We updated the checklists of extant, native amphibians and reptiles of China based on the previously published checklist of reptiles in 2015, the online checklist of amphibians on the database AmphibiaChina, newly published data as of December 2019, and previously uncollected literature prior to 2015. In total, the amphibian fauna of China consists of 515 species in 62 genera, 13 families, and three orders (Anura: 431 species in 47 genera and nine families; Caudata: 82 species in 14 genera and four families; Gymnophiona: one species in one genus and one family), while the reptilian fauna of China consists of 511 species in 135 genera, 35 families, and three orders (Crocodylia: one species in one genus and one family; Testudines: 34 species in 18 genera and six families; Squamata 466 species in 116 genera and 28 families [Serpentes: 256 species in 73 genera, 18 families; Lacertilia: 211 species in 43 genera and 10 families]). Specifically, for amphibians between 2015 and 2019, one family was recorded from China for the first time, two new genera were described, a genus was resurrected, a genus was recorded from China for the first time, 74 new, valid species were either described or resurrected, 18 recognized species were recorded from China for the first time, and six genera and eight species were considered as junior synonyms. For reptiles between 2015 and 2019, five subfamilies were elevated to the full family status, one new subfamily and a new genus were described, three genera were resurrected, three recognized genera were recorded from China for the first time, 35 new species were described, two species were resurrected from synonyms, six subspecies were elevated to the full species status, 10 recognized species were recorded from China for the first time, four genera and four species were considered as junior synonyms, and distribution records of one genus and four recognized species were removed from China. Furthermore, by reviewing literature before 2015, we make additional changes on the previous reptile checklist, including adding new records of three genera, elevating three subspecies to full species status, adding new records of three recognized species, synonymizing three genera and two species as junior synonyms, and removing the distribution record of a single recognized species from China. Lastly, we revise the Chinese common names of some reptilian groups with recomandations to maintain the stability of the Chinese common names. The number of new species and new national records for amphibians and reptiles between 2015 and 2019 in China accounts for 17.1% and 10.2% of the total number of species in each group, respectively. Because new species are described at considerable speed and given the constant changes in the taxonomy of China’s herpetofuna, it is crucial to update the checklists regularly and discuss the existing taxonomic problems, so that such information reflects the most current state of knowledge and are available for taxonomic researchers and conservation biologists alike.

How large-scale patterns of species diversity emerge is a central yet controversial issue in ecology and biogeography. Despite the long history of studies the mechanisms driving species diversity patterns in space remain poorly known. Using distribution data of all gymnosperm species in China, we assessed the influence of environmental factors on spatial patterns of species diversity in China. Further, we evaluated the proportion of gymnosperms in local floras. We found that species diversity of gymnosperms decreases along a south-north axis. Hengduan Mountains, with the highest species diversity, is a hotspot of gymnosperms. Species diversity patterns differ significantly between the gymnosperm subclasses. In particular, the species diversity pattern of Pinidae is similar to that of all species combined, while the species diversity of Gnetidae is highest in the drylands of northwestern China. In contrast, Cycadidae is restricted to southern China. Environmental heterogeneity and precipitation are the best predictors of species diversity patterns of all gymnosperms combined, followed by temperature anomaly since the Last Glacial Maximum (LGM), elevational range and energy. That different factors predict species diversity patterns of different gymnosperm subclasses, may reflect the differences in their evolutionary history and physiological adaptions. The ratio of gymnosperm to angiosperm species diversity is lower in the warm and humid eastern and southern parts of China, and increases towards the drylands in western and northern parts. Environmental energy and precipitation were good predictors of the ratio of gymnosperms to angiosperms. Specifically, the ratio decreases with increase of energy and decrease of precipitation suggesting that angiosperms may have stronger competitive ability in warm and humid regions while gymnosperms adapt better to dry and cold environments.

Avian ecological studies tend to center on birds and their habitats. According to the literature, studies in avian ecology have shifted from focusing on behavior and habitat selection to focusing on human disturbance, habitat suitability and habitat structure, which has been made possible partially due to remote sensing (RS) technology. Characteristics and applications of RS data are varied. Here, we assessed various RS methods, considering the current state of avian ecology. Light remote sensing is most commonly used. Infrared trigger cameras and video complement field work to monitor brooding, defensive and other behaviors, while the infrared images contain massive amounts of data. Multi-spectral images are used most frequently for mapping habitat and can directly track species when captured at a high spatial resolution. Hyperspectral data has great potential in classifying objects with similar spectral characteristics. LiDAR data mainly contributes to studies of habitat structure. Researchers have used Radar to monitor flying birds over extended periods of time, where the microwave images with multi-polarization may promote the precision of mapping complex habitats. In practice, we recognize that data scale may affect study results and that some RS inversion model parameters lack ecological significance. Multi-source data could enhance mapping accuracy and provide context for the intersection of spatial and temporal resolutions of images. In the future, RS technology development should pay more attention to provide specific spectral information, more convenient interpretation methods, and more rational multi-source data combinaions, for a better use of them.

Since rapid human population growth, overconsumption of natural resources by human activities and climate change, loss and extinction of species is increasing, and biodiversity become an important global issue. Traditional ground-based biodiversity researches focus on the species or community, which can not provide necessary information for biodiversity conservation and assessment at a large scale. Since the advantages in spatial coverage and time series, remote sensing is very useful in large-scale biodiversity monitoring, mapping and assessment. According to the height of the platform, remote sensing platforms can be classified into satellite remote sensing, airborne remote sensing and near-surface remote sensing, which can obtain biodiversity information at different spatial scales. The purpose of this study is to review the recent advances of application of different remote sensing platforms for biodiversity research. We focus on the following aspects, such as observation methods, research scale, and analyze advantages and limitations of different remote sensing platforms. Finally, we summary the future application of remote sensing in biodiversity research. From the literature statistics result, we found that satellite platform were used more frequently in biodiversity research than other remote sensing platform. Due to the high flight cost, the biodiversity researches used airborne remote sensing was fewer than the researches used satellite. Near-surface remote sensing includes the UAV platform and the ground-based platform, which is an emerging remote sensing platform and hotspot in remote sensing of biodiversity. Compared to satellite and airborne remote sensing platforms, the near-surface remote sensing platform can directly observe the individuals and can directly obtain information from species or population. Although there are some limitations in these three platforms, we believe that remote sensing technology can better serve biodiversity conservation and assessment from different temporal and spatial scales with the development of remote sensing platforms and the improvement of sensors.

The diversity and abundance of below-ground microorganisms and animals play an important role in shaping above-ground biodiversity and helps maintain ecosystem function. Yet, we have a limited understanding of belowground biodiversity, e.g. its spatial/temporal patterns, driving factors and responses to global change and human activities. This knowledge gap is particularly acute for the Tibetan alpine grassland that is sensitive to climate change and occupies 60% of the area of the Tibetan Plateau. Here, we first review recent studies that reported the drivers of patterns in five major soil organism groups, including fungi, bacteria, archaea, nematodes and arthropods on Tibetan alpine grassland. We then focus on the responses of soil biodiversity to climate change and human activities. Finally, we highlight some open questions for future research of soil diversity on the Tibetan alpine grassland. Specifically, we recommend that future studies examine (1) The mechanisms underlying distribution patterns of belowground biodiversity; (2) Links between aboveground and belowground biodiversity; (3) Effects of belowground biodiversity on the health and functioning of ecosystems; (4) Manipulative experiments of belowground biodiversity.

The application of UAV technology brings new opportunities and revolutions to the monitoring and research on biodiversity in protected area. However, we find that no monitoring technology solutions combining UAV and ground approaches have been formed yet, due to the lack of concerns on protected objects. Considering to better perform various monitoring technology strengths and to effectively support management and monitoring in protected area, we review study cases on UAV and ground investigation domestic and overseas firstly, and then compare the demands from conservation, management and monitoring of all kinds protected area in China. In general, the ecosystems, species, site relics and landscape are regarded as protected objects in all kinds of protected area. Meanwhile, conservation, recovering, study, education, recreation, and sustainable development become the management goals. Based on the demands mentioned above, we present an integrated technology solution which composed of four categories and 14 subjects for UAV and ground to monitor biodiversity coherently. This solution includes image recognition and classification, data inversion and pattern analysis, digital modeling and surface measuring, patrolling and inspection. In addition, monitoring time and frequency, index, integration approach, data postprocessing can be acquired in the solution. Furthermore, monitoring subjects were chosen to apply and test in the Three Parallel Rivers World Heritage, such as plant identification, vegetation growth, landscape pattern, surface measuring, and law enforcement. While achieving good results on the solution verification, we hope that this monitoring solution will do significant help to improve the protected area biodiversity conservation and management level, also be part of technological storage in assessment and supervision.

Human activities has increasingly threatened the biodiversity of the world. Biodiversity science is a discipline that depends on scale, and research questions are often affected by the ecological process of multi-temporal scales. The traditional survey methods of biodiversity are often limited by human and material resources. It is therefore urgent to integrate different data sources in the biodiversity sciences. The remote sensing technique has developed from optical remote sensing to the multi-source remote sensing including different platforms combined with various sensors, and further to integrate the hyperspectral and hyper spatial resolution and light detection and ranging (LiDAR). The large coverage, the accessibility to remote areas, and the long-term repeatability of the remote sensing technique provide new and better solutions for studying ecological and scientific issues at different temporal and spatial scales. In this paper, we review the opportunity and challenges in the application of remote sensing in biodiversity sciences and conservation practices. Specifically, we focus on the applications of remote sensing in the issues related to the population dynamics, species interaction and community diversity, functional traits and functional diversity and biodiversity management. We suggest that the satellite and airborne remotes that employed multi-band or hyperspectral, high spatial resolution and LiDAR provide biodiversity information from different scopes, and will play essential roles in the investigation of biodiversity in large-scale and remote areas. In the near future, species discrimination technique based on spectral characteristics and structure detection based on LiDAR will improve our understanding of the biodiversity sciences and management. We suggest to strengthen the communication between remote-sensing scientists and biodiversity researchers to promote the application of remote sensing technologies in biodiversity research and at different temporal and spatial scales.

The term “wild animal” has different meanings not only in Chinese but in many languages all over the world. Here, we identify uses of the term “wild animal” through examining interpretations and applications in local, national, and international laws and language used in human controlled animal reproduction. We put forward a two-dimensional conceptual framework of “wild animals” that distinguishes 12 continuous states of animals from “wild” to “domesticated”. Animal groups that have not been artificially selected in the medium- and long-term were considered wild animals. Domesticated animals, whether or not they live under human control, such as domestic cats, dogs, poultry, livestock, and animal models or stray or feral were not considered “wild animals”. However, the management of some categories, such as tamed animals of wild species or exotic/invasive animals needs to base on ecological safety, species conservation, and legislative objectives. The Law on the Protection of Wildlife of the People’s Republic of China (LPW) shall apply to endangered animal species threatened by humans, whether they were found in the wild or under human control condition. For the management of other states of “wild animals”, existing laws should be strictly implemented, and new laws should be enacted with genetic resources, zoonotic diseases, animal welfare, and ecological safety in mind. We additionally make specific recommendations for the definition of “wild animal” for use under the LPW.

Most members of the Bunyavirales could infect humans and animals and thus pose great potential threat to public health. According to the 10^th Report on Virus Taxonomy released by the International Committee on Taxonomy of Viruses (ICTV, 2017), the taxonomy of Bunyaviruses has been updated. Based on the information of this report, we highlight the taxonomy of the new Bunyavirales and summarize the historical changes of ICTV classification of this virus, including classification, designation, typical species, genomic structures, encoding protein, major vectors and hosts, geographic distribution, and specific viral properties. In addition, based on the viral genome-encoded RdRp gene sequence, a phylogenetic analysis is performed for the all nine families and 13 genera as well as the representative species of Bunyavirales.

In 1859, Charles Darwin put forward the concept of the tree of life (TOL), a metaphor for charting relationships between organisms in space and time in his The Origin of Species. The TOL is a cornerstone in evolutionary theory and makes sense of all biology. Decades of research in plant molecular systematics has led to substantial progress in understanding many aspects of the plant TOL. Here, we summarized five major aspects of reconstructing the plant TOL, which are being studied at the present day and will continue to be goals moving forward. These include: (1) constructing genus- and species-level phylogenies for plant groups; (2) resolving deep-time and/or rapidly divergent phylogenetic relationships using genomic approaches; (3) updating classification systems by combining morphological and molecular data; (4) integrating fossil taxa into phylogenies derived from extant taxa; and (5) building big trees using supermatrix methods. We then outlined the current state of plant molecular systematics and highlight existing problems in the field, specifically in regard to China. Finally, we propose the corresponding guidelines and policy suggestions for the continued study of China’s reconstruction of the plant TOL.

Ecological niche modeling seeks to infer the relationship between occurrences of a species and environmental covariates and has been widely applied in biodiversity studies. Light detection and ranging (LiDAR) is a new active remote sensing technology that is being increasingly used for acquisition of 3D structural information of forests. However, its applications in ecological niche modeling are rarely studied. In this study, we wanted investigate the effectiveness of LiDAR in modeling the spatial distribution of fisher (Martes pennanti) in the southern Sierra Nevada Mountains, California. We used artificial neural networks, generalized linear model, generalized additive model, discriminative maximum entropy, and multivariate adaptive regression splines to implement the presence and background learning (PBL) method separately. We then combined all the models based on weighted average to create an ensemble model. The generative maximum entropy model was also considered for comparison. Area under the receiver operating characteristic curve (AUC) and F_pb based on presence and background data were used to evaluate the continuous and binary outputs, respectively. Our results show that the values of AUC and F_pb were 0.779 and 1.077, respectively, when only climate variables (such as temperature and precipitation) were included in the models, whereas the values of AUC and F_pb were 0.800 and 1.106, respectively, when both climate and LiDAR-derived variables (such as canopy bulk density, height to live canopy base, leaf area index, digital elevation model, slope, etc.) were included in the models. Therefore, we conclude that LiDAR-derived variables are helpful in modeling the spatial distribution of fisher, and has good potential in ecological niche modeling.

The mechanism of formation and evolution of phenotypic diversity is one of the key problems in biodiversity science because phenotype diversity is not only a marker of species diversity, but carries the designs adjusted to environments. Plant leaves exhibit a great deal of morphological variation. Such variation is attributed largely to changes of leaf marginal architecture. Leaf marginal shapes can be described as entire, serrate, lobed (varying in depth and patterns) and dissected (also referred to as compound leaf). The molecular mechanism controlling the development of leaf marginal shape has been intensively studied in Arabidopsis thaliana, Cardamine hirsuta, Solanum lycopersicum, and some other plants. Many important regulatory factors such as transcription factors, small RNAs and plant hormones have been found involved in the development of leaf serration or dissection. Among those factors, the transcription factor NAM/CUC, miR164 and auxin in the auxin efflux module play a central role through a feedback loop, and this regulatory module appears to be conserved across the eudicots; the transcription factors TCPs, SPLs and some other miRNAs also take part in the auxin efflux pathway. Transcription factors of the KNOX family play roles in the development of leaf lobes as well although most of the researches about KNOX genes have focused on their regulation of the morphogenesis of compound leaves. In addition, studies in Arabidopsis, Cardamine and other taxa of the Brassicaceae have shown that the gene RCO promotes the development of leaf dissection by repressing growth at the flanks of protrusions generated by CUC-auxin patterning. The present paper reviews the recent progress and integrate the major results of researches about the molecular mechanisms that underlie leaf serration or dissection. We hope this may provide reference for unraveling the morphogenetic origin of the spectacular diversity of leaf marginal shapes.

Wildlife population is low and most of them are very sensitive to human disturbing, which makes traditional survey difficult. As known, infra-red camera technology has many advantages in wildlife study. However, with its wide application and increased data amount, researchers are facing some problems concerning infra-red camera monitoring and later data processing and analyzing. This paper describes in details three key problems on infra-red camera data management and use, such as lacking standardization, integration and normalization. The present paper also lists and analyzes eight aspects about photo data mining, based on researches carried out in the Qinling Mountains, Wolong Nature Reserve, etc. It involves individual recognition, temporal/spatial activity pattern, information-extracting of occasional species, behavior and reproduction, disease situation and interference by humans. If all this information can be used effectively, we hope to provide scientific support at some extent on wildlife and biodiversity conservation and management in future.

Mangrove forests are ecological communities growing in the intertidal zone of tropical and subtropical coastlines. Due to their high productivity, mangrove forests are essential to persistence of biodiversity along coastlines and have high carbon sequestration ability. In this article we review aspects of monitoring mangrove forests using recent multi-source remote sensing data. First, we reviewed studies on monitoring mangrove dynamics. By integrating object-based and pixel-based classification, high spatial resolution images were used to classify different mangrove species. Landsat images were then used to monitor the dynamics of mangrove forests and analyze factors driving them. Second, we reviewed studies measuring structural parameters of mangroves. Specifically, unmanned aerial vehicle multispectral data and ground-based Light Detection and Ranging (LiDAR) data were used to compute leaf area index of mangrove forests. Finally, we reviewed studies examining physiology and biochemistry parameters. These studies explored adaption of chlorophyll content in mangrove forests under different submergence conditions, whether the invasive species Spartina alterniflora affects the light use efficiency and changed the response of photochemical reflectance index (PRI) to LUE. Our review provides a useful reference for selecting appropriate analytical methods when extracting information of mangroves from remotely sensed data. We emphasize the effectiveness of remote sensing in studying mangrove spatiotemporal patterns, extracting structural parameters, monitoring biochemical parameters, thus aiding efforts to conserve mangrove ecosystems.

Developing effective policies for biodiversity conservation and restoration policies requires spatially and temporally explicit data on distribution of species and habitats. Remote sensing provides an effective technical tool to meet this requirement. In recent years, the rapid development of integrated multi-platform, multi-scale, multi-mode remote sensing technology the implementation of integrated remote sensing observations across space-air-field provides novel opportunities for biodiversity monitoring. In this paper, we review the main methods of remote sensing that aids biodiversity monitoring and assess existing remote sensing observation experiments. We found that current methods of biodiversity monitoring using remotely-sensed data lacked the support of space-air-field integrated observations and the existing space-air-field integrated observations did not include biodiversity parameters. The Wanglang integrated observation and experiment station for mountain ecological remote sensing illustrates the potential to integrate experimental station-based and space-air-field integrated observations for biodiversity monitoring. Our review highlights that integrating direct observations with remote sensing can provide spatio-temporally explicit information on species and habitats and improve the informed monitoring of biodiversity.

Seed rain patterns are a crucial influence on plant regeneration. Although it is very challenging to understand the dynamics of seed rain, long-term monitoring of seeds can provide useful insights. In this study, we monitored seed rain patterns of forests dominated by Parashorea chinensis in Xishuangbanna, Southwest China for nine years. We recorded 8,993,224 seeds belonging to 226 species, between May 2008 and April 2017. We categorized seeds of 77 species as large, 61 species as medium, 72 species as small, 13 species as tiny, 1 species as infinitesimally grainy seed and 2 species as filamentous. More than 70% of all seeds belong to the top 10 dominant species. Seeds of all types showed pronounced inter-annual variation for both seed number and species number. At least one mast seeding was observed for each of the seed type during nine years.

Patterns in the distribution of species richness have always been a central theme in macroecology. The karst landforms in Southwest China (mainly Guangxi, Yunnan and Guizhou provinces) are among the largest of the global biodiversity hotspots. In this study, we sought to understand spatial patterns of amphibian species richness and its relationship with environmental factors. We compiled a large dataset of 18,246 records of point location data for 219 amphibian species occurring in China. We retrieved this data from published literature, Herpetology museums of Chengdu Institute of Biology and Kunming Institute of Zoology, Chinese Academy of Sciences, Guangxi Zhuang Autonomous Region Museum of Nature and the Central South University of Forestry and Technology, and published sources. We used this data to generate the potential distributions of each species using ecological niche modeling. We combined the potential distributions maps of all species into a composite map to describe species richness patterns on the grid cell of 10 km × 10 km, and then conducted multivariate regression and model selection. Our results showed that 12 species were distributed only in karst area, accounting for 5.48% of the total species pool, 104 species were found in non-karst area (47.49% of total species), and 103 species were found in both karst area and non-karst area (47.03% of total species). Based on the raw data of museum collections data and MaxEnt species distribution modeling, we found that amphibian species richness in the study area decreased at higher latitudes. Karst landforms and non-karst landforms differed in their distribution patterns of amphibian species richness (χ² = 36.47, P < 0.0001), but the model was a poor fit to the data (McFadden’s Rho square = 0.0037). The most significant environmental predictors of species richness were mean annual rainfall (R² = 0.232, P < 0.001) and precipitation of driest Month (R² = 0.221, P < 0.001). The results based on model selection showed that underlying mechanisms related to landforms and different ecological hypotheses might simultaneously explain patterns of amphibian species richness in the study area. Future research should examine other biological factors such as interference, predation, and competition to understand the mechanisms controlling patterns of amphibian species richness.

A key soil invertebrate, earthworms significantly affect soil quality and the broader ecosystem. In this paper, we review the ecological characteristics of earthworm species Amynthas corticis, A. morrisi, A. robustus, A. aspergillum, Pontoscolex corethrurus and Eisenia fetida in southern China and their effects on soil pH, enzyme activity, metal accumulation and availability, the formation of soil pores and micro-aggregates, and the decomposition of organic waste. In sum: (1) Earthworms in southern China can survive in soil with a wide range of pH (3.8-7.9), and their survival rates are related to soil type, organic matter content, soil contamination level and earthworm species; (2) Enzyme activity in earthworm guts, castings and drilosphere indicate the appetite of different earthworm species, the process of soil nutrient cycling and soil microbial characteristics, respectively; (3) Earthworms are capable of accumulating different metals and altering their availability, but this capability varies depending on earthworm species, element and soil type; (4) Earthworm activity and cast production can change soil structure, increase the amount of soil pores and affect the size, amount and distribution of soil aggregates. Moreover, we highlight the potential application of earthworms toward resolving the acidification of red soil, nutrient imbalance in tea gardens, soil metal contamination, the compaction and destruction of soil during expressway construction, and the utilization of agricultural and urban organic waste. At present, due to insufficient investigations into the physiological characteristics of earthworms and a lack of Amynthas sp. breeding technology, earthworm applications are scarcely conducted at medium and large scales. Hence the promotion of earthworm technology is especially limited in southern China. It will be necessary to explore the potential of earthworms in soil restoration further and to analyze the mechanisms earthworms employ during soil construction and management in order to develop technologies to perform the functions currently occupied by earthworms.

Biological invasion is a major threat to multiple ecosystems across the globe, causing severe damages to ecological integrity, loss of biodiversity, economic and social development and even human health. With the rapid development in aquaculture, shipping and aquarium and ornamental trades in the past several decades, China has become one of the countries most influenced by invasive species. Studies have clearly shown that the development and application of robust early monitoring and warning is one of the most effective ways to prevent and possibly control invasive species in aquatic ecosystems. Compared to terrestrial ecosystems, there remain several technical difficulties for developing early monitoring and warning in aquatic habitats. The technical challenges are mainly due to several features of aquatic biological communities such as high biodiversity and complex structure, a large number of microscopic species, extremely low population density and lack of available taxonomic keys for species identification. With the rapid development of high-throughput sequencing techniques, environmental DNA (eDNA)-metabarcoding has become the top priority method for developing the early monitoring and warning programs in aquatic ecosystems. In this review, we aim to synthesize the research progress on eDNA-metabarcoding and its application to early monitoring and warning of invasive species in aquatic ecosystems. In addition, we briefly discuss the technological advantages of eDNA-metabarcoding for the early monitoring and warning programs. Finally, we propose research perspectives for solutions to technical issues for false positive and false negative errors in the eDNA-metabarcoding process.

Gaur (Bos gaurus) are found in the Yunnan Province and Zangnan in southern Tibet in China. We conducted two field surveys in Xishuangbanna, Pu’er and Mt. Gaoligongshan in Yunnan Province, from February to March and November to December in 2016. We collected 47 valid occurrence locations of gaur by combining survey data and records from literature. Our analysis suggests that there are 180-210 gaurs in the Yunnan Province which face a serious survival crisis. No gaur signs were found in Mt. Gaoligongshan. Next, we used MaxEnt models to predict the potentially suitable habitats for gaur. We grouped 14 habitat predictor variables into five classes—terrain, land cover type, human footprint index, the distance to water and road, as well as climatic factors, and determined the contribution of each habitat factor to habitat suitability for gaur. The accuracy of our prediction models was accessed by the area under the curve (AUC) values for a receiver operating characteristic (ROC) curve. The validation showed that the results had high average AUC value of 0.994. The simulated potential habitat was divided into four classes—the most suitable habitat, moderately suitable habitat, low suitability habitat, and unsuitable habitat. The most suitable habitats for gaur are mainly located in southern Yunnan and Zangnan and spanned 4,987 km² and 13,995 km² respectively. Habitats with moderate suitability (total area = 32,778 km²) were located in the marginal areas of the most suitable habitats and in the Mt. Gongligongshan area. The most suitable habitats were mixed with habitat patches of moderate and low suitability for gaur in the southern parts of Xishuangbanna. In contrast, the central and northern parts of the study area were classified entirely as low suitable habitats and unsuitable habitats. The results of a Jackknife test indicated that temperature seasonality and isothermality had the strongest influence on habitat suitability for gaur, whereas terrain factor and precipitation had little effect. Temperature difference, land cover type and human footprint index were the main variables that explained patterns of gaur distribution. The results of land cover classification (using remote sensing) showed that rubber plantations have fragmented the suitable habitat and reduced landscape connectivity for gaur. We recommend that the relevant management authorities should protect natural forests, control the development of rubber plantations and other agricultural development in habitats suitable for gaur, and improve landscape connectivity to restore gaur populations in the landscape.

Whether a maximum entropy (MaxEnt) model constructed at one spatial scale is representative of species distributions at other scales is an important issue in the application and development of these models. Using distribution data for Manglietia insignis, we used the minimum convex polygon (MCP) method to model species distribution for three spatial scales—Three Parallel Rivers, Yunnan Province and China—with a 20 km buffer outside the distribution region. We built the MaxEnt model for Three Parallel Rivers, Yunnan Province and China using 19, 67, and 88 presence-only records respectively and combined these with data on environmental factors at the point locations. We estimated the prediction accuracy of the MaxEnt model using receiver operating characteristic (ROC) curve and omission rate (OR). Next, we used ArcGIS to analyze distribution trends for habitat suitability and potential hotspots. We identified the location of geometric centroid of potentially suitable areas using Zonal and used the Jackknife method to test the dominant environmental factors affecting the distribution of M. insignis. We found that the area under ROC curve (AUC value) for Three Parallel Rivers, Yunnan Province and China were 0.936, 0.887, and 0.930 respectively and OR values were 0.18, 0.15, and 0.20, indicating that MaxEnt model for all three spatial scales could successfully predict the distribution of M. insignis. Distribution trends of potential habitat suitability and habitat hotspots were consistent between different scales and were concentrated in the river basins of Dulong River, Nujiang River and Lancang River, with no significant zonal transfer for the location of geometric centroid. Different environmental factors affected the geographical distribution of M. insignis at the three spatial scales, suggesting scale dependence in the distribution patterns of M. insignis. In summary, this study indicates that MaxEnt model of M. insignis performs stably and successfully for different spatial scales. In addition, the consistency of results across spatial scales became more obvious for hotspots, indicating that hotspot analysis greatly reduced the effect of spatial scale for the MaxEnt model. Thus, we propose integrating MaxEnt model and hotspot analysis to simulate the geographical distributions of species.

Phylogeography seeks to identify the historical ecological and evolutionary processes underlying modern-day phylogenetic relationships across a spatial gradient. Owing to the characteristics of uniparental inheritance, low mutation rates and haploid, chloroplast DNA (cpDNA) markers record the events occurring in historical long-term evolutionary processes to different extents, and hence aid in understanding the mechanisms for phylogeographic variation. Here we discuss how these characteristics affect cpDNA marker selection, how they increase or reduce population genetic differentiation, how they lengthen or shorten the average gene coalescent times, how they promote or impede gene introgression among species and how the process of lineage sorting functions from polyphyly to paraphyly to monophyly. We reviewed the theoretical bases of these mechanisms, as well as the progress made in empirical studies regarding the theories of phylogeographic variation. Because of the heterogeneity of DNA sites in mutation rate, selection strength and interactions with genetic drift effects, one study to examine the genome-wide pattern of phylogeography will be necessary in the future. This must include the analysis of differential gene introgression and gene flow among sites, as well as the distribution of the differential phases of lineage sorting along the chloroplast genome.

Algae are important flora in mangrove ecosystems. Algae can be divided into three ecological groups, namely phytoplankton, benthic microalgae, and macroalgae in mangrove ecosystems, which play important roles in organic carbon production and nutrient cycle. Despite the importance of algae for ecosystem function, studies of mangrove ecosystems have focused on higher plants and animals, with few studies of algae. Due to their abundance in mangrove ecosystems, studies of algae can broaden our understanding about the structure and function of mangrove ecosystems. In this review, we first briefly introduce algal groups and their ecological importance in mangrove ecosystems. Then, we emphasize species composition and geographical distribution of phytoplankton, benthic diatoms and macroalgae, and their importance in key ecological processes such as primary production, water pollution, element cycle, and carbon stock dynamics in mangrove ecosystem. The researches have showed that the species number of phytoplankton and benthic diatoms in mangroves varied from dozens to hundreds, and diatoms are dominant both in species composition and abundance, which are important primary producer, animal food, and pollution indicator. Macroalgae are mainly composed of red algae, green algae, brown algae and blue-green algae. Green algae are dominant in species richness whereas red algae are abundant in quantity. Algae contribute significantly to the carbon pool by sequestering and cycling carbon. We propose that future studies should focus on algal diversity and its role in ecological processes in mangrove ecosystems. Furthermore, we suggest that studies of algae should be part of comprehensive investigations on long-term ecosystem dynamics. The influence of continental runoff and tidal patterns on algal diversity and blue carbon dynamics in mangrove areas also deserve more attention, on account of being directly related to nutrient replenishment and dynamics. Since algal diversity in mangrove sediment is influenced by physico-chemical and biological condition of the system, it could be used as an indicator of climate change and effects of anthropogenic activity on mangrove ecosystems.

Millipedes (Diplopoda) are a highly diverse group of soil invertebrates and play vital roles in terrestrial ecosystems. Millipedes contribute to the cycling of carbon and nutrients through their feeding activities and gut processes that help decompose litter. However, the functions of millipedes have been poorly researched compared to other groups of soil animals such as earthworms. Here, we briefly summarize the ecological functions of millipedes: Millipedes can fragment, consume and transform litter to accelerate its decomposition. Millipedes prefer large amounts of semi-decomposed litter and the efficiency of millipedes in assimilating litter can vary with litter source, temperature and microbial biomass in the litter. Millipedes can regulate the cycling of soil carbon and other key nutrients through feeding and excretion activities. Nitrogen enters to the soil when litter is fragmented by millipedes, but there are different views on how millipedes affect the soil carbon cycle. Millipede faeces decompose more rapidly than the pre-ingested litter. Such a transformation of litters to faeces would accelerate carbon cycling. However, other studies have suggested a relatively low decomposition rate of millipede faeces when compared with un-ingested litter, which could contribute to soil carbon sequestration and stabilization. In addition, the survival of millipedes affects soil phosphorus cycle. They can increase the content of available phosphorus in soil. Millipedes interact with other soil animals such as earthworms and also can regulate the abundances of soil microorganisms. Our review indicates that further studies are required to better understand and document the role of millipedes in ecosystem functioning.

The research achievements of the Chinese Forest Biodiversity Monitoring Network (CForBio), a comprehensive research platform for biodiversity science, are highly influential for promoting biodiversity-related research in China. A detailed assessment of CForBio’s publication growth, core research areas, and ability to foster cooperation will provide important information for the long-term development of CForBio and related ecological monitoring research. In order to understand CForBio’s impact on science, this study made a comprehensive bibliometric analysis of research papers produced by CForBio-associated scientists, published between 2007 and 2017, using the China National Knowledge Infrastructure and Web of Science databases. Since 2007, the number of papers published by CForBio has grown rapidly, from 3 in 2007 to 55 in 2017 , as has the number of papers published in journals included in the Science Citation Index (from 1 in 2007 to 34 in 2017). The top three most prolific authors are Guangze Jin (70 papers), Keping Ma (68 papers), and Zhanqing Hao (68 papers). The most active research institutions are the Institute of Botany, Chinese Academy of Sciences (CAS) (104 papers), the Institute of Applied Ecology of CAS (67 papers), and the South China Botanical Garden of CAS (59 papers). CForBio-associated institutions and scholars cooperate infrequently, and cross-unit collaborative research needs improvement. The core research topics of CForBio focus on patterns of tree spatial distribution, plant functional traits, tree density dependence, and community phylogeny; these topics provide a theoretical basis for elucidating the mechanisms of forest community assembly among the different climatic zones in China. In the future, CForBio should strengthen cooperation among institutions—both domestic and abroad, establish data sharing pathways, further emphasize new technologies and techniques such as near-surface remote sensing and multi-source data fusion, and continue to fund research on the multi-scale and multi-dimensional analysis of biodiversity patterns, plant-soil feedback mechanisms, and tree canopy and root structure function.

Accurate coordinate position is a prerequisite for combining drone-assisted remotely sensed data and ground survey data. However, in the practice of surveying forests, many factors prevent accurate measurement of coordinate position and inaccurate coordinates may lead to incorrect conclusions. Therefore, researchers must pay attention to factors effecting accuracy of position. In this study, we compared location error of ground control points (GCPs), model error of photogrammetric point cloud (estimated by Photoscan software) and reprojection error of camera exposure position. First, we found that real time kinematic (RTK) global navigation satellite system (GNSS) cannot locate position in tropical forest with high accuracy. The root mean square error (RMSE) of GCPs in canopy gaps were 0.167 ± 0.158 m and 0.297 ± 0.170 m in the horizontal and vertical axes respectively. In comparison, RMSE of GCPs within forests were 0.392 ± 0.368 m and 0.657 ± 0.412 m respectively for horizontal and vertical axes. Second, the number and measurement accuracy of GCPs influenced model error of photogrammetric point cloud. Third, reprojection error of camera exposure position (18.434 ± 5.252 m and 34.042 ± 6.920 m in horizontal and vertical axes respectively) was much greater than location error of GCPs when the drone acquired position with a single-station GPS system. Fourth, standard deviation of difference between estimated digital terrain model (DTM_estimated) and measured digital terrain model (DTM_measured) was positively correlated with mean canopy height (r = 0.713, P < 0.05). DTM_estimated was better estimated at 20 ha scale than at 1 ha scale. Based on these results, we suggest that uniform distribution and sufficient numbers of GCPs can improve drone-assisted mapping accuracy. Lightweight-drone-based photogrammetry has an advantage in requiring fewer equipment and enabling creation of accurate DSM (digital surface model), but remains incapable of estimating ground elevation. Researchers should consider these factors related to accuracy before using drones for surveys.

Mount Badagongshan (BDGS) National Nature Reserve is located in the northern margin of Wuling Mountain, which harbor large areas of evergreen and deciduous broadleaved mixed forests. These forests have high species diversity and possess a complex community structure. In 2010-2011, a 25 ha (500 m × 500 m) forest dynamic plot was established in this reserve according to the standards of the Center for Tropical Forest Science (CTFS). Within this plot, all woody plants with DBH ≥ 1 cm were mapped and identified to species level. Based on these data, we analyzed community composition and spatial structure of the vegetation community. We found 186,575 individuals in the plot, belonging to 53 families, 114 genera and 232 species. There were 38 species that had > 1,000 individuals each and these species comprised 87% of total abundance. The most abundant species was Litsea elongata. There were 103 rare species, i.e. with ≤ 25 individuals, which accounted for 44% of all woody species but only made up 0.4% of the total abundance. Across all individuals in the plot, the average DBH was 5.41 cm. Individuals with DBH ≤ 5 cm accounted for 68.4% of the overall abundance and the 7,474 individuals with DBH ≥ 20 cm accounted for only 4% of the overall abundance. The frequency distribution of DBH appeared to have a reverse “J” shape, suggesting that the community was maintaining successful regeneration and normal growth patterns. The number of species increased linearly with increasing area. When the sampling area was increased to 10 ha, we recorded 201 species, which represented more than 90% species of the entire plot. These 1-ha samples had average abundance of 7,261.8 ± 974.8 (SD), average species richness of 128.2 ± 8.2 (SD), average of 3.56 ± 0.11 (SD) for Shannon-Wiener index, and 1.69 ± 0.06 (SD) for Pielou evenness index. There was no significant relationship between abundance and the diversity indices, suggesting that instead of the sampling effect, some other mechanisms affected the species diversity pattern in BDGS plot.

Many studies have examined the patterns and mechanisms underlying the structure of mid-subtropical forest community, but spatial variation in species diversity has rarely been investigated. We examined spatial variations in α- and β-diversity among and between 24 subplots of 1-ha each within the 24 ha forest dynamics plot in Gutianshan National Nature Reserve. We found that (1) the top two dominant species were the same for almost all the subplots, but the third dominants differed greatly; (2) α-diversity varied greatly among subplots: total number of individuals showed the largest differences, followed by species richness, Shannon-Wiener index, and Pielou evenness index; (3) species richness showed no correlation with total abundance and Pielou evenness index but was positively correlated with Shannon-Wiener index, which was positively correlated with Pielou evenness; (4) there was high species turnover between neighboring subplots, but these patterns were not consistent with the spatial variation in species richness. Our results highlight the importance of spatial scales for assessing community structure and mechanisms of community assembly. Since forest communities are influenced by ecological processes at multiple scales, large-scale plots may be better than small-scale plots to explore multiple mechanisms of community assembly.

It is difficult to carry out highly effective management in the natural protected areas of China due to complicated land ownership and lack of scientific research, especially in the National Park pilots. This paper proposes a conservation easement policy based on focused conservation needs by integrating an innovative adaptive management method and an ecological compensation plan, using the Qianjiangyuan National Park pilot as an example. First, the major conservation needs of the ecosystem elements are refined by determining the spatial scope of the easement implementation according to the land type. Secondly, the relationship between conservation need and the livelihood of local residents is clarified to form the classified conservation list. The evaluation method for easement is designed in three dimensions: improvement of monitoring indicators of the ecosystem, compliance with positive and negative actions and community capacity cultivation. Finally, the easement contract is formed by outlining the clear rights and responsibilities of the easement donor and donee. A scientific and flexible plan for ecological compensation is also carried out. This method can effectively solve the problem of land resource fragmentation at both on the ecosystem and landscape scale, which is normally caused by inconsistent ownership, as well as the conflict between community development and ecological conservation. Finally, this plan can be applied to the natural protected areas in southern China where the collective forest coverage is relatively high.

Understanding spatial distribution and habitat overlap of sympatric species is essential to developing integrated policies for conserving species and regional biodiversity. This study combined data from the 4th National Survey of giant panda (Ailuropoda melanoleuca) and long-term field survey. We used the Maximum entropy model (MaxEnt) to predict the distributions of two sympatric bears, the giant panda and Asiatic black bear (Ursus thibetanus) in Liangshan Mountains. Based on spatial distribution of two species, we measured habitat fragmentation and spatial overlap of habitat use, and assessed environmental requirements of both species. Our results indicated that: (1) both species had similar distributions of suitable habitats, both were mainly distributed on the ridges of Liangshan Mountains. The suitable habitat area of giant panda and black bear were 1,383.84 km² and 2,411.49 km², respectively. (2) The habitats of both species were fragmented and separated into many patches. However, habitat connectivity for the black bear was better than for giant panda. (3) Niche overlap indices, calculated by ENMTools, showed that two species have high overlap in their ecological niche (D = 0.654 and I = 0.901). The overlapping habitat comprised 958.29 km² of the study area, which contained 69.25% of giant panda habitat and 39.74% of black bear habitat. (4) We used permutation techniques to estimate the importance of environmental variables in the MaxEnt model. Distance to residents and altitude were the most influential predictors for both species. Vegetation types and mean temperature of coldest quarter were the third and fourth important predictor for giant panda, while annual maximum enhanced vegetation index (EVI) and distance to roads was important for the black bear. To protect these two species more effectively, a series of measures have to be adopted, such as strengthening vegetation restoration, controlling disturbance, and enhancing connectivity between habitat patches. We recommend that a systematic, multi-species conservation plan should be developed.

To find out the main plant community types of uninhabited islands in the nearshore Xiamen, in mid-to-late October 2017, we recorded 360 vascular plant species, including 78 trees, 109 small trees or shrubs, 23 vines and 150 herbs. We also found 49 invasive alien species, 10 of which have been identified as the most serious invasive. Compositional analysis showed that vegetation in these 12 uninhabited islands were of tropical and sub-tropical types. Consistent with the subtropical geography of these islands, vegetation mainly consisted of pan-tropical species and its variants. Generally, the islands had similar species composition. Herbaceous plants dominated the flora of these islands. Power and logarithm functions best described the species-area relationships of island vascular plants. Area had the largest effect on species richness of these islands followed by other spatial parameters such as the ratio of shoreline length, elevation, and perimeter area. Habitat diversity and island edge affected similarity of vascular plant species among different islands. Except for Wuyu Isle, we did not find evidence for small island effects in these surveys.

Identifying spatial patterns and assembly rules in communities is a central study topic in ecology. With the unprecedented rate at which biodiversity is decreasing, it is necessary to recognize the spatial patterns and assembly rules in communities in order to understand why biodiversity is being lost and to be able to protect it. However, previous studies have focused more on plant communities in above-ground terrestrial ecosystems, neglecting below-ground ecosystems, especially soil faunal communities. Indeed, soil faunal biodiversity is a crucial component of global biodiversity because soil faunal communities assist in the maintenance of important ecosystem structures and functions. Therefore, one important aim of identifying spatial patterns and assembly rules in soil faunal communities is to clarify mechanisms of maintaining soil faunal biodiversity at multiple scales, so as to promote these processes, which also maintain ecosystem structures and functions. Soil faunal communities usually form complicated spatial patterns at multiple spatial scales. Here, we propose spatial autocorrelation characteristics, and then show how the complicated spatial patterns are demonstrated by patches and gaps of soil faunal communities at multiple scales. These spatial patterns are mainly controlled by processes of biotic interactions, environmental filtering and random dispersal. Consequently, we discuss the impacts of these processes on soil faunal communities. Finally, we suggest that these three processes are essential to evaluate and construct a theoretical framework for soil faunal communities and should continue to be studied in the future. Because interest in spatial patterns and assembly rules of soil faunal communities is relatively new in China, we expect this review will promote the development of related research areas.

Tea (Camellia sinensis) is an important crop and is sensitive to climate change. Evaluating the impact of climate change on tea distribution and production is not only important for the global economy but also the livelihoods of farmers in many countries. Here we compiled data from 858 global occurrences of C. sinensis and six climatic variables, and used species distribution model (SDM) to predict the current potential distribution and possible range shifts in response to climate change in 2070 under Representative Concentration Pathway 2.6 and 8.5 (RCP2.6 and RCP8.5). The results indicate that the current potential distribution of tea is mainly confined to Asia, Africa and South America, and distribution is limited by mean temperature of coldest quarter (MTCQ) and precipitation of warmest quarter (PWQ). Under future climate change scenarios, by 2070 suitable habitat for tea could significantly shrink at low latitudes, but expand at middle latitudes, leading to a northward shift of the distribution. However, the influence of future climate change on tea distribution differed across regions. The climatically suitable areas in Argentina, Myanmar, and Vietnam are projected to decrease by 57.8%-95.8%, whereas those in China and Japan are projected to increase by 2.7%-31.5%. Moreover, 68% of the new suitable habitat for tea cultivation under future climate change are predicted to lie within areas of natural vegetation cover. Therefore, the establishment of new tea gardens in these areas may lead to conflicts between tea cultivation and conservation of natural vegetation and biodiversity.

Poyang Lake, the largest freshwater lake in China, is one of two lakes that maintain a natural hydrological link with the Yangtze River. The lake system is critical for biodiversity conservation globally, harboring large number of migratory waterbirds. During the dry season, Poyang Lake fragments in to numerous sub-lakes, and different sub-lakes have different hydrological control and management mode. However, the recent hydrological alternation, presumably caused by the operation of Three Gorge Dam (TGD), is threatening the ecological integrity of the lake system, especially as a wintering ground for waterbirds. A robust investigation of the effects of TGD on vegetation cover and productivity at this critical biodiversity hotspot is therefore timely, and could incorporate recent advances in remote sensing and ecological modelling. In this study, using MODIS EVI (enhanced vegetation index) time series, we investigated the spatiotemporal patterns of growth in the lake for the period of 2000-2014, which includes periods before (2000-2006) and after (2007-2014) TGD was commissioned. Firstly, we extracted 107 16-day MODIS EVI time series (February 2000 to April 2015) for 10 randomly placed transects across the lake. We then applied the adaptive Savitzky-Golay smoothing algorithm to the EVI time series, and extracted four key growth metrics, namely, the starting date of growth season, growth season length, seasonal peak EVI, and productivity index. We found significant associations between the hydrological alternation and changes in vegetation seasonality. First, we found that the vegetation growth characteristics of wetlands under different hydrological control modes showed significant differences. In particular, the vegetation located in the freely connected sub-lakes had a later start of growing season, shorter growing season, lower peak EVI value, and lower primary productivity compared to sub-lakes of other modes. Second, due to the hydrological alteration, growth characteristics of sites in freely connected sub-lakes displayed two cycles per year and differed significantly before and after 2006. The advance of the autumn growing season led to excessive accumulation of biomass, which reduced the palatability of the food of migratory geese. However, this difference does not exist in the sites located in the local controlled sub-lake. Third, free connected and local controlled sub-lakes are both important for the protection of migratory birds of Poyang Lake. It is necessary to protect areas harboring both types of sub-lakes to provide a wider food source for wintering migratory birds. Local hydrology control can, to some extent, slow down the impact of much larger scale hydrological alteration on wetland vegetation growth.

Endangered species conservation is an important part of biodiversity conservation, heavily helped by threatened species assessment guides. The assessment of threatened level has gradually evolved from being qualitative to quantitative with qualitative supplement. This paper reviews the research progress of the domestic threatened plant species quantitative assessment system, and introduces the mature IUCN Red List Assessment System, CITES Assessment System, and the National Natural Conservation Association Assessment System. Through this, we propose future development requirements of quantitative assessment criteria for threatened species should have the following characteristics: (1) a clear, unified, and reasonable definition of category setting, (2) quantitative, objective, and non-redundant criteria for endangered categories, (3) adaptation to different geographical range while simultaneously expressing threatened category over different ranges, (4) evaluation indicators contain the dynamic information of the species which can quantitatively analyze the change of the species through time. In addition, the domestic quantitative assessment system for threatened species should form a standardized outline with increased publicity to combine theoretical research with specific conservation actions. Lastly, China should adopt the widely-used endangered rating systems to assess species threatened level and integrate domestic biodiversity conservation work into the global scale.

Species classification and identification is the basis of biodiversity monitoring, and is critical to deal with almost all ecological questions. In this paper, we aim to understand the current status and existing problems in plant species classification and identification using multi-source remote sensing data. We summarized the studies in this field since the year 2000, and found that most of these studies focus on temperate or boreal forests in Europe and North America, or African savanna. Airborne hyperspectral data is the most widely used remote sensing data source, and the LiDAR, as a supplementary data, significantly improves the classification accuracy through the information of single tree segmentation and three-dimensional vertical structure. Support vector machine and random forest are the most widely used non-parametric classification algorithms with an average classification accuracy of 80%. With the development of computer technology and machine learning, artificial neural network has developed rapidly in species identification. Based on the literature-based analysis, we propose that the current research in this field is still facing some challenges, including the complexity of classification objects, the effective integration of multi-source remote sensing data, the integration of plant phenology and texture characteristics, and the improvement in plant classification algorithm. The accuracy of plant classification and identification could be greatly improved by using the high-frequency data collection over time, the integration of hyperspectral and LiDAR data, the use of specific spectral information such as short-wave infrared imagery, and the development of novel deep learning techniques.