Forests
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Predicting the Potential Distribution of Perennial Plant Coptis chinensis Franch. in China under Multiple Climate Change Scenarios Coptis chinensis Franch. (Ranales: Ranunculaceae) is a perennial species with high medicinal value. Predicting the potentially geographical distribution patterns of C. chinensis against the background of climate change can facilitate its protection and sustainable utilization. This study employed the optimized maximum entropy model to predict the distribution patterns and changes in potentially suitable C. chinensis’ regions in China under multiple climate change scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) across different time periods (1970–2000, 2050s, 2070s, and 2090s). The results revealed that the currently potentially suitable regions of C. chinensis span an area of 120.47 × 104 km2, which accounts for 12.54% of China’s territory. Among these areas, the low, moderate, and highly suitable regions are 80.10 × 104 km2, 37.16 × 104 km2, and 3.21 × 104 km2, respectively. The highly suitable regions are primarily distributed in Chongqing, Guizhou, Zhejiang, Hubei, and Hunan Provinces. Over time, the potentially suitable regions of C. chinensis are predicted to shrink. Furthermore, our study revealed that the relatively low impact areas of C. chinensis were mainly distributed in Yunnan, Guizhou, Hubei, Chongqing, and other Provinces. Centroid transfer analysis indicated that except for SSP1-2.6, the center of the potentially suitable region of C. chinensis showed a trend of gradual transfer to the northwest and high-altitude areas.
Forests - Tập 12 Số 11 - Trang 1464
Optimized Maxent Model Predictions of Climate Change Impacts on the Suitable Distribution of Cunninghamia lanceolata in China Climate change significantly influences changes in ecological phenomena and processes, such as species distribution and phenology, thus accelerating the rate of species extinction or prosperity. Climate change is considered to be one of the most important threats to global biodiversity in the 21st century and will pose significant challenges to biodiversity conservation in the future. The use of niche modelling to predict changes in the suitable distribution of species under climate change scenarios is becoming a hot topic of biological conservation. In this study, we use data from China’s National Forest Continuous Inventory as well as specimen collection data of Cunninghamia lanceolata (Lamb.) Hook to run optimized Maxent models to predict potential suitable distribution of the species in the present day, 2050s, and 2070s under different climate change scenarios in China. In the modeling process, the most important uncorrelated variables were chosen, and the sample-size-adjusted Akaike information criterion (AICc) was used to select the optimal combination of feature type and regularization multiplier. Variable selection reduced the number of variables used and the complexity of the model, and the use of the AICc reduced overfitting. Variables relating to precipitation were more important than temperature variables in predicting C. lanceolata distribution in the optimal model. The predicted suitable distribution areas of C. lanceolata were different for the different periods under different climate change scenarios, with the centroids showing a degree of northward movement. The suitable distribution area is predicted to become more fragmented in the future. Our results reveal the climate conditions required for the suitable distribution of C. lanceolata in China and the likely changes to its distribution pattern in the future, providing a scientific basis for the sustainable management, protection, and restoration of the suitable habitat of this economically important tree species in the context of climate change.
Forests - Tập 11 Số 3 - Trang 302
Predicting the Potential Distribution of Two Varieties of Litsea coreana (Leopard-Skin Camphor) in China under Climate Change Climate change considerably affects vegetation growth and may lead to changes in vegetation distribution. Leopard-skin camphor is an endangered species, and the main raw material for hawk tea, and has various pharmacodynamic functions. Studying the potential distribution of two leopard-skin camphor varieties under climate change should assist in the effective protection of these species. We collected the distribution point data for 130 and 89 Litsea coreana Levl. var. sinensis and L. coreana Levl. var. lanuginosa, respectively, and data for 22 environmental variables. We also predicted the potential distribution of the two varieties in China using the maximum entropy (MaxEnt) model and analyzed the key environmental factors affecting their distribution. Results showed that the two varieties are mainly located in the subtropical area south of the Qinling Mountains–Huai River line in the current and future climate scenarios, and the potentially suitable area for L. coreana Levl. var. lanuginosa is larger than that of L. coreana Levl. var. sinensis. Compared with current climatic conditions, the potentially suitable areas of the two leopard-skin camphor varieties will move to high-latitude and -altitude areas and the total suitable area will increase slightly, while moderately and highly suitable areas will be significantly reduced under future climatic scenarios. For example, under a 2070-RCP8.5 (representative of a high greenhouse gas emission scenario in the 2070s) climatic scenario, the highly suitable areas of L. coreana Levl. var. sinensis and L. coreana Levl. var. lanuginosa are 6900 and 300 km2, and account for only 10.27% and 0.21% of the current area, respectively. Temperature is the key environmental factor affecting the potential distribution of the two varieties, especially the mean daily diurnal range (Bio2) and the min temperature of the coldest month (Bio6). The results can provide a reference for relevant departments in taking protective measures to prevent the decrease or extinction of the species under climate change.
Forests - Tập 11 Số 11 - Trang 1159
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.
Forests - Tập 12 Số 2 - Trang 125
Climatic Change Can Influence Species Diversity Patterns and Potential Habitats of Salicaceae Plants in China Salicaceae is a family of temperate woody plants in the Northern Hemisphere that are highly valued, both ecologically and economically. China contains the highest species diversity of these plants. Despite their widespread human use, how the species diversity patterns of Salicaceae plants formed remains mostly unknown, and these may be significantly affected by global climate warming. Using past, present, and future environmental data and 2673 georeferenced specimen records, we first simulated the dynamic changes in suitable habitats and population structures of Salicaceae. Based on this, we next identified those areas at high risk of habitat loss and population declines under different climate change scenarios/years. We also mapped the patterns of species diversity by constructing niche models for 215 Salicaceae species, and assessed the driving factors affecting their current diversity patterns. The niche models showed Salicaceae family underwent extensive population expansion during the Last Inter Glacial period but retreated to lower latitudes during and since the period of the Last Glacial Maximum. Looking ahead, as climate warming intensifies, suitable habitats will shift to higher latitudes and those at lower latitudes will become less abundant. Finally, the western regions of China harbor the greatest endemism and species diversity of Salicaceae, which are significantly influenced by annual precipitation and mean temperature, ultraviolet-B (UV-B) radiation, and the anomaly of precipitation seasonality. From these results, we infer water–energy dynamic equilibrium and historical climate change are both the main factors likely regulating contemporary species diversity and distribution patterns. Nevertheless, this work also suggests that other, possibly interacting, factors (ambient energy, disturbance history, soil condition) influence the large-scale pattern of Salicaceae species diversity in China, making a simple explanation for it unlikely. Because Southwest China likely served as a refuge for Salicaceae species during the Last Glacial Maximum, it is a current hotspot for endemisms. Under predicted climate change, Salicaceae plants may well face higher risks to their persistence in southwest China, so efforts to support their in-situ conservation there are urgently needed.
Forests - Tập 10 Số 3 - Trang 220
Predicting the Potential Distribution of Paeonia veitchii (Paeoniaceae) in China by Incorporating Climate Change into a Maxent Model A detailed understanding of species distribution is usually a prerequisite for the rehabilitation and utilization of species in an ecosystem. Paeonia veitchii (Paeoniaceae), which is an endemic species of China, is an ornamental and medicinal plant that features high economic and ecological values. With the decrease of its population in recent decades, it has become a locally endangered species. In present study, we modeled the potential distribution of P. veitchii under current and future conditions, and evaluated the importance of the factors that shape its distribution. The results revealed a highly and moderately suitable habitat for P. veitchii that encompassed ca. 605,114 km2. The central area lies in northwest Sichuan Province. Elevation, temperature seasonality, annual mean precipitation, and precipitation seasonality were identified as the most important factors shaping the distribution of P. veitchii. Under the scenario with a low concentration of greenhouse gas emissions (RCP 2.6), we predicted an overall expansion of the potential distribution by 2050, followed by a slight contraction in 2070. However, with the scenario featuring intense greenhouse gas emissions (RCP 8.5), the range of suitable habitat should increase with the increasing intensity of global warming. The information that was obtained in the present study can provide background information related to the long-term conservation of this species.
Forests - Tập 10 Số 2 - Trang 190
Landscape-Scale Mixtures of Tree Species are More Effective than Stand-Scale Mixtures for Biodiversity of Vascular Plants, Bryophytes and Lichens Tree species diversity can positively affect the multifunctionality of forests. This is why conifer monocultures of Scots pine and Norway spruce, widely promoted in Central Europe since the 18th and 19th century, are currently converted into mixed stands with naturally dominant European beech. Biodiversity is expected to benefit from these mixtures compared to pure conifer stands due to increased abiotic and biotic resource heterogeneity. Evidence for this assumption is, however, largely lacking. Here, we investigated the diversity of vascular plants, bryophytes and lichens at the plot (alpha diversity) and at the landscape (gamma diversity) level in pure and mixed stands of European beech and conifer species (Scots pine, Norway spruce, Douglas fir) in four regions in Germany. We aimed to identify compositions of pure and mixed stands in a hypothetical forest landscape that can optimize gamma diversity of vascular plants, bryophytes and lichens within regions. Results show that gamma diversity of the investigated groups is highest when a landscape comprises different pure stands rather than tree species mixtures at the stand scale. Species mainly associated with conifers rely on light regimes that are only provided in pure conifer forests, whereas mixtures of beech and conifers are more similar to beech stands. Combining pure beech and pure conifer stands at the landscape scale can increase landscape level biodiversity and conserve species assemblages of both stand types, while landscapes solely composed of stand scale tree species mixtures could lead to a biodiversity reduction of a combination of investigated groups of 7 up to 20%.
Forests - Tập 10 Số 1 - Trang 73
Generalized Nonlinear Mixed-Effects Individual Tree Diameter Increment Models for Beech Forests in Slovakia Individual tree growth and yield models precisely describe tree growth irrespective of stand complexity and are capable of simulating various silvicultural alternatives in the stands with diverse structure, species composition, and management history. We developed both age dependent and age independent diameter increment models using long-term research sample plot data collected from both monospecific and mixed stands of European beech (Fagus sylvatica L.) in the Slovak Republic. We used diameter at breast height (DBH) as a main predictor and other characteristics describing site quality (site index), stand development stage (dominant height and stand age), stand density or competition (ratio of individual tree DBH to quadratic mean diameter), species mixture (basal area proportion of a species of interest), and dummy variable describing stand management regimes as covariate predictors to develop the models. We evaluated eight versatile growth functions in the first stage using DBH as a single predictor and selected the most suitable one, i.e., Chapman-Richards function for further analysis through the inclusion of covariate predictors. We introduced the random components describing sample plot-level random effects and stochastic variations on the diameter increment, into the models through the mixed-effects modelling. The autocorrelation caused by hierarchical data-structure, which is assumed to be partially reduced by mixed-effects modelling, was removed through the inclusion of the parameter accounting for the autoregressive error-structures. The models described about two-third parts of a total variation in the diameter increment without significant trends in the residuals. Compared to the age independent mixed-effects model (conditional coefficient of determination, R c 2 = 0.6566; root mean square error, RMSE = 0.1196), the age dependent model described a significantly larger proportion of the variations in diameter increment ( R c 2 = 0.6796, RMSE = 0.1141). Diameter increment was significantly influenced differently by covariate predictors included into the models. Diameter increment decreased with the advancement of stand development stage (increased dominant height and stand age), increasing intraspecific competition (increased basal area proportion of European beech per sample plot), and diameter increment increased with increasing site quality (increased site index) and decreased competition (increased ratio of DBH to quadratic mean diameter). Our mixed-effects models, which can be easily localized with the random effects estimated from prior measurement of diameter increments of four randomly selected trees per sample plot, will provide high prediction accuracies. Our models may be used for simulating growth of European beech irrespective of its stand structural complexity, as these models have included various covariate variables describing both tree-and stand-level characteristics, thinning regimes, except the climate characteristics. Together with other forest models, our models will be used as inputs to the growth simulator to be developed in the future, which is important for decision-making in forestry.
Forests - Tập 10 Số 5 - Trang 451
Individual Tree Diameter and Height Growth Models for 30 Tree Species in Mixed-Species and Uneven-Aged Forests of Mexico Lack of knowledge of individual tree growth in species-rich, mixed forest ecosystems impedes their sustainable management. In this study, species-specific models for predicting individual diameter at breast height (dbh) and total tree height (h) growth were developed for 30 tree species growing in mixed and uneven-aged forest stands in Durango, Mexico. Growth models were also developed for all pine, all oaks, and all other species of the genus Arbutus (strawberry trees). A database of 55,158 trees with remeasurements of dbh and h of a 5-year growth period was used to develop the models. The data were collected from 217 stem-mapped plots located in the Sierra Madre Occidental (Mexico). Weighted regression was used to remove heteroscedasticity from the species-specific dbh and h growth models using a power function of the tree size independent variables. The final models developed in the present study to predict dbh and total tree height growth included size variables, site factors, and competition variables in their formulation. The developed models fitted the data well and explained between 98 and 99% and of the observed variation of dbh, and between 77 and 98% of the observed variation of total tree height for the studied species and groups of species. The developed models can be used for estimating the individual dbh and h growth for the analyzed species and can be integrated in decision support tools for management planning in these mixed forest ecosystems.
Forests - Tập 11 Số 4 - Trang 429
Phenology-Based Method for Mapping Tropical Evergreen Forests by Integrating of MODIS and Landsat Imagery Updated extent, area, and spatial distribution of tropical evergreen forests from inventory data provides valuable knowledge for research of the carbon cycle, biodiversity, and ecosystem services in tropical regions. However, acquiring these data in mountainous regions requires labor-intensive, often cost-prohibitive field protocols. Here, we report about validated methods to rapidly identify the spatial distribution of tropical forests, and obtain accurate extent estimates using phenology-based procedures that integrate the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat imagery. Firstly, an analysis of temporal profiles of annual time-series MODIS Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and Land Surface Water Index (LSWI) was developed to identify the key phenology phase for extraction of tropical evergreen forests in five typical lands cover types. Secondly, identification signatures of tropical evergreen forests were selected and their related thresholds were calculated based on Landsat NDVI, EVI, and LSWI extracted from ground true samples of different land cover types during the key phenology phase. Finally, a map of tropical evergreen forests was created by a pixel-based thresholding. The developed methods were tested in Xishuangbanna, China, and the results show: (1) Integration of Landsat and MODIS images performs well in extracting evergreen forests in tropical complex mountainous regions. The overall accuracy of the resulting map of the case study was 92%; (2) Annual time series of high-temporal-resolution remote sensing images (MODIS) can effectively be used for identification of the key phenology phase (between Julian Date 20 and 120) to extract tropical evergreen forested areas through analysis of NDVI, EVI, and LSWI of different land cover types; (3) NDVI and LSWI are two effective metrics (NDVI ≥ 0.670 and 0.447 ≥ LSWI ≥ 0.222) to depict evergreen forests from other land cover types during the key phenology phase in tropical complex mountainous regions. This method can make full use of the Landsat and MODIS archives as well as their advantages for tropical evergreen forests geospatial inventories, and is simple and easy to use. This method is suggested for use with other similar regions.
Forests - Tập 8 Số 2 - Trang 34
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