Wild pollinator bees play an important role in ecosystem function and food security. In recent years, natural forests have been lost, while afforestation programs are primarily monoculture plantation, whether commercial or restorative. The net effect for bees has been fragmentation and sometime wholesale loss of habitats. For instance, diversity of wild bees in pure forest, Camellia oleifera and rubber (Hevea brasiliensis) plantation was found to be unexpectedly low. The rampant use of neonicotinoid pesticides and herbicide is known to negatively impact development and behavior of bees. Urbanization has dramatically impacted bee communities, with significant changes in species richness between suburban and central business areas. These are likely tied to the effect of effluent, exhaust gas and dust on foraging, growth and development. Climate change from greenhouse gas emissions can disrupt the mutualistic relationship between pollinating bees and plants via rapid phenological shifts. The above environmental changes occurring in China are likely cause wide declines in diversity and decreases in populations. Although China has rich natural heritage for bees, there is a lack of long term monitoring programs for species of pollinator bees and a dearth of data on distributions of bee species. As a result, the drivers of bee community composition and population decline are poorly understood. We emphasize the need to prioritize surveys of pollinating bees, continue ongoing monitoring programs and build wider research networks for the study of wild pollinator bees. These steps will ensure that sufficient data can accumulate for developing a prediction and risk assessment framework to help manage the declines in pollinating bee populations and mitigate the attendant economic and non-economic impacts.
Understanding the relationship between plant diversity and productivity can provide essential information for forest management. We surveyed plant communities in Pinus massoniana dominated plantations from four regions of Guangxi. Using correlation analysis, automatic linear modeling and variance partitioning, we assessed the effect of species diversity, functional diversity, and functional dominance on productivity. We found that productivity was extremely positively correlated with species richness, Shannon index, functional richness and functional evenness (P < 0.01). Species evenness, RaoQ, functional dispersion, functional group richness and aspect were also positively correlated with productivity (P < 0.05), while forest age was negatively correlated with productivity (P < 0.01). Four functional diversity parameters positively correlated with four species-diversity indices. No evidence of negative density-dependence was found. In the best variance partitioning model, functional diversity parameters, functional dominance and forest age explained 56%, 43% and 33% of variance in productivity respectively; and the overlap between functional diversity parameters and functional dominance was up to 27%. Functional richness and functional evenness were major contributors of complementary effects while community weighted mean (CWM) of growth form contributed to selection effects. Plots identified as dominantly shrub had higher productivity than plots identified as dominantly herbs or trees, suggesting that subordinates and transients may have important effects on ecosystem functions. The best-fit subset model built by automatic linear modeling included forest age, growth form CWM, functional richness, functional evenness and functional group richness (FGR) indescending order. We recommend that to maintain diversity and forest function, protection of understory plant species should be strengthened. Further, to enhance productivity and biodiversity we recommend planting functionally important species through compensatory photosynthesis and growth competition in understorey layers.
The study of the relationship between biodiversity and ecosystem functioning (BEF) is a hot topic in the field of terrestrial ecosystem ecology, and is of great significance for the efficient use and management of ecosystems. Furthermore, it plays an important role in the restoration of degraded ecosystems and biodiversity conservation. Alpine grassland is the main ecosystem type found in the Qinghai-Tibet Plateau. In recent years, progress has been made on species diversity and ecosystem functioning and their mutual relationship in alpine grasslands. This paper analyzes existing problems in the research of grassland biodiversity and ecosystem functioning in terms of the study of underlying ecological processes and the impacts on ecosystem multi-functionality under global change. The effects of different grassland types, grassland degradation, grazing disturbance, simulated climate change, mowing, fertilization, enclosure, and replanting on the relationship between biodiversity and ecosystem functioning in alpine grasslands are also thoroughly reviewed in this paper. Moreover, deficiencies and future research directions of alpine grassland BEF are identified: carrying on the BEF research of alpine grasslands based on the functional diversity of species, comprehensively considering the effects of abiotic factors such as resource supply levels, disturbance intensity and scale, and environmental fluctuation on the relationship between species diversity and ecosystem function, and paying attention to the effect of scale and element coupling on BEF research of alpine grasslands under global climate change. Finally, based on research progress and conclusions of BEF in alpine grasslands, we put forward suggestions to improve the utilization rate of alpine grassland resources and biodiversity conservation, including strengthening grazing management, protecting biodiversity, improving governance of degraded grasslands, maintaining biodiversity function, strengthening innovation and protection concepts and enhancing ecosystem functioning that has been seriously weakened by climate change and human disturbance.
Nature reserves are a cornerstone of global conservation strategies. However, the effectiveness of the reserve in conserving ecosystem function such as carbon storage is poorly understood. The Shennongjia National Nature Reserve is a conservation icon and has taken exceptional efforts to protect forests. It provides a unique case to address this question. Here, we quantified the carbon storage from aboveground carbon, belowground carbon, litter, coarse woody debris, and soil organic carbon inside and outside the Shennongjia National Nature Reserve between 1990 and 2010, based on inventory data and digitized historical land cover maps. The result showed that the woodland covered 92.76% of the reserve, most of which was coniferous forest (51.85%), deciduous broad-leaved forest (35.11%), and evergreen broad-leaved forest (4.47%). Between 1990 and 2010, the area of the woodland has increased 0.11%, while the area of shrubland and cropland has declined 8.85% and 6.06%, respectively. The Shennongjia National Natural Reserve has accumulated 24.24 Tg carbon (22.57-26.62 Tg C) until 2010, of which 90.68% was contributed by soil organic carbon and aboveground carbon. A total of 95% of the carbon storage in Shennongjia National Nature Reserve are contributed by evergreen broad-leaved forest, deciduous broad-leaved forest and coniferous forest. Between 1990 and 2010, the aboveground carbon pool and soil organic carbon pool has increased 14.50 kt C (11.81-18.31 kt C) and 6.84 kt C, respectively. The carbon density inside the reserve is 22.37 t C/ha higher than that outside the reserve. Our results indicated that the Shennongjia National Nature Reserve is efficiently conserving forest carbon.
World Natural Heritage site is recognized globally as the pinnacle of natural protected areas that are the cornerstones of biodiversity conservation. The World Natural Heritage of Shennongjia represents one of the worldwide biodiversity hotspots. But, until now, it has not been clear how outstanding the universal value of Shennongjia is worldwide, and this study presents one of the most compelling challenges to conservation efforts. Here, we compiled literature and conducted additional field surveys in the Shennongjia region to illustrate the outstanding universal value of Shennongjia World Natural Heritage Site using World Heritage criteria (ix) and (x), following the operational guidelines for the implementation of the World Heritage Convention. Results show that the heritage of Shennongjia offers an outstanding example of the ongoing ecological processes occurring in the development of intact subtropical mixed broad-leaved evergreen and deciduous forests in the Northern Hemisphere. This region presents a typical example of mountain altitudinal biological zones in the Oriental Deciduous Forest Biogeographical Province. Shennongjia is also a vital origin location for global temperate flora, and harbors the highest concentration of global temperate genera of trees. Moreover, the heritage of Shennongjia displays exceptional biodiversity and is a key habitat for numerous relic, rare, endangered and endemic species. The richness of deciduous woody species in Shennongjia is the highest in the world. Our study provides great insight into protecting, monitoring and managing the outstanding world heritage in the Northern Hemisphere.
High-quality biodiversity data are the scientific basis for understanding the origin and maintenance of biodiversity and dealing with its extinction risk. Currently, we identify at least seven knowledge shortfalls or gaps in biodiversity science, including the lack of knowledge on species descriptions, species geographic distributions, species abundance and population dynamics, evolutional history, functional traits, interactions between species and the abiotic environment, and biotic interactions. The arrival of the current era of big data offers a potential solution to address these shortfalls. Big data mining and its applications have recently become the frontier of biodiversity science and macroecology. It is a challenge for ecologists to utilize and effectively analyze the ever-growing quantity of biodiversity data. In this paper, I review several biodiversity-related studies over global, continental, and regional scales, and demonstrate how big data approaches are used to address biodiversity questions. These examples include forest cover changes, conservation ecology, biodiversity and ecosystem functioning, and the effect of climate change on biodiversity. Furthermore, I summarize the current challenges facing biodiversity data collection, data processing and data analysis, and discuss potential applications of big data approaches in the fields of biodiversity science and macroecology.
As the most direct and active ecological interface of the interaction between forest and its environment, the forest canopy, known as the earth’s “eighth continent”, contains the greatest forest biological diversity, and plays an important role in the formation and maintenance of biodiversity as well as the processes and functions of the ecosystem. However, the forest canopy is highly sensitive to global climate change and human disturbance. In the wake of increasing human activities and global climate change, the forest ecosystem, especially the forest canopy, is facing a serious threat. Therefore, protection of forest canopy biodiversity and sustainable utilization are increasingly important issues in modern ecology research under the scenarios of climate change, and have gained more and more attention in the fields of forest ecology, climatology, and environmental science. Accordingly, in 2015, the Chinese Forest Canopy Biodiversity Monitoring Network was created within the framework of Sino BON. This network includes biodiversity monitoring plots those were or will be equipped with forest canopy cranes. According to international standards, the network will unify monitoring parameters of forest canopy biodiversity using monitoring standards and norms, and conduct long-term monitoring of plant diversity (including epiphytic seed plants and epispore plants), fauna diversity, microbial diversity and their dynamic changes, through large scale zonal forest canopies. Combined with monitoring of the microclimate, we will build four dynamic databases (including a forest canopy microclimate database, canopy plant, canopy arthropod, and canopy microbial). The network is expected to discern the change patterns of forest canopy biodiversity of typical forest ecosystems in China, and to reveal how they influence the functioning of forest ecosystems and respond to global change.
The application of phylogenetic relationships helps us to understand species composition and species distribution patterns, which provide a scientific basis for the effective protection and sustainable use of biological diversity. Phylogenetic diversity (PDfaith), based on branch lengths of the phylogenetic tree, is the most basic measurement index. Many indices are derived from PDfaith, which makes difficult to choose the most appropriate parameters. The most effective and feasible way is to select suitable indices based on specific research questions, and some examples have been presented in plant phylofloristics and biodiversity conservation. DNA sequences have rapidly accumulated particularly through the global DNA barcoding project, which provides a standardized mass data, and can be used to reconstruct mega-phylogeny. But studies conducted around the phylogenetic diversity require more information, specifically data on species distribution, environmental factors, and climatic data. In addition, some fundamental questions need to be verified, such as the relationship between phylogenetic diversity and ecosystem functions.
Under global climate change, biodiversity is decreasing rapidly due to deforestation and habitat fragmentation, which has serious consequences for ecosystem functioning. In recent years, the relationship between biodiversity and ecosystem functioning has been a core research area in ecology. Previous researchers have paid great attention to the relationship between biodiversity and individual ecosystem functioning, and seldom consider multiple functions (multifunctionlity), especially in forest ecosystems. Here, based on survey data from 94 plots of Pinus yunnanensis in a natural secondary forest, we selected variables related to ecosystem functioning: woody plant biomass, soil organic carbon, plant nitrogen, plant phosphorus, soil total nitrogen, soil hydrolyzable nitrogen, soil total phosphorus, and soil available phosphorus. We used an averaging approach, single threshold approach, and multiple threshold approach to evaluate the effects of species richness on ecosystem multifunctionality and impacting factors. Results showed that the relationship between species richness and ecosystem multifunctionality was stronger than that of individual ecosystem functioning. Species richness had a significant positive effect on multifunctionality within thresholds ranging from 3% to 88%. When using a moderate threshold (54%), species richness had the strongest positive effect, and the percentage of maximum possible species richness was 53.53%. Path analysis of a structural equation model showed that species richness had the strongest (positive) effect on multifunctionality in the Pinus yunnanensis natural secondary forest. Mean annual temperature, mean annual precipitation, and soil pH had insignificant effects on multifunctionality, but indirect effects via influences on species richness. Species richness may be of primary importance when considering ecosystem multifunctionality. Increasing species numbers may not always lead to the optimal state of all functions. Increasing species numbers had the strongest effects on multifunctionality, but only once multifunctionality reached moderate levels.
Increasing attention has recently been focused on the linkages between plant functional traits and ecosystem functioning. A comprehensive understanding of these linkages can facilitate to address the ecological consequences of plant species loss induced by human activities and climate change, and provide theoretical support for ecological restoration and ecosystem management. In recent twenty years, the evidence of strong correlations between plant functional traits and changes in ecosystem processes is growing. More importantly, ecosystem functioning can be predicted more precisely, using plant functional trait diversity (i.e., functional diversity) than species diversity. In this paper, we first defined plant functional traits and their important roles in determining ecosystem processes. Then, we review recent advances in the relationships between ecosystem functions and plant functional traits and their diversity. Finally, we propose several important future research directions, including (1) exploration of the relationships between aboveground and belowground plant traits and their roles in determining ecosystem functioning, (2) incorporation of the impacts of consumer and global environmental change into the correlation between plant functional traits and ecosystem functioning, (3) effects of functional diversity on ecosystem multifunctionality, and (4) examination of the functional diversity-ecosystem functioning relationship at different temporal and spatial scales.
The expansion of Phyllostachys edulis into the adjacent secondary evergreen broad-leaved forest (EBF) is obvious and greatly affects its ecological function. Little research has examined its effects on community structure and biodiversity. We comparatively analyzed the characteristics of species composition, community structure and diversity before and after the expansion of P. edulis forest (PEF), P. edulis-broad-leaved mixed forest (PBMF) and EBF along a gradient of P. edulis expansion in the Jinggangshan National Nature Reserve in Jiangxi Province using a space for time substitution method. Results indicated that: (1) The Bray-Curtis similarity index values of the tree layer, shrub layer and herb layer between PEF and EBF were 0.003, 0.046 and 0.030, respectively. (2) The PEF vertical structure showed a “>” type and the abundance percentage was 33.3% in 12-14 m interval, its diameter at breast height (DBH) class structure concentrated distribution in 5-10 cm interval, whose percentage was as high as 90.0%; while the EBF vertical structure showed a “L” type and the abundance percentages was 54.3% in 2-4 m interval, its DBH class distribution range was relatively wide, the average percentage of four larger diameter grades was 10.3%. (3) The Shannon-Wiener index value in the tree layer declined from 2.56 in EBF to 0.06 in PEF, with a reduction of 98%. In the shrub layer, the index value dropped from 2.58 to 2.03, declining 21%. We suggest that the expansion of P. edulis simplified the community composition and structure of the secondary evergreen broad-leaved forest and reduced species diversity, which can cause adverse impacts on forest ecosystem functioning.
Long term series of remotely sensed imagery of net primary production (NPP) data could reflect ecosystem health. In this study, we employed NPP to evaluate the effects of ecological engineering (nature reserve and new ecological engineering in 2004 or 2005 techniques) by the sampling area comparison method in the Chang Tang and Sanjiangyuan national nature reserves on the Tibetan Plateau. The results showed that: (1) among the 10 pairs of sampling areas, annual NPP of 9 pairs tended to increase between 1982 and 2009; (2) the new ecological engineering techniques improved the effectiveness of ecosystem conservation, with NPP in 8 pairs of sampling areas increasing faster than before; and (3) among all alpine grassland types, the new ecological engineering techniques remarkably improved the effectiveness of conserving the meadows.
Soil microbial diversity has not been extensively observed due to technique limitations. With the development of the high-throughput sequencing technique and bioinformatics, much progress has been made in observations of microbial diversity. Currently, international microbiome initiatives have been founded (including the Earth Microbial Project). However, problems in these projects include a lack of dynamic observations, differences in observational methods, and data integration. The soil microbial observation network (SMON) is an important part of the Chinese Biodiversity Monitoring and Research Network (Sino BON). The observational network initially selected field observation sites in forest ecosystems along a temperature and precipitation gradient from south to north, in grassland ecosystems along a precipitation transect from east to west, and in typical wetland and agricultural ecosystems in China. Field ecological observation stations have been established in these selected ecosystems. Key tasks for the SMON are to observe spatial and temporal dynamics of soil microbial communities and functional genes in various ecosystems, including bacteria, archaea, fungi, and lichens. Observational data will be published periodically in the format of database, annals, and illustrated handbooks. Key methods used in the SMON are high- throughput sequencing, metagenomics, and bioinformatics. A soil biota database is currently being constructed to store observational data for public inquiry and analysis. Through the efforts of SMON, we plan to explore the driving mechanisms of spatial and temporal variations of soil microbial communities and their functional genes, and understand the relationships between microbial diversity and ecosystem function, in order to predict microbial dynamics under global environmental change scenarios, and to design strategies to protect soil microbial diversity and properly utilize microbial resources.
The relationship between biodiversity and ecosystem multifunctionality (BEMF) is a hot issue in current ecological studies. The measurement of ecosystem multifunctionality (EMF) is a crucial aspect of BEMF research; however, the metrics of EMF have been inconsistent among previous studies. We reviewed seven approaches of quantifying EMF (single function approach, turnover approach, averaging approach, single threshold approach, multiple thresholds approach, orthologous approach and multivariate model approach) and classified the related studies based on the metrics of EMF used. We illustrated the multiple-threshold approach with published data from our previous work to help researchers better understand the approach. The inconsistent use of EMF metrics made it difficult to compare different studies, which constrains further development of BEMF research. Hence, there is an urgent need to develop a general approach to measuring multifunctionality appropriately.
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