of oilseed rape oil on a national scale. We hypothesized that II may also be dominant in shaping the future Sclerotinia stem rot threat to oilseed rape. The objective of the present study was to check this hypothesis by comparing the DI and II of climate change on the level of Sclerotinia stem rot risk. We express the relationships between these phenomena numerically on the regional scale. The regions of Poland that are expected to experience major increases in S. sclerotiorum pressure on oilseed rape in the future are also indicated.
2. Materials and Methods
2.1. Development of a Model for Simulating the Flowering Time of Oilseed Rape
Our model was developed on the basis of data collected in field experiments conducted at Winna Góra (60 km south of Poznań) in 2005–2022. Each year, three oilseed rape cultivars were used in the study (
Table 1). The data gathered in odd years were used to build the model, while model validation was performed on data from even years.
The model development consisted of quantifying the relationship between the accumulated rapeseed developmental rate (ARDR) and the phenological development stages of the cultivars listed in
Table 1, according to the BBCH scale [
38]. The phenological development stages were registered twice per week in the period from the first of January to the end of oilseed rape flowering period each year. Detailed information explaining how to calculate the rapeseed developmental rate (RDR) was presented by Racca et al. [
39]. The collected data were used to build a model simulating oilseed rape development. The model consisted of two submodels (
Table 2). The first one describes oilseed rape development from 1 January to the beginning of flowering period (BBCH 61), while the second covers the period from the beginning to the end of flowering (BBCH 61–69) (
Table 2). The validation of the model was based on a comparison of the simulated and observed results.
2.2. Development of a Model for Estimating Sclerotinia Stem Rot Severity in Oilseed Rape at Flowering Time
The model was developed using the information collected by Koch and presented in her doctoral thesis [
22]. The data shown in this study illustrate the disease severity registered at different temperatures as an effect of the infection of oilseed rape stalks by ascospores. To mathematically describe the pathogen response to the stimulus, we used two submodels. Both define the effect of the temperature upon disease severity. The first, double logistic, operates in the range of 6–18 °C, while the second, based on the Beta function, operates in the range of 18–26 °C (
Table 3).
2.3. Projection of the Effect of Climate Change on the Sclerotinia Stem Rot Severity in Oilseed Rape
The simulations were performed using two sets of meteorological data. The first consisted of data registered in the period of 1986–2005 at 133 locations in Poland (
Figure 1).
The second was obtained after transforming the recorded data to reflect temperature changes under the RCP4.5 and RCP8.5 scenarios according to the 29 climate models presented on the Climate Change Knowledge Portal created by the World Bank (
https://climateknowledgeportal.worldbank.org/download-data (accessed on 15 January 2023) (
Table 4).
The transformation of meteorological data was conducted using the delta change approach, which consists of adding the mean monthly change value for the model results for the projected and registered periods to an observed time series according to Equation (1):
where Tdb is the debiased temperature; Tobsref is the daily temperature observed in the reference period; Tsimproj is the monthly temperature simulated for the projected period; and Tsimref is the monthly temperature simulated for the reference period.
The next task of the study was to estimate the effect of climate change on Sclerotinia stem rot severity in oilseed rape. This was completed using simulations of the impact of temperature on both pathogen development and the oilseed rape flowering period. This task was accomplished in three steps. The first step was to determine the dates of the beginning and the end of the oilseed rape flowering period (BBCH 61, BBCH 69). In the second step, the disease severity for each day of the flowering period was calculated. The third step consisted of calculating the sum of disease severity in the flowering period for each region (Dolnośląskie, Kujawsko-Pomorskie, Lubelskie, Lubuskie, Łódzkie, Małopolskie, Mazowieckie, Opolskie, Podkarpackie, Podlaskie, Pomorskie, Śląskie, Świętokrzyskie, Warmińsko-Mazurskie, Wielkopolskie, Zachodniopomorskie), scenario (RCP4.5, RCP8.5) and period (2020–2039, 2040–2059, 2060–2079, 2080–2099).
Subsequently, we grouped the regions according to disease severity by applying a cluster analysis using the Euclidean distance in such a way that the connection level within the same group was as high as possible, whereas within combinations of other groups, it was as small as possible. Distinct groups of regions depending on disease severity were formed on the basis of the Euclidean distance equaling 1.0.
The next part of the study was designed to measure the impact of climate change on disease severity. To fulfill this task, in addition to the simulation results collected so far, information about disease severity for both the registered (1986–2005) and projected periods (2020–2039, 2040–2059, 2060–2079, 2080–2099) without the influence of temperature on oilseed rape flowering was needed. This is why another series of simulations was conducted. This time, the dates of oilseed rape flowering indicated for the period of 1986–2005 were also used in simulations for the other periods. On the basis of both simulation series, the impact of climate change on disease severity was calculated according to the equations presented below.
The direct impact of temperature on disease severity was calculated using Equation (2):
where DI is the direct impact of climate change on disease severity; ds–tor i, j is the disease severity obtained from simulations without allowing for the influence of temperature on the development of oilseed rape for scenario i and period j (i: RCP4.5, RCP8.5; j: 2020–2039, 2040–2059, 2060–2079, 2080–2099); and ds1986–2005 is the disease severity obtained in simulations for the period of 1986–2005.
The sum of the direct and indirect impacts of climate change on disease severity was calculated using Equation (3):
where (D + I)I is the sum of the direct and indirect impacts of climate change on disease severity; ds+tor i, j is the disease severity obtained in simulations allowing for the influence of temperature on the development of oilseed rape for scenario i and period j (i: RCP4.5, RCP8.5; j: 2020–2039, 2040–2059, 2060–2079, 2080–2099); and ds1986–2005 is the disease severity obtained in simulations for the period of 1986–2005.
The indirect impact of climate change on disease severity was calculated using Equation (4):
where II is the indirect impact of climate change on disease severity; (D + I)I is the sum of the direct and indirect impacts of climate change on disease severity; and DI is the direct impact of climate change on disease severity.
For further analysis, the accumulated rate of change (AROC) of the direct impact (DI) and indirect impact (II) of climate change over time was calculated using Equation (5):
where AROC is the accumulated rate of change; Ii is the impact measured at period i; Ii + 1 is the impact measured at period i + 1; T is the time taken for that change to occur; and N is the total number of observations.
4. Discussion
The present study focused on an exploration of the relationships between the direct impact and indirect impact of climate change on the level of Sclerotinia stem rot risk. On the basis of the meteorological data analyzed, we found that the flowering period of oilseed rape is expected to start and end earlier in the future, irrespective of the RCP scenario. In both scenarios, climate change affects the start date of the flowering period more than the end date. Moreover, these changes are dependent on the period. Over time, they will grow from the smallest for 2020–2039, reaching the highest values in 2080–2099. The simulation also revealed that the changes expected under the RCP8.5 scenario are greater than under RCP4.5 for all periods analyzed.
These findings are in agreement with the study results presented by Hájková et al. [
40], who noticed a significant shift in the beginning of the oilseed rape flowering period. The authors demonstrated that the onset of flowering advanced progressively in the Czech Republic, and the differences between the start of that phenophase in 1991 and 2012 reached almost 15 days. Further studies of earlier-flowering plants in response to ongoing climate change have been registered in other European countries [
41,
42]. For example, Parmesan and Yohe [
43] confirmed this trend by analyzing the flowering periods of 461 plant species. According to Franks et al. [
44], the shifts in phenophases are largely attributed to rising temperatures. In agreement with these findings, Hájková et al. [
40] showed that the best predictor for the onset of oilseed rape flowering is the mean air temperature. The close relationship of oilseed rape flowering with this parameter was also demonstrated by Wójtowicz [
45], who studied the effect of the mean air temperature registered in April on the start of that phenophase. The present study findings, which deal with the onset of flowering period, are also reflected by the results obtained in the studies performed with the use of models. Racca et al. [
37] showed that the flowering of oilseed rape compared to the period of 1970–2000 is expected to start earlier, from 17–19 to 30–49 days for 2020–2055 and 2070–2100, respectively.
Our study demonstrated that the oilseed rape flowering period is expected to be prolonged in the future, mainly due to an earlier start of that phenophase under warming conditions. Similar conclusions were reached by Mo et al. [
46], who analyzed data including 136 plant species from 217 observational sites across eight climatic zones in China from 1963 to 2013 and stated that flowering duration was prolonged, mainly because the beginning of flowering was more substantially advanced than the end of the flowering period.
The earlier start of the flowering period that was proven in the present study may implicate earlier infections of oilseed rape caused by
S. sclerotiuorum. Confirmation of this thesis can be found in the work of Tiedman and Ulger [
47], who stated that warming may enhance the infection window for this pathogen, in both the mid (2001–2030) and longer term (2071–2100), possibly leading to earlier infections in the future.
Our results also provide evidence for the effect of climate warming on the severity of Sclerotinia stem rot. This phenomenon is more dependent on the RCP scenario, while the influence of the locality appears to be smaller. Under the RCP4.5 scenario, nearly 60% of the simulations performed for 16 localities in four periods showed a reduction in disease severity in comparison to those registered for 1986–2005, while under RCP 8.5, this reduction was generated for nearly 90% of cases. These results are in agreement with the outcomes of Racca et al. [
45], who, based on simulations, predicted a significant decrease in
Sclerotinia infection risk, especially for the years of 2071–2100, for Lower Saxony in Germany.
In this study, we also presented the effect of the RCP scenario on the clustering of regions according to Sclerotinia stem rot severity. Under the RCP8.5 scenario, the clustering results appear to be more variable than under RCP4.5. However, under both scenarios, the lowest disease severity for all periods was generated for Zachodniopomorskie and Pomorskie. The results obtained indicate the need to adapt the protection of oilseed rape against S. sclerotiorum to regional conditions, reflecting the projected Sclerotinia stem rot severity for the region and period.
The future reduction in Sclerotinia stem rot severity presented in our study on the basis of the simulation outcomes results from the indirect impact of climate change. A comparison of the indirect impact and direct impact showed the superiority of the effect of the former over the latter on the Sclerotinia stem rot severity caused by climate warming in the future. Under the RCP4.5 scenario, the accumulated rate of change (AROC) for the indirect impact was greater than the AROC for the direct impact for 10 regions, while under RCP8.5, this relationship was registered for 16 regions.
The results obtained indicated the meaning of the indirect impact of climate change on the future threat to crops of pathogens and the necessity of taking this parameter into account when predicting outbreaks of plant diseases.
The complexity of climate change’s effects on future pathogen risk has also been highlighted by others. For example, Madgwick et al. [
48] analyzed the impact of climate change on Fusarium ear blight in the UK and proved the significance of incorporating a model of host plant development into the assessment of the pathogen risk. According to these authors, the date of wheat anthesis, i.e., the growth stage at which wheat is the most vulnerable to infection with Fusarium ear blight, is expected to appear earlier by about 11–15 days across the whole country in the 2020s and 2050s. Also, Evans et al. [
49,
50] and Butterworth et al. [
51] demonstrated that the projection of crop epidemics triggered by climate change requires both crop and pathogen development to be taken into account. The present study demonstrates an extension of this approach and numerically expresses the relationships between the direct impact and indirect impact of climate change, which covers a knowledge gap in this field. Our results highlight the role of the indirect impact in shaping disease severity and indicate that, besides the direct impact, it should be incorporated into assessment methods of climate change effects. This approach enhances our ability to project the ongoing changes driven by global warming. We propose that the accelerated development of oilseed rape in the future, caused by climate change, will contribute to the mitigation of Sclerotinia stem rot. However, we are aware that the results presented in this work cannot be generalized, because they concern only one disease and one country. Further research involving further pathogens and climatic zones is required to establish the nature of the relationship between the direct impact and indirect impact of climate change. Focusing on this problem will help to answer the question of how agriculture can adapt to or mitigate ongoing climatic changes. In our earlier study, which focused on measuring the direct impact and indirect impact of climate change on the fatty acid composition in rapeseed oil, we analyzed the relationship between these phenomena on a national scale [
52]. This time, we described the relationship between the direct impact and indirect impact on a regional scale, which enabled us to present the problem more precisely.
In conclusion, it must be stressed that there are several uncertainties that impede the correct long-term projection of plant disease epidemics. Firstly, the development of the disease is influenced by many factors, among which, apart from the temperature, precipitation and humidity play very important roles. It must be pointed out that estimations of the rainfall distribution in a long time period are extremely difficult, if not impossible [
37]. It is also not easy to assess long-term breeding progress; hence, there is a lack of knowledge about the phenological development of future cultivars, and their resistance to pathogens makes it difficult to predict disease severity over a period of 100 years. Nevertheless, according to Wiens et al. [
53], one should not worry too much about projection uncertainties, as the alternative would be to ignore future risks. Therefore, it is believed that crop disease risk simulations, although not perfect, are helpful for the development of strategies to mitigate the effect of climate change [
37].