Assessing Habitat Suitability of Parasitic Plant Cistanche deserticola in Northwest China under Future Climate Scenarios

Effect of global warming on the potential distribution of a holoparasitic plant (Phelypaea tournefortii): both climate and host distribution matter

Phelypaea tournefortii (Orobanchaceae) primarily occurs in the Caucasus (Armenia, Azerbaijan, Georgia, and N Iran) and Turkey. This perennial, holoparasitic herb is achlorophyllous and possesses one of the most intense red flowers among all plants worldwide. It occurs as a parasite on the roots of several Tanacetum (Asteraceae) species and prefers steppe and semi-arid habitats. Climate change may affect holoparasites both directly through effects on their physiology and indirectly as a consequence of its effects on their host plants and habitats. In this study, we used the ecological niche modeling approach to estimate the possible effects of climate change on P. tournefortii and to evaluate the effect of its parasitic relationships with two preferred host species on the chances of survival of this species under global warming. We used four climate change scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5) and three different simulations (CNRM, GISS-E2, INM). We modeled the species' current and future distribution using the maximum entropy method implemented in MaxEnt using seven bioclimatic variables and species occurrence records (Phelypaea tournefortii - 63 records, Tanacetum argyrophyllum - 40, Tanacetum chiliophyllum - 21). According to our analyses, P. tournefortii will likely contract its geographical range remarkably. In response to global warming, the coverage of the species' suitable niches will decrease by at least 34%, especially in central and southern Armenia, Nakhchivan in Azerbaijan, northern Iran, and NE Turkey. In the worst-case scenario, the species will go completely extinct. Additionally, the studied plant's hosts will lose at least 36% of currently suitable niches boosting the range contraction of P. tournefortii. The GISS-E2 scenario will be least damaging, while the CNRM will be most damaging to climate change for studied species. Our study shows the importance of including ecological data in niche models to obtain more reliable predictions of the future distribution of parasitic plants.

Identifying the natural reserve area of Cistanche salsa under the effects of multiple host plants and climate change conditions using a maximum entropy model in Xinjiang, China

Cistanche salsa (C. A. Mey.) G. Beck, a holoparasitic desert medicine plant with multiple hosts, is regarded as a potential future desert economic plant. However, as a result of excessive exploitation and poaching, its wild resources have become scarce. Thus, before developing its desert economic value, this plant has to be protected, and the identification of its natural reserve is currently the top priority. However, in previous nature reserve prediction studies, the influence of host plants has been overlooked, particularly in holoparasitic plants with multiple hosts. In this study, we sought to identify the conservation areas of wild C. salsa by considering multiple host-plant interactions and climate change conditions using the MaxEnt model. Additionally, a Principal Component Analysis (PCA) was used to reduce the autocorrelation between environmental variables. The effects of the natural distribution of the host plants in terms of natural distribution from the perspective of niche similarities and extrapolation detection were considered by filtering the most influential hosts: Krascheninnikovia ceratoides (Linnaeus), Gueldenstaedt, and Nitraria sibirica Pall. Additionally, the change trends in these hosts based on climate change conditions combined with the change trends in C. salsa were used to identify a core protection area of 126483.5 km². In this article, we corrected and tried to avoid some of the common mistakes found in species distribution models based on the findings of previous research and fully considered the effects of host plants for multiple-host holoparasitic plants to provide a new perspective on the prediction of holoparasitic plants and to provide scientific zoning for biodiversity conservation in desert ecosystems. This research will hopefully serve as a significant reference for decision-makers.

Predicting the potential distribution of four endangered holoparasites and their primary hosts in China under climate change

Climate change affects parasitic plants and their hosts on distributions. However, little is known about how parasites and their hosts shift in distribution, and niche overlap in response to global change remains unclear to date. Here, the potential distribution and habitat suitability of four endangered holoparasites and their primary hosts in northern China were predicted using MaxEnt based on occurrence records and bioclimatic variables. The results indicated that (1) Temperature annual range (Bio7) and Precipitation of driest quarter (Bio17) were identified as the common key climatic factors influencing distribution (percentage contribution > 10%) for Cynomorium songaricum vs. Nitraria sibirica (i.e., parasite vs. host); Temperature seasonality (Bio4) and Precipitation of driest month (Bio14) for Boschniakia rossica vs. Alnus mandshurica; Bio4 for Cistanche deserticola vs. Haloxylon ammodendron; Precipitation of warmest quarter (Bio18) for Cistanche mongolica vs. Tamarix ramosissima. Accordingly, different parasite-host pairs share to varying degree the common climatic factors. (2) Currently, these holoparasites had small suitable habitats (i.e., moderately and highly) (0.97-3.77%), with few highly suitable habitats (0.19-0.81%). Under future scenarios, their suitable habitats would change to some extent; their distribution shifts fell into two categories: growing type (Boschniakia rossica and Cistanche mongolica) and fluctuating type (Cynomorium songaricum and Cistanche deserticola). In contrast, the hosts' current suitable habitats (1.42-13.43%) varied greatly, with highly restricted suitable habitats (0.18-1.00%). Under future scenarios, their suitable habitats presented different trends: growing type (Nitraria sibirica), declining type (Haloxylon ammodendron) and fluctuating type (the other hosts). (3) The niche overlaps between parasites and hosts differed significantly in the future, which can be grouped into two categories: growing type (Boschniakia rossica vs. Alnus mandshurica, Cistanche mongolica vs. Tamarix ramosissima), and fluctuating type (the others). Such niche overlap asynchronies may result in severe spatial limitations of parasites under future climate conditions. Our findings indicate that climate factors restricting parasites and hosts' distributions, niche overlaps between them, together with parasitic species identity, may jointly influence the suitable habitats of parasitic plants. Therefore, it is necessary to take into account the threatened holoparasites themselves in conjunction with their suitable habitats and the parasite-host association when developing conservation planning in the future.

The Influence of Climate Change on Three Dominant Alpine Species under Different Scenarios on the Qinghai–Tibetan Plateau

The Qinghai–Tibetan Plateau (QTP) with high altitude and low temperature is one of the most sensitive areas to climate change and has recently experienced continuous warming. The species distribution on the QTP has undergone significant changes especially an upward shift with global warming in the past decades. In this study, two dominant trees (Picea crassifolia Kom and Sabina przewalskii Kom) and one dominant shrub (Potentilla parvifolia Fisch) were selected and their potential distributions using the MaxEnt model during three periods (current, the 2050s and the 2070s) were predicted. The predictions were based on four shared socio-economic pathway (SSPs) scenarios, namely, SSP2.6, SSP4.5, SSP7.0, SSP8.5. The predicted current potential distribution of three species was basically located in the northeastern of QTP, and the distribution of three species was most impacted by aspect, elevation, temperature seasonality, annual precipitation, precipitation of driest month, Subsoil CEC (clay), Subsoil bulk density and Subsoil CEC (soil). There were significant differences in the potential distribution of three species under four climate scenarios in the 2050s and 2070s including expanding, shifting, and shrinking. The total suitable habitat for Picea crassifolia shrank under SSP2.6, SSP4.5, SSP7.0 and enlarged under SSP8.5 in the 2070s. On the contrary, the total suitable habitat for Sabina przewalskii enlarged under SSP2.6, SSP4.5, SSP7.0 and shrank under SSP8.5 in the 2070s. The total suitable habitat for Potentilla parvifolia continued to increase with SSP2.6 to SSP8.5 in the 2070s. The average elevation in potentially suitable habitat for Potentilla parvifolia all increased except under SSP8.5 in the 2050s. Our study provides an important reference for the conservation of Picea crassifolia, Sabina przewalskii, Potentilla parvifolia and other dominant plant species on the QTP under future climate change.

Predicting the suitable habitats of parasitic desert species based on a niche model with Haloxylon ammodendron and Cistanche deserticola as examples

Haloxylon ammodendron, an excellent tree species for sand fixation and afforestation in the desert areas of western China, is threatened by climate change and anthropogenic activities. The suitable habitat of this species is shrinking at a remarkable rate, although conservation measures have been implemented. Cistanche deserticola is an entirely parasitic herb that occurs in deserts, is a source of "desert ginseng" worldwide, and has extremely high medicinal value. Little is known about using niche models to simulate habitat suitability and evaluate important environmental variables related to parasitic species. In this study, we modeled the current suitable habitat of H. ammodendron and C. deserticola by MaxEnt based on occurrence record data of the distributions of these two species in China. We grouped H. ammodendron and C. deserticola into three groups according to the characteristics of parasitic species and modeled them with environmental factors. The results showed that bioclimate was the most important environmental parameter affecting the H. ammodendron and C. deserticola distribution. Precipitations, such as annual precipitation, precipitation seasonality, and precipitation in the driest quarter, were identified as the most critical parameters. The slope, diurnal temperature range, water vapor pressure, ground-frost frequency, and solar radiation also substantially contributed to the distribution of the two species. The proportions of the most suitable areas for Groups 1, 2, and 3 were 1.2%, 1.3%, and 1.7%, respectively, in China. When combined with cultural geography, five hot spot conservation areas were determined within the distribution of H. ammodendron and C. deserticola. The comprehensive analysis indicated that by using MaxEnt to model the suitable habitat of parasitic species, we further improved the accuracy of the prediction and coupled the error of the distribution of a single species. This study provides a useful reference for the protection of H. ammodendron forests and the management of C. deserticola plantations.

Habitat potential modelling and mapping of Teucrium polium using machine learning techniques

Determining suitable habitats is important for the successful management and conservation of plant and wildlife species. Teucrium polium L. is a wild plant species found in Iran. It is widely used to treat numerous health problems. The range of this plant is shrinking due to habitat destruction and overexploitation. Therefore, habitat suitability (HS) modeling is critical for conservation. HS modeling can also identify the key characteristics of habitats that support this species. This study models the habitats of T. polium using five data mining models: random forest (RF), flexible discriminant analysis (FDA), multivariate adaptive regression splines (MARS), support vector machine (SVM), and generalized linear model (GLM). A total of 119 T. poliumlocations were identified and mapped. According to the RF model, the most important factors describing T. polium habitat were elevation, soil texture, and mean annual rainfall. HS maps (HSMs) were prepared, and habitat suitability was classified as low, medium, high, or very high. The percentages of the study area assigned high or very high suitability ratings by each of the models were 44.62% for FDA, 43.75% for GLM, 43.12% for SVM, 38.91% for RF, 28.72% for MARS, and 39.16% for their ensemble. Although the six models were reasonably accurate, the ensemble model had the highest AUC value, demonstrating a strong predictive performance. The rank order of the other models in this regard is RF, MARS, SVM, FDA, and GLM. HSMs can provide useful output to support the sustainable management of rangelands, reclamation, and land protection.

Predicting the invasive trend of exotic plants in China based on the ensemble model under climate change: A case for three invasive plants of Asteraceae

Ageratina adenophora, Eupatorium odoratum, and Mikania micrantha are three highly destructive invasive plants of Compositae in China. Through the screening of SDMs, random forest (RF), gradient boosting model (GBM), artificial neural network (ANN), and flexible discriminant analysis (FDA) with TSS greater than 0.8 are selected to construct a high-precision ensemble model (EM) as the prediction model. We use specimen sites and environmental variables containing climate, soil, terrain, and human activities to simulate and predict the invasion trend of three invasive weeds in China in current, the 2050s, and the 2070s. Results indicate that the highly invasive risk area of three exotic plants is mostly distributed along the river in the provinces south of 30° N. In the future scenario, the three exotic plants obviously invade northwards Yunnan, Sichuan, Guizhou, Jiangxi and Fujian. Climate is the most important variable that affects the spread of three kinds of alien plant invasions. Temperature and precipitation variables have a similar effect on A. adenophora and E. odoratum, while M. micrantha is more sensitive to temperature. It has been reported that Ipomoea batatas and Vitex negundo can prevent the invasion of three invasive plants. Hence, we also simulate the suitable planting areas for I. batatas and V. negundo. The results show that I. batatas and V. negundo are suitable to be planted in the areas where the three weeds show invasion tendency. In the paper, predicting invasion trends of exotic plants and simulating the planting suitability of crops that can block invasion, to provide a practical significance reference and suggestion for the management, prevention, and control of the invasion of exotic plants in China.

Impact of Past and Future Climate Change on the Potential Distribution of an Endangered Montane Shrub Lonicera oblata and Its Conservation Implications

Climate change is an important driver of biodiversity patterns and species distributions, understanding how organisms respond to climate change will shed light on the conservation of endangered species. In this study, we modeled the distributional dynamics of a critically endangered montane shrub Lonicera oblata in response to climate change under different periods by building a comprehensive habitat suitability model considering the effects of soil and vegetation conditions. Our results indicated that the current suitable habitats for L. oblata are located scarcely in North China. Historical modeling indicated that L. oblata achieved its maximum potential distribution in the last interglacial period which covered southwest China, while its distribution area decreased for almost 50% during the last glacial maximum. It further contracted during the middle Holocene to a distribution resembling the current pattern. Future modeling showed that the suitable habitats of L. oblata contracted dramatically, and populations were fragmentedly distributed in these areas. As a whole, the distribution of L. oblata showed significant migration northward in latitude but no altitudinal shift. Several mountains in North China may provide future stable climatic areas for L. oblata, particularly, the intersections between the Taihang and Yan mountains. Our study strongly suggested that the endangered montane shrub L. oblata are sensitive to climate change, and the results provide new insights into the conservation of it and other endangered species.

The Global Potential Distribution of Invasive Plants: Anredera cordifolia under Climate Change and Human Activity Based on Random Forest Models

The potential distribution of the invasive plant Anredera cordifolia (Tenore) Steenis was predicted by Random Forest models under current and future climate-change pathways (i.e., RCP4.5 and RCP8.5 of 2050s and the 2070s). Pearson correlations were used to select variables; the prediction accuracy of the models was evaluated by using AUC, Kappa, and TSS. The results show that suitable future distribution areas are mainly in Southeast Asia, Eastern Oceania, a few parts of Eastern Africa, Southern North America, and Eastern South America. Temperature is the key climatic factor affecting the distribution of A. cordifolia. Important metrics include mean temperature of the coldest quarter (0.3 °C ≤ Bio11 ≤ 22.9 °C), max temperature of the warmest month (17.1 °C ≤ Bio5 ≤ 35.5 °C), temperature annual range (10.7 °C ≤ Bio7 ≤ 33 °C), annual mean air temperature (6.8 °C ≤ Bio1 ≤ 24.4 °C), and min temperature of coldest month (−2.8 °C ≤ Bio6 ≤ 17.2 °C). Only one precipitation index (Bio19) was important, precipitation of coldest quarter (7 mm ≤ Bio19 ≤ 631 mm). In addition, areas with strong human activities are most prone to invasion. This species is native to Brazil, but has been introduced in Asia, where it is widely planted and has escaped from cultivation. Under the future climate scenarios, suitable habitat areas of A. cordifolia will expand to higher latitudes. This study can provide a reference for the rational management and control of A. cordifolia.

Non-Pessimistic Predictions of the Distributions and Suitability of Metasequoia glyptostroboides under Climate Change Using a Random Forest Model

Metasequoia glyptostroboides Hu & W. C. Cheng, which is a remarkable rare relict plant, has gradually been reduced to its current narrow range due to climate change. Understanding the comprehensive distribution of M. glyptostroboides under climate change on a large spatio-temporal scale is of great significance for determining its forest adaptation. In this study, based on 394 occurrence data and 10 bioclimatic variables, the global potential distribution of M. glyptostroboides under eight different climate scenarios (i.e., the past three, the current one, and the next four) from the Quaternary glacial to the future was simulated by a random forest model built with the biomod2 package. The key bioclimatic variables affecting the distribution of M. glyptostroboides are BIO2 (mean diurnal range), BIO1 (annual mean temperature), BIO9 (mean temperature of driest quarter), BIO6 (min temperature of coldest month), and BIO18 (precipitation of warmest quarter). The result indicates that the temperature affects the potential distribution of M. glyptostroboides more than the precipitation. A visualization of the results revealed that the current relatively suitable habitats of M. glyptostroboides are mainly distributed in East Asia and Western Europe, with a total area of approximately 6.857 × 106 km2. With the intensification of global warming in the future, the potential distribution and the suitability of M. glyptostroboides have a relatively non-pessimistic trend. Whether under the mild (RCP4.5) and higher (RCP8.5) emission scenarios, the total area of suitable habitats will be wider than it is now by the 2070s, and the habitat suitability will increase to varying degrees within a wide spatial range. After speculating on the potential distribution of M. glyptostroboides in the past, the glacial refugia of M. glyptostroboides were inferred, and projections regarding the future conditions of these places are expected to be optimistic. In order to better protect the species, the locations of its priority protected areas and key protected areas, mainly in Western Europe and East Asia, were further identified. Our results will provide theoretical reference for the long-term management of M. glyptostroboides, and can be used as background information for the restoration of other endangered species in the future.