Investigation of Climatic Factors Affecting the Amount of Foraged Matsutake Mushrooms in Korea

Abstract

Tricholoma matsutake is a valuable edible mushroom in Eastern Asia. Due to the challenges of artificial cultivation, T. matsutake cultivation has relied on foraging from pine forests. Changes in global climate variables, such as temperature and precipitation, could affect the amount of foraged T. matsutake. In this study, we investigated the correlation between the amount of foraged T. matsutake and climatic factors (average monthly temperature and precipitation) in Yangyang-gun using the augmented Dickey–Fuller test and the ordinary least squares method. Among the assessed correlations between the foraged T. matsutake and different climatic factors, the average temperature in August was significantly correlated with the amount of foraged T. matsutake, increasing by 1.5 tons when the temperature in August increased by 1 unit. Overall, this study identified a potentially strong positive correlation between the average temperature in August and amount of foraged T. matsutake.

1. Introduction

Tricholoma matsutake, also known as matsutake mushroom, derives its name from two Japanese words: “matsu”, meaning pine, and “take”, meaning mushroom. T. matsutake has historically been a valuable and economically important food in Korea, Japan, and China. Due to its unique aroma, derived from the compound matsutakeol, T. matsutake is a commonly used food additive in soups and main dishes to enhance the overall aroma. It is also utilized as a medicinal fungus to prevent and treat several disorders, including diabetes and cardiovascular diseases [1,2,3,4].

Like other ectomycorrhizal fungi, matsutake mushrooms form symbiotic relationships with the root system of their hosts, contributing to the nutrient cycle of the forest ecosystem. T. matsutake establishes a symbiotic structure with its host, the pine tree, facilitating a nutrient exchange through interactions between the mushroom’s hyphal system and the fine root hairs of the pine tree [5,6]. This relationship often leads to the development of specific formations known as fairy rings. They are discovered near pine trees and develop in gravel and weakly acidic soils with low nutrients and high amounts of sand that offer good drainage [7,8]. During summer, stormwater results in the formation of this gravel and sand mixture, while the pines in these forests exhibit tolerance to a broad spectrum of stress conditions [7,8,9]. In Korea, T. matsutake grows in Korean forests where red pine is the dominant species, characterized by slightly acidic and well-drained soils shaped by the climate of the Korean Peninsula [9,10].

Both soil and climatic conditions play important roles in the growth of T. matsutake in pine forests. The matsutake mushroom undergoes different developmental phases throughout its life cycle: the initiation and growth of the mycelium from March to June and the development of the fruiting body from late August to early October [11]. However, global climate change in the 21st century has significantly affected climatic factors such as temperature and precipitation, potentially affecting the growth of T. matsutake in Korea [12,13,14]. A previous study identified a quantitative relationship between climatic factors and T. matsutake habitat suitability [15]. The study revealed that temperature and precipitation could potentially influence the development of matsutake mushrooms. Despite this evidence, few studies have demonstrated a significant relationship between the amount of foraged matsutake mushroom and climatic factors. Since foraged mushroom growth and productivity depend on climatic factors, analyzing the correlation between the amount of foraged T. matsutake and climatic factors is essential. In this study, we investigated the correlation between the amount of foraged T. matsutake, temperature, and precipitation in Yangyang-gun, Korea, from 2003 to 2023.

2. Materials and Methods

2.1. Conceptual Frameworks

Edible mushrooms, including Tricholoma matsutake, predominantly inhabit forested areas [16,17]. Previous studies have confirmed that changes in temperature and precipitation affect not only the vigor of woody and herbaceous plants in forests but also species composition and the herbaceous layer. These climatic changes may decrease mushroom mycelial activity and psychrophilic fungi while increasing the growth and abundance of thermophilic and xerophilic fungi. Such climatic factors may also result in a decrease in the development of mushroom fruiting bodies. Consequently, they may lead to a decrease in mushroom foraging [18,19,20,21].

Yangyang-gun is one of the most important provinces for T. matsutake foraging in Gangwon-do, Korea [11]. To assess the temporal variation in the amount of foraged matsutake mushrooms, data on the amount of T. matsutake foraged in Yangyang-gun between 1990 and 2023 were obtained from the National Forestry Cooperative Federation and Yangyang Institute of Technology. Figure 1 illustrates the data regarding the variation in the amount of foraged matsutake mushrooms from 1990 to 2023 [22].

Figure 1 illustrates a continuous decrease in the amount of foraged T. matsutake each year. Similarly to other mushroom species, temperature and precipitation are crucial factors for the growth of T. matsutake [15,18], thereby resulting in the continued decline and variability in the amount of foraged T. matsutake. In order to confirm the correlation between matsutake mushrooms and climatic factors more accurately, climatic surveys in Yangyang-gun are necessary.

In the context of global climatic change, several studies also investigated climate change in Gangwon-do [23,24]. From the studies, an increase in temperature and a decreasing trend in precipitation in Gangwon-do have been identified. Similarly to other provinces in Gangwon-do, Yangyang-gun is also expected to undergo an increase in temperature and a decrease in precipitation. These climatic trends are expected to affect pine forest formation and the amount of T. matsutake foraged in Yangyang-gun. However, few studies have examined such climatic changes in this region over time. In this study, we investigated changes in the climatic factors of Yangyang-gun over 20 years. The amount of foraged T. matsutake (expressed in tons), temperature (expressed in degrees Celsius), and precipitation (expressed in millimeters) in Yangyang-gun are illustrated in Figure 2. Data from 2003 to 2023 are illustrated since the monitoring of the temperature and precipitation in Yangyang-gun began in 2003 [25].

Similarly to previous studies on temperature variations in Gangwon-do, Yangyang-gun has exhibited two types of climatic changes: an increase in temperature and a decreasing trend in precipitation. However, as shown in Figure 2, the correlation between the amount of T. matsutake foraged and climatic factors remains unclear. To investigate this relationship, a meta-analysis was carried out based on previous studies conducted by Kauserud’s team in 2008, Alfranca’s team in 2015, and Procházka’s team in 2023 [18,19,21]. From these studies, data regarding the amount of foraged T. matsutake, temperature, and precipitation were analyzed.

2.2. Data of Foraged T. matsutake, Temperature, and Precipitation

Data on the amount of foraged T. matsutake, temperature, and precipitation were collected from publicly available datasets provided by the Institute of Korea. The amount of foraged T. matsutake in Yangyang-gun was investigated based on auction quantities reported by the Korea Forest Service and Forestry Cooperative in Korea, which oversees the reported foraging of matsutake mushrooms [22]. From these data, foraged mushrooms from registered mushroom pickers were identified, and the amount of foraged T. matsutake in Yangyang-gun was inferred. The temperature and precipitation data in Yangyang-gun were obtained from reports by the Agricultural Weather Information Service in the Rural Development Administration in Korea [25]. Additional surveys in the mushroom habitats were conducted to ensure the reliability of the information regarding climatic factors. The average annual temperature is reported in degrees Celsius, and the average annual precipitation is reported in millimeters.

2.3. Stationarity Test

A comparison of the time series data was conducted to identify the correlation between the amount of mushrooms and climatic factors. This entails assessing the stationarity of the variables using a unit root test. In this study, we employed the Dickey–Fuller test, which is most commonly used for identifying variable correlations. This test comprises two versions: the simple version and the augmented version [18,19,26].

The simple version includes several types of equations depending on whether there is no trend and intercept (Equation (1)), only a trend (Equation (2)), or an intercept (Equation (3)). Each equation is presented below:

Δy_t = βy_t−1 + ϵ_t

(1)

Δy_t = α + βy_t−1 + ϵ_t

(2)

Δy_t = α + δt + βy_t−1 + ϵ_t

(3)

In the equations, Δy_t, α, δ, β, and ϵ_t represent the difference in the y_t, intercept, slope of trend, the coefficient for the unit root test, and the error term, respectively. However, in the simple version of the Dickey–Fuller test, analyzing the correlation between factors for each time period is unfeasible due to the unavailability of a lagged term. Thus, there is a limit to identifying the correlation between the amount of foraged T. matsutake and climatic factors.

To analyze the correlation between the amount of foraged T. matsutake, temperature, and precipitation in relation to annual variations, the augmented Dickey–Fuller (ADF) test was used, incorporating the trend, conception, and lagged term (Equation (4)). The relevant equation for the ADF test is presented below:

$$\mathsf{\Delta }{\mathrm{y}}_{\mathrm{t}}=\mathsf{\alpha }+\mathsf{\delta }\mathrm{t}+\mathsf{\beta }{\mathrm{y}}_{\mathrm{t}-1}+{\sum }_{i=1}^p{\mathsf{\beta }}_{\mathrm{i}}\mathsf{\Delta }{\mathrm{y}}_{\mathrm{t}-\mathrm{i}}+{\mathsf{ϵ}}_{\mathrm{t}}$$

(4)

In the equation, Δy_t−i corresponds to the lagged term, and ${\sum }_{i=1}^p\mathsf{\beta }$_iΔy_t−i corresponds to the number of lagged terms to control the correlation. In addition, the results of the ADF test were ascertained using the following formula (Equation (5)):

$$\mathrm{t}\mathrm{DF}={\displaystyle \frac{\mathrm{Î}}{\mathrm{S}\mathrm{E}\left(\mathrm{Î}\right)}}$$

(5)

The null hypothesis was set as I = 0, indicating a unit root in the time series. For the alternative hypothesis, I < 0 suggests stationarity exists.

In summary, the level of stationarity in the correlation between the variables (annual amount of foraged T. matsutake, average monthly temperature, and precipitation) was assessed using the ADF test incorporating trend, conception, and lagged terms.

Among the regression methods, linear regression offers an advantage for quantitatively assessing the correlation between the foraged T. matsutake and climatic factors. In this study, the ordinary least squares (OLS) method was employed, the most commonly and widely used method. If stationarity is identified in the ADF test, the OLS method can be used to analyze the correlation between the amount of foraged T. matsutake and climatic factors [18,27].

In the theoretical regression function, the amount of foraged mushrooms (in this study, PM) is the dependent variable, and the climatic factors (in this study, average monthly temperature and precipitation) are the independent variables. The following formula (Equation (6)) was used for the regression:

y = β₀ + β_nX_n + ϵ

(6)

In the equation, y, X, β₀, β_n, and ϵ correspond to the mean of the dependent variable (foraged T. matsutake), independent variable (climatic factors), intercept, slope of trend, and error term, respectively. In OLS, this equation is most commonly employed for determining variable correlation.

To ensure the reliability of the regression model, the sum of squared residuals (SSR, also denoted as Q) was calculated based on the correlation between the variables in Equation (6). The following formula (Equation (7)) was used in the regression:

$$\mathrm{Q}={\min }_{{\mathsf{\beta }}_0{\mathsf{\beta }}_1{\mathsf{\beta }}_2}{\sum }_{i=1}^n{({\mathrm{y}}_{\mathrm{i}}-{\mathsf{\beta }}_0-{\mathsf{\beta }}_1{\mathrm{X}}_{1\mathrm{i}}-{\mathsf{\beta }}_2{\mathrm{X}}_{2\mathrm{i}},\dots ,{\mathsf{\beta }}_{\mathrm{n}}{\mathrm{X}}_{\mathrm{n}\mathrm{i}})}^2$$

(7)

Based on the SSR results, the suitability of the OLS model for assessing the correlation between the variables was evaluated, and the amount of foraged T. matsutake was calculated based on changes in the climatic factors.

3. Results and Discussion

Prior to investigating the relationship between the amount of foraged T. matsutake and climatic factors in a time series, it was necessary to analyze the descriptive statistics for the dependent variable (foraged T. matsutake). This analysis aimed to ascertain the reliability of the correlation between the foraged T. matsutake and climatic factors. The results are provided in

Table 1. Descriptive statistics for the variable foraged Tricholoma matsutake (2003–2023).

Variable	Mean	Median	Minimum	Maximum
Foraged T. matsutake	5829.6	4999.1	481.0	14,380.2
Foraged T. matsutake (log)	8.4	8.5	6.2	9.6

.

The descriptive statistics for the foraged T. matsutake revealed significant differences between the minimum and maximum, as well as between the mean and median. These results indicated an asymmetric data distribution, potentially impeding the correlation analysis. Thus, the foraged T. matsutake foraging data were logarithmically transformed to achieve a symmetrical distribution and stabilize the correlation analysis. Following this transformation, a normal distribution was obtained using the logged data, as evidenced by the relatively close relationship between the mean and median and the considerable difference between the minimum and maximum.

From the ADF test in this study, the stationarity level for the amount of foraged T. matsutake in the correlation analysis was not presented. To obtain stationarity, diffusion was processed against the data in 2006 and 2013, which exhibited the lowest correlation between the mushroom and climatic factors. With the diffused data, the stationarity level of each variable (foraged T. matsutake, average monthly temperature, and precipitation) was evaluated, and the results are provided in

Table 2. Augmented Dickey–Fuller test between foraged Tricholoma matsutake and climatic factors across different months.

		Annual	January	February	March	April	May	June	July	August	September	October	November	December
Temp.	ADF statistic	−3.09	−2.74	−5.08	−2.57	−3.64	−2.50	−2.83	−3.58	−4.00	−0.53	1.10	−3.12	−4.14
	p-value	0.11	0.22	<0.01	0.29	0.03	0.33	0.18	0.03	<0.01	0.98	1.00	0.10	<0.01
Prec.	ADF statistic	−3.55	−3.92	−4.22	−4.47	−2.49	−3.81	−4.74	−2.20	−1.15	−3.66	−3.10	−3.50	−0.89
	p-value	0.03	<0.01	<0.01	<0.01	0.33	0.02	<0.01	0.49	0.92	0.03	0.11	0.04	0.96

In foraged Tricholoma matsutake, ADF statistic: −5.08, p-value: <0.01. Significance level α = 0.05.

.

The results of the ADF test indicated stationarity in the amount of foraged T. matsutake in relation to the average temperature in February, August, and December and the average precipitation in January, February, March, and June. The correlation with the amount of foraged T. matsutake could be assessed using these variables. In addition, the correlation coefficient, which measures the strength and direction of relationships between two variables, was calculated to identify the degree of similarity between the mushroom and climatic factors with stationarity. Among the correlation coefficients, the average temperature in August exhibited the highest values of the stationarity coefficient in relation to the amount of foraged T. matsutake at 0.68 (

Table 3. Correlation coefficients between Tricholoma matsutake foraging and climatic factors exhibiting stationarity.

	Temp. (February)	Temp. (August)	Temp. (December)	Prec. (January)	Prec. (February)	Prec. (March)	Prec. (June)
Corr. with Tricholoma matsutake	−0.15	0.68	0.20	0.14	0.14	−0.01	−0.10

). This result suggested a moderately close relationship between the average temperature in August and the foraged T. matsutake. In the graph, the relationship between the log-transformed amount of foraged T. matsutake and the average temperature in August is clearly evident (Figure 3).

To calculate the amount of foraged T. matsutake based on climatic factors exhibiting stationarity, an OLS model was employed to evaluate the correlation between the foraged matsutake mushroom, temperature, and precipitation. The reliability of the model was evaluated using the R², t-statistic, and p-value, ensuring data robustness. The OLS model’s results are summarized in

Table 4. Linear regression of the correlation between foraged T. matsutake and climatic factors.

Corr. with Tricholoma matsutake	Model	R2	t-Statistic	p-Value
Temp. (February)	log(ŷi) = 8.5101 + (−0.0618)⋅xi	0.02	−0.61	0.55
Temp. (August)	log(ŷi) = (−0.7465) + 0.3883⋅xi	0.46	3.81	<0.01
Temp. (December)	log(ŷi) = 8.3492 + 0.0793⋅xi	0.04	0.86	0.40
Prec. (January)	log(ŷi) = 8.3463 + 0.1127⋅xi	0.02	0.60	0.56
Prec. (February)	log(ŷi) = 8.3088 + 0.1152⋅xi	0.02	0.60	0.56
Prec. (March)	log(ŷi) = 8.4431 + (−0.0047)⋅xi	0.00	−0.03	0.98
Prec. (June)	log(ŷi) = 8.5413 + (−0.0238)⋅xi	0.01	−0.41	0.69

Significance level α = 0.05.

.

Based on the results, only a correlation between the foraged T. matsutake and average temperature in August was identified, thereby demonstrating the reliability of the data.

Using the climatic factors that exhibited high reliability, results for the amount of foraged T. matsutake prediction were constructed using the OLS model. Based on the model results, a 1.5-ton increase in foraged T. matsutake was predicted for every 1-unit increase in August’s average temperature. For the recommended conditions for maximum prediction stability, the August temperature should be between 21.8 °C and 26.2 °C. If the temperature falls outside this range, the model’s predictive power diminishes due to a shift in the temperature pattern, making it impossible to utilize the previously established relationship between the mushroom foraging and temperature. A new correlation coefficient and model must be developed to address such alterations in temperature patterns.

Previous studies on matsutake mushrooms have examined the relationships between the growth of T. matsutake and climatic factors [11,15]. Unfortunately, few studies have investigated the direct relationship between the amount of foraged matsutake mushroom and climatic factors. We compared the results of this study to other studies that examined the correlation between the amount of wild mushrooms harvested and climatic factors. In wild mushrooms, an increase in precipitation causes a higher degree of mushroom foraging [18,28,29]. In the case of the investigation in the Czech Republic into wild mushroom using the ADF test and OLS method, a 21-ton increase in foraged wild mushroom was predicted for every 1-unit increase in the average precipitation. The effects on foraged wild mushroom growth of temperature have also been identified [19,30,31]. For example, using ADF and the Phillips–Perron (PP) test, the correlation coefficient for wild mushroom according to the temperature was 0.61. In addition, high humidity and favorable soil conditions play an important role in the growth and amount of wild mushrooms [28,32]. This relationship can also be identified in the results showing that mushroom production is expected to increase by 23% to 93% when the soil moisture and temperature rise.

As seen in other studies, the increase in the amount of foraged wild mushroom, temperature, and precipitation have a positive relationship. However, this comparison is bound to be limited due to the different growth conditions between wild mushrooms and T. matsutake. Specifically, regarding the soil conditions, while wild mushrooms can grow in a wide range of soil temperatures, T. matsutake requires a narrow range of soil temperatures, between 19 °C and 20 °C. Unlike other wild mushrooms, T. matsutake requires the pine tree as its host. Additionally, regarding the T. matsutake habitat condition, there are specific requirements for soil conditions, such as weak acidity, low nutrient content, and appropriate drainage [6,8,16]. Therefore, a comparison with other studies regarding the correlation between foraged T. matsutake and climatic factors is still necessary to derive more meaningful results from this study.

As mentioned, there are no reports of a significant correlation between the amount of foraged T. matsutake and climatic factors. Instead, several studies have investigated the correlation between climatic factors and the growth of matsutake mycelia in fairy rings in pine forests [6,8,16,32]. These studies suggest that climatic factors, including temperature and precipitation, contribute to the development of T. matsutake mycelia within 5 cm below ground at fairy rings. These findings highlight the positive effect of temperature and precipitation on the dominance of T. matsutake mycelium and the formation of matsutake mushrooms in sterile and dry soils. As climatic factors can influence the soil conditions for matsutake mushrooms, it can be inferred that both temperature and precipitation are closely related to T. matsutake foraging [6,33].

From the correlation analysis, the correlation coefficient of the average temperature in August was 0.68. In comparison with the previous study [19], this correlation coefficient degree indicates a sufficiently high correlation between the amount of foraged matsutake mushroom and the average temperature in August. This positive correlation, however, does not always guarantee a close relationship between matsutake mushroom foraging and climatic factors. In this study, the linear relationships derived using the ADF test and OLS model alone do not fully investigate the correlation between the foraged matsutake mushroom and climatic factors. Furthermore, the t-statistics (3.81) and p-value (<0.01) confirmed that the ADF-OLS model has statistical significance and reliability, but the R² result (0.46) confirmed that the model does not account for half of the data variability in this investigation. The linear relationship and R² result indicate that although the model in this study presents, to some extent, a correlation between matsutake mushroom foraging and the average temperature in August, this temperature cannot be considered the only affecting factor. In other words, in addition to the factors with stationarity in this study, various factors including factors with non-stationarity are likely to affect matsutake mushroom foraging. Despite these limitations, by investigating the relationship between mushroom foraging and temperature in this study, the amount of foraged T. matsutake could be predicted with some reliability, and above all, we were able to secure the factor that significantly influenced the amount of foraged matsutake mushrooms. And this factor, the average temperature in August, could potentially be one of several factors influencing mushroom foraging.

Due to the significant impact of non-stationary factors on growth, it is essential to ensure their stationarity. As mentioned in the above paragraph, the soil conditions, including the soil temperature, soil moisture, and microorganisms in fairy rings, are also expected to significantly affect variables associated with T. matsutake foraging. The capacity to increase the correlation coefficient from moderate to high regarding the average temperature in August is a subject of interest. Due to the accelerating global climate change in the 21st century [19,20], temperature, a crucial factor in matsutake mushroom foraging, may become more optimal during other months compared to August. To respond to this changing climate, various Machine Learning (ML) techniques, such as classification trees, random forest, linear and radial support vector machine, and neural networks, are expected for the investigation of the non-linear relationship between the amount of foraged T. matsutake and various environmental factors [34]. In conclusion, continuously ongoing and continuously revised investigations regarding the linear and non-linear relationships between mushroom foraging and relevant factors are essential to improve the quality of the obtained data and address climatic changes.

4. Conclusions

Since the emergence of human societies, Tricholoma matsutake has been recognized as a popular and valuable mushroom that grows in the sterile, dry soil of pine forests. Temperature and precipitation influence the growth of matsutake mushrooms and the amount of foraged T. matsutake. In this study, employing a 20-year-period meta-analysis on climate variables in Yangyang-gun, we identified a significant positive correlation between matsutake mushroom foraging and the average temperature in August. The correlation coefficient at 0.68 and the relation between a 1-unit increase in temperature and a 1.5-ton increase in mushroom foraging indicated the significant effect of the average temperature in August on T. matsutake foraging. These results are in line with the results of previous studies. However, this relationship is only expected to be one of several relationships between mushroom foraging and external environmental factors. Moreover, the findings of this study are predicated on linear relationships and necessitate the examination of non-linear relationships. Nevertheless, the average temperature in August still significantly affects the amount of foraged T. matsutake. Additionally, with the continuous investigation regarding the correlation between mushroom foraging and the aforementioned factors, the development of a more reliable model to predict the amount of foraged T. matsutake will provide an improved predictive value.