Research Article |
Corresponding author: Huiming Liu ( liuhm_xj@qq.com ) Academic editor: Chris Margules
© 2019 Chuangye Song, Huiming Liu, Jixi Gao.
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation:
Song C, Liu H, Gao J (2019) Habitat preference and potential distribution of Magnolia officinalis subsp. officinalis and M. o. subsp. biloba in China. Nature Conservation 36: 93-111. https://doi.org/10.3897/natureconservation.36.36171
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Magnolia officinalis subsp. officinalis and M. officinalis subsp. biloba are important medicinal plants in China. The bark of these two subspecies is commonly used in the production of a widely-used Chinese traditional medicine named ‘Houpu’. In recent years, M. o. subsp. officinalis and M. o. subsp. biloba have become increasingly threatened owing to the over-harvesting of their bark and the fragmentation of their habitats. In this study, we aimed to support the conservation and cultivation of these two subspecies in China by: (1) assessing the relationship between numerous environmental variables and the geographical distributions of the subspecies; (2) analysing the environmental characteristics of suitable habitats for both subspecies and predicting the spatial distribution of these habitats in China; and (3) identifying conservation areas of both subspecies in China via overlay analysis. We also assessed the degree of human disturbance within suitable habitats. We found that temperature was a major determinant for the distribution of M. o. subsp. officinalis. Conversely, the distribution of M. o. subsp. biloba was primarily dependent on precipitation rather than temperature. Distinct habitat preferences were observed between M. o. subsp. officinalis and M. o. subsp. biloba. Suitable habitats of M. o. subsp. officinalis were primarily distributed in the northern subtropical areas of China, with greater fluctuations in ambient temperature, lower extreme temperatures, less precipitation and greater fluctuations in precipitation. Habitats suitable for M. o. subsp. biloba were highly fragmented and were distributed in the central subtropical areas of China. We found that a large proportion of suitable habitats were not in the protected areas and that they were significantly disturbed by human activity. This analysis could provide useful information for the conservation of both M. o. subsp. officinalis and M. o. subsp. biloba and could aid in the selection of cultivation sites.
Habitat suitability, Maxent, receiver operating curve, nature reserves, human disturbance, Chinese medicine
Magnolia officinalis subsp. officinalis and M. officinalis subsp. biloba are two important medicinal plants in the Magnoliaceae. The bark of these subspecies is used to make a famous traditional Chinese medicine named ‘Houpu’. Houpu has been widely used in traditional Chinese medicinal practices for around 2000 years. Houpu has traditionally been thought to promote the flow of “qi” and blood and to reduce negative energy (
The demand for Houpu has increased dramatically over the last few decades. However, M. o. subsp. officinalis and M. o. subsp. biloba grow at a relatively slow rate and bark can only be harvested from trees that are more than 15 years old. This has led to the over-harvesting of M. o. subsp. officinalis and M. o. subsp. biloba bark. In addition, the two subspecies have poor natural reproductive capacities (
Habitat conservation is an efficient way to protect threatened species (
Thus, the objectives of this study were to: (1) analyse the relationship between environmental conditions and the distribution of M. o. subsp. officinalis and M. officinalis subsp. biloba and to improve our understanding of their habitat preferences; (2) estimate the spatial distribution of suitable habitats in China; and (3) identify the conservation areas and the extent of human disturbance in the suitable habitats. We hope this research will provide technical support for the conservation and cultivation of M. o. subsp. officinalis and M. o. subsp. biloba in China.
According to the Flora of China (Volume 30(1)) (
A total of 241 specimens were reviewed from the Chinese Herbarium (http://www.cvh.ac.cn/) to retrieve the distribution information of M. o. subsp. officinalis and M. o. subsp. biloba. As most specimens were identified as M. o. in the original background information of these specimens, we invited plant taxonomists to re-identify these specimens to the level of subspecies.
We also collected geographical distribution information for both subspecies from the published literature (
Information on nineteen bioclimatic variables was retrieved from WorldClim (http://www.worldclim.org/) (Table
The Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM) was used to derive topographic variables in this research. The vertical accuracy of the ASTER GDEM is 20 m and its horizontal accuracy is 30 m with 95% confidence (
Topographic variables used in this research include altitude, slope and aspect. Slope and aspect were calculated using the Spatial Analyst Tools in ArcGIS (v9.3). Slope helps to identify the rate of maximum change in z-value from each cell and the range of slope values in degrees is 0 to 90 (
To reduce the deleterious effects of collinearity on model fit, the maximum coefficient allowed between pairs of variables was set to 0.7 (
We retrieved data on the spatial distribution of national nature reserves from the Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment of China (http://www.nies.org/). We also retrieved land cover data (2015) of 1-km spatial resolution from the Resources and Environment Data Center of the Chinese Academy of Sciences (http://www.resdc.cn/).
Many software algorithms can be used to calculate habitat suitability using only species presence data, such as Bioclim (
In this study, we used Maxent to evaluate habitat suitability in M. o. subsp. officinalis and M. o. subsp. biloba. We randomly selected 25% of the data entries for each subspecies for use as test data, with the remaining 75% being used to train the model (training data). The Maxent model parameters were set as follows: ‘maximum iterations’ was 500, ‘maximum number of background points’ was 10000, ‘replicates’ was 1 and ‘replicated run type’ was ‘cross-validate’. The ‘convergence threshold’ was 0.00001 and the ‘regularization multiplier’ was 1.
The output ASCII grid produced by Maxent is continuous probability data ranging from 0 to 1, which represents the habitat suitability of a species in a specified region. Based on previous research (
Percent contribution and permutation importance are approaches available in the Maxent software which evaluate the contribution of variables to model predictions. Percent contribution and permutation importance are estimated based on the model gain, which is closely related to the deviance and is used to measure the goodness of fit of the model (
We also fitted response curves to evaluate how habitat suitability responded to variation in the environmental variables. In order to reduce the effects of correlation between pairs of environmental variables on model fit, each response curve was fitted using only one environmental variable. The fitted response curves are shown in Suppl. material
Permutation importance of each environmental variable in determining Magnolia officinalis subsp. officinalis and M. officinalis subsp. biloba distributions
Variable | M. o. subsp. officinalis | M. o. subsp. biloba |
---|---|---|
altitude [m] | 8.8 | 0.3 |
aspect [°] | 0.1 | 0.1 |
slope [°] | 0 | 0.1 |
temperature seasonality | 11.1 | 18.5 |
min. temperature of coldest month [°C] | 74.4 | 1.5 |
mean temperature of wettest quarter [°C] | 0 | 1.4 |
mean diurnal range [°C] | 1.5 | 4.2 |
annual precipitation [mm] | 2.3 | 72.4 |
precipitation of warmest quarter [mm] | 0.7 | 0.5 |
precipitation of driest month [mm] | 1.1 | 1 |
In numerous studies, only presence data (such as herbarium data) was available when attempting to model species distributions and habitat suitability. Absence data (negative records) are rare, despite their usefulness in assessing model specificity. Thus, it was difficult for us to use ROC (receiver operating characteristic curves) to evaluate the performance of the fitted models.
In ROC, the ordinate axis represents the sensitivity, while the abscissa axis represents the false-positive fraction (1-specificity). The AUC (area under curve) is then used to measure the prediction success of the fitted model. AUC values range from 0 to 1; if AUC values are higher than 0.5, the imitative effect of the fitted model is deemed different from random (
We used overlay analysis and maps of national nature reserves and the identified suitable habitats to identify conservation areas where M. o. subsp. officinalis and M. o. subsp. biloba populations were likely to occur. We also used overlay analysis of land cover and the identified suitable habitats to calculate the percentage for each land cover type in the suitable habitats and evaluated the extent to which these habitats have been disturbed by human activity.
Amongst the ten selected variables, the environmental variables which most affected the distribution of M. o. subsp. officinalis were min. temperature of coldest month, followed by temperature seasonality and altitude (Table
M. o. subsp. biloba seems to be more influenced by annual precipitation and extreme precipitation (precipitation of wettest month, precipitation of driest month, precipitation of wettest quarter, precipitation of driest quarter, precipitation of coldest quarter). Temperature fluctuation (temperature seasonality, temperature annual range, isothermality and mean diurnal range) also had notable influences on the distribution of M. o. subsp. biloba.
Habitats suitable for M. officinalis subsp. biloba are mainly located in central subtropical regions (Fig.
Compared to M. officinalis subsp. biloba, M. officinalis subsp. officinalis tends to grow at higher altitudes (Fig.
The spatial distributions of habitats suitable for Magnolia officinalis subsp. officinalis and M. officinalis subsp. biloba.
Approximate ranges of environmental variables suitable for each subspecies based on response curves
Environmental variable | Environmental ranges for M. o. subsp. officinalis | Environmental ranges for M. o. subsp. biloba | |
---|---|---|---|
Topography | altitude [m] | 845–1750 | 156–594 |
aspect[°] | 87–151 | 68–140 | |
Temperature | annual mean temperature [°C] | 11–15 | 16–19.5 |
mean diurnal range [°C] | 6.7–9.2 | 6.4–7.8 | |
isothermality | 26–30 | 25–28.5 | |
temperature seasonality | 663–775 | 687.5–787.5 | |
max. temperature of warmest month [°C] | 24.5–28 | 29.4–32.5 | |
min. temperature of coldest month [°C] | -3.8–-0.63 | 1.9–5 | |
temperature annual range [°C] | 27–29 | 25.6–28.8 | |
mean temperature of wettest quarter [°C] | 18.5–22.8 | 19.4–22.5 | |
mean temperature of driest quarter [°C] | 1.3–5 | 6.9–13.1 | |
mean temperature of warmest quarter [°C] | 20–24 | >24.4 | |
mean temperature of coldest quarter [°C] | 1.3–4.7 | 5–10 | |
Precipitation | annual precipitation [mm] | 1187.5–1500 | 1625–2156 |
precipitation of wettest month [mm] | 194–200 | 265–413 | |
precipitation of driest month [mm] | 16–34 | 43–95 | |
precipitation seasonality | 56–65 | 47–60 | |
precipitation of wettest quarter [mm] | 525–712.5 | 712.5–1000 | |
precipitation of driest quarter [mm] | 50–106 | 169–337.5 | |
precipitation of warmest quarter [mm] | 530–750 | 562.5–750 | |
precipitation of coldest quarter [mm] | 62–112.5 | 184–337.5 |
Overlay analysis of the identified suitable habitats and national nature reserves found that only 8.4% of the habitats suitable for M. officinalis subsp. officinalis were located in national nature reserves. Similarly, for M. o. subsp. biloba, only 3.4% of suitable habitats were located in national nature reserves. Thus, large areas of habitats, suitable for both subspecies, are not protected and are thus at risk (Fig.
Overlay analysis of the identified suitable habitats and land cover found that the majority of land in habitats, suitable for both M. o. subsp. officinalis and M. o. subsp. biloba, is woodland and forest (based on area) (Figs
Land cover status (2015) within the suitable habitats of Magnolia officinalis subsp. officinalis.
The large-scale geographical distribution of vegetation is heavily influenced by the climate (
The reasons for this difference may be due to the different habitat preferences of the two subspecies. Habitats suitable for M. o. subsp. officinalis are mostly located in northern and central subtropical regions at high altitudes (Fig.
The output ASCII grid produced by Maxent is continuous probability data ranging from 0 to 1. A threshold is needed to transform the probability data into binary data (0/1) and to acquire the information about the spatial distribution of suitable habitats. In previous studies, 0.5 (
Maxent uses a variety of methods to determine thresholds, including the minimum training presence, 10th percentile training presence, equal training sensitivity and specificity, maximum training sensitivity plus specificity and so on (Suppl. material
Nature reserves provide effective refugia for wild plants. In this study, only a small number of habitats, suitable for either M. officinalis subsp. officinalis or M. officinalis subsp. biloba, were located in national nature reserves (Fig.
Overlay analysis of land cover data and the locations of suitable habitats found that the majority of land in suitable habitats was woodland and forest (Figs
The geographical distributions of plants are heavily influenced by numerous environmental factors including climate, hydrology, soil, human activity and other factors (
The habitat suitability assessment, conducted in this study, provides a scientific basis for the selection of priority protected areas in the conservation of M. o. subsp. biloba and M. o. subsp. officinalis. In addition to habitat suitability, the genetic diversity of endangered species needs to be considered when selecting priority areas for conservation (
Magnolia officinalis subsp. officinalis and M. officinalis subsp. biloba are closely related subspecies. However, there are marked differences in the geographical distributions of these two subspecies (
China is the ancestral home of the Magnoliaceae, with more than 40% of Magnoliaceae species having originated in southwest China (
In this study, we found that the environmental variables, which influence species distributions, are different for each subspecies. The distribution of M. officinalis subsp. officinalis was primarily determined by variation in minimum temperatures, while the distribution of M. officinalis subsp. biloba was primarily determined by variation in precipitation.
We identified the habitats suitable for both subspecies and found that the two subspecies have distinct habitat preferences. Compared to M. o. subsp. biloba, M. o. subsp. officinalis is found in more northerly areas, grows at higher altitudes and is able to survive in areas experiencing greater fluctuations in ambient temperature, lower extreme temperatures, less precipitation and greater fluctuations in precipitation.
The results of this analysis could provide useful information to support the in situ conservation of both M. o. subsp. officinalis and M. o. subsp. biloba and could aid in the selection of cultivation sites.
In the future, field survey data on the distribution of Magnolia species should be included in the assessment of habitat suitability to offset the deficiencies with regard to the specimen data. Genetic diversity assessment should be performed, together with habitat suitability assessment to provide stronger scientific support for the conservation of Magnolia species.
We thank Dr Shengxiang Yu for prepraring part of the presence data of M. officinalis subsp. officinalis and M. officinalis subsp. biloba.
This work was funded by the CASEarth project (XDA19020301, XDA19050402) of the Chinese Academy of Sciences and the Ministry of Sciences and Technology (The National Key Research and Development Program of China, 2017YFC0503801, 2016YFC0500103).
Tables S1–S3
Data type: statistical data
Explanation note: Table S1. Correlation coefficients between pairs of environmental variables. Table S2. Thresholds estimated by Maxent for the fitted model of Magnolia officinalis subsp. officinalis. Table S3. Thresholds estimated by Maxent for the fitted model of Magnolia officinalis subsp. biloba.
Figures S1–S7
Data type: statistical data
Explanation note: Figure S1. Response curves of habitat suitability to variables of topography of Magnolia officinalis subsp. officinalis. Figure S2. Response curves of habitat suitability to variables of temperature for Magnolia officinalis subsp. officinalis. Figure S3. Response curves of habitat suitability to variables of precipitation for Magnolia officinalis subsp. officinalis. Figure S4. Response curves of habitat suitability to variables of topography for Magnolia officinalis subsp. biloba. Figure S5. Response curves of habitat suitability to variables of temperature for Magnolia officinalis subsp. biloba. Figure S6. Response curves of habitat suitability to variables of precipitation for Magnolia officinalis subsp. biloba. Figure S7. Receiver operating characteristic curves of the fitted models (Fractional predicted area: the fraction of the total study area predicted present; Omission rate: the proportion of the localities falling outside the prediction.).