Sociodemographic characteristics of the study participants

The MEP use surveys consisted of semi-structured interviews with a total of 122 people in six focus group discussions. The study informants were divided into groups according to age as follows: < 30, 31–40, 41–50, 51–60, and > 60 years old. Most informants were in the 51–60 (51.6%), 41–50 (20.5%), and 31–40 (14.8%) age groups, a distribution that was representative of the main users of ethnic medicine and knowledge inheritors. Few individuals in the youngest (< 30 years old; 5.7%) and oldest (> 60 years old; 7.4%) age categories were interviewed (Table S2).

Plant biodiversity in the Daur minority area

The field survey collected data in the Ewenki Autonomous Banner, the Arun Banner, Zhalantun City, and the Molidawar Daur Autonomous Banner for several years. A total of 501 species of plants, which belonged to 87 families and 284 genera, were thoroughly studied and recorded. Asteraceae was the dominant plant family used (75 species), followed by Rosaceae (37 species), Ranunculaceae and Leguminosae (32 species each), and Lamiaceae (30 species).

Diversity of MEPs used by the Daur

In total, 52 species of commonly used MEPs from 29 families and 47 genera were identified using the UV (Table 1). Among them, Rosaceae was the dominant plant family used (seven species), followed by Asteraceae (six species), Amaryllidaceae (four species), Ranunculaceae and Lamiaceae (three species each), and Betulaceae, Cucurbitaceae, Apiaceae, Urticaceae, and Poaceae (two species each). The remaining 19 families (Salicaceae, Cannabaceae, Polygonaceae, Amaranthaceae, Grossulariaceae, Euphorbiaceae, Araliaceae, Ericaceae, Solanaceae, Plantaginaceae, Viburnaceae, Liliaceae, Asphodelaceae, Typhaceae, Fabaceae, Zingiberaceae, Brassicaceae, Rhamnaceae, and Phrymaceae) were represented by one species each. Herbs (39 species, 75%) were the commonly used MEP type, followed by trees (seven species, 13.5%) and shrubs (six species, 11.5%). In the past, most MEPs were collected from the natural environment, but now, with the increasing use of herbal medicines for different purposes, the extent of cultivation has increased, and therefore, approximately 42.3% of these MEPs can be obtained through cultivation.

Table 1 List of frequently used MEPs by the Daur in Inner Mongolia, China

Depending on the plant, various parts may be used in the treatment of diseases. According to the informants, the most commonly used parts are as follows: all parts of the plant (12 species), followed by the root and seed (10 species each); fruit (7 species); leaf (6 species); bulb, rhizome, bark, branch, flower, and seed oil (2 species each); and root nodules, leaf sheath, and tree sap (1 species each) (Fig. 3). Notably, the Daur people predominantly used easily accessible and regenerating aboveground parts of MEPs, which differs from the approach used in traditional Chinese medicine. This largely balances the use of MEPs with the conservation of natural resources.

Fig. 3

The statistics of the used parts for MEPs of Daur ethnic group

We also collected information on the administration route, preparation, dosage, and usage of MEPs by the Daur people. According to the present study, MEPs were prepared via decocting, smashing, boiling, extracting, and burning. They were most often ingested as pills or powder or cooked with ingredients such as milk, honey, wine, vinegar, oats, sesame oil, egg white, rice bran, beans, barley, nuts, the crucian carp, or a pig stomach. Some MEPs were used externally in the form of a wash, fumigate, or wrap. Dosages were estimated for most MEPs and were dependent on the age of the patient, severity of the illness, diagnosis, and experience of the healer.

Use value

The Daur group with ethnobotanical knowledge on their application considered MEPs to be primarily suitable for single therapeutic uses or health benefits (36%), followed by two aspects (34%) and three or more aspects (30%). The quantitative UV indices revealed that the MEPs most used as medicines are B. pendula subsp. mandshurica (with a UV of 1.07), Artemisia integrifolia, Actaea dahurica, Crataegus pinnatifida, Saposhnikovia divaricata, Artemisia argyi, and Jacobaea cannabifolia (all with UVs of 1.00) and Fagopyrum esculentum, Avena sativa, and Perilla frutescens (with a UV of 0.99, 0.99, and 0.93, respectively). Many parts of these plant species, which are readily available or are typical species in the area, are used as a health food and a medicine.

Informant consensus factor

The ICF was used to identify plants of particular intercultural relevance and evaluate how homogenous the obtained information was. Overall, 11 disease categories were identified. The ICF was calculated for each disease category, and it ranged from 0.93 to 1.00. The highest ICF (1.00) was obtained for tumour, which involved one species and one use report. However, the high ICF value for this classification may be related to the low number of cases. The classification with the second highest ICF was for rheumatic immunity system problem (0.99) with 5 species and 534 use reports. The high values achieved in the study probably indicate a high degree of consensus among the informants. The classification with the third highest ICF was for skin problem (0.98) with 6 species and 305 use reports, where the use of medicinal species was random, and no consensus was reported among the informants (Table S4).

Health benefits and therapeutic uses of MEPs by the Daur

Table 1 presents MEPs utilised by the Daur for 85 therapeutic uses; these were classified into 11 groups based on the intended body system or targeted health category. The availability of the network model structure may improve our understanding of the relationships between MEPs, health benefits, therapeutic uses, and medical classification. According to the network statistics, the number of nodes was 129, the number of edges was 194, and the average node betweenness was 416 (Fig. 4). Statistically, the ‘Digestive system’ category was most frequently detected and included 22 health benefits and therapeutic uses, including those for dental disease, diarrhoea, gastric ulcer, loss of appetite, cough, dyspepsia, gaseous abdominal distention, enteritis, hepatitis, abdominal pain, dysentery, laryngeal carcinoma, rheumatism, weakness, lethargy, acute gastroenteritis, and stomach flu. Other categories included ‘Infectious or parasitic’, ‘Rheumatic immunity system’, ‘Respiratory system’, and ‘Trauma’. Treatment for rheumatism, trauma, cough, diarrhoea, and chronic nephritis were among more important health benefits and therapeutic uses. The health benefits and therapeutic use classification indicated a link between traditional MEP knowledge and modern medicine; however, the MEP knowledge of the Daur ethnic group retained its inherent characteristics. Among the uses, various common ailments (cough, constipation, diarrhoea, and trauma) and endemic diseases (rheumatism and rheumatoid arthritis) were treated with numerous therapies as part of the basic health service provision (Table 2).

Fig. 4

Network visualisation of the relationships between health benefits, therapeutic uses, body system classification and MEPs

Table 2 Top 5 nodes of MEPs, health benefits, therapeutic uses, and body system classification in the network ranked by the betweenness centrality value in “cytoNCA”Relationship among cultural, socio-economic, and resource factors with MEPs

The SD model method considers the dynamic interactions among multiple factors and thus meets the requirements of simulation systems and can more clearly represent changing relationships. We present a model with four closely related subsystems: resources, culture, socioeconomic factors, and MEP use. Flowcharts demonstrating the relationships among and between the variables of each subsystem are shown in Fig. 6. The resources’ subsystem includes resource protection, exploitation, and overexploitation. This subsystem describes the interrelationship among various elements of sustainable resource use. The culture subsystem includes education quality. Higher education systems often negatively affect the spread of ethnic languages and religious beliefs, but promote further communication of the scientific literature. The socioeconomic subsystem includes urbanisation, large-scale farming, economic growth, and the population. This subsystem mainly describes how changes in societal norms and economic development affect the major production modes and lifestyle traits of individuals within the population. The negative ( +) and positive (-) markers associated with each arrow indicate the direction of influence of each factor on the others. The series of positive and negative causal relationships among the three subsystems and the use of MEPs form the causal feedback loops of this study.