CForBio: a network monitoring Chinese forest biodiversity

Drought tolerance and species abundance mediate dry season negative density dependence in a tropical forest

Conspecific negative density dependence (CNDD) is thought to be a key process in maintaining plant diversity. However, the strength of CNDD is highly variable in space and time as well as among species, and correlates of this variation that might help to understand and explain it remain largely unquantified. Using Bayesian hierarchical models, we took advantage of 10-year seedling monitoring data that were collected annually in every dry and rainy season in a seasonal tropical forest. We quantified the interspecific variation in the strength of CNDD and its temporal variation. We also examined potential correlates of this interspecific and temporal variation, including species functional traits (such as drought-tolerant traits, defense-related traits, and recourse acquisition traits) and species abundances. In the dry season, we found a negative relationship between the density of neighboring conspecific seedlings on seedling survival, while in the rainy season, there was a negative relationship between the density of neighboring conspecific adults on seedling survival. In addition, we found that interspecific variation in CNDD was related to drought-tolerant traits in the dry season but not in the rainy season. Across years, we found that drought-intolerant species suffer less CNDD during the dry seasons that have higher rainfall, whereas drought-tolerant species suffer less CNDD when the dry season has lower rainfall. We also found that rare species suffered stronger CNDD in the dry season. Overall, our study highlights that CNDD is highly variable among species and through time, necessitating a deeper appreciation of the environmental and functional contexts of CNDD and their interactions.

Bacterial genome size and gene functional diversity negatively correlate with taxonomic diversity along a pH gradient

Bacterial gene repertoires reflect adaptive strategies, contribute to ecosystem functioning and are limited by genome size. However, gene functional diversity does not necessarily correlate with taxonomic diversity because average genome size may vary by community. Here, we analyse gene functional diversity (by shotgun metagenomics) and taxonomic diversity (by 16S rRNA gene amplicon sequencing) to investigate soil bacterial communities along a natural pH gradient in 12 tropical, subtropical, and temperate forests. We find that bacterial average genome size and gene functional diversity decrease, whereas taxonomic diversity increases, as soil pH rises from acid to neutral; as a result, bacterial taxonomic and functional diversity are negatively correlated. The gene repertoire of acid-adapted oligotrophs is enriched in functions of signal transduction, cell motility, secretion system, and degradation of complex compounds, while that of neutral pH-adapted copiotrophs is enriched in functions of energy metabolism and membrane transport. Our results indicate that a mismatch between taxonomic and functional diversity can arise when environmental factors (such as pH) select for adaptive strategies that affect genome size distributions.

Patterns of compound-leaf form and deciduous-leaf habit across forests in China: Their association and key climatic factors

Leaf form (compound vs. simple) and habit (evergreen vs. deciduous) are key functional traits of trees to adapt to various climates and are vital in determining plant response to climate change. However, their association and climatic determinants remain uncertain, especially in East Asian forests in the largest monsoon region on earth. To fill these knowledge gaps, we compiled a dataset comprising 42 intact forests and over 2200 angiosperm tree species across China (spanning 30 latitudes and 47 longitudes). The geographical and climatic patterns of leaf form and habit were analyzed. The association between compound leaf and deciduousness was tested for tropical, subtropical and temperate climatic zones. We found that both the percentage of compound leaf (CT%) and deciduous tree species (DT%) increased with latitude and decreased with mean annual precipitation (MAP). For all forests, DT% was negatively related to mean annual temperature (MAT), whereas CT% was not. Nevertheless, both DT% and CT% increased with increasing MAT in the tropics, possibly owing to the high vapor pressure deficits (VPD) and canopy water deficits associated with high temperatures. A positive linear relationship between CT% and DT% was found across all forests and within different climatic zones except for temperate, and the intercept of the regression line was significantly higher in the tropics than in the subtropics. Overall, as supported by principal component analysis, deciduousness was negatively associated with both temperature and precipitation, while CT negatively with precipitation only across zones and positively with temperature in the tropics. Different relationships in different climatic zones suggest potentially different selective forces. Our findings provide novel insights into the linkage between leaf form and habit, as well as how climate shapes the landscape of broadleaf forests, which has important implications regarding the response of forest composition to climate change.

Tropical-temperate comparisons in insect seed predation vary between study levels and years

The biotic interaction hypothesis, which states the species interaction becomes stronger in the tropics, is deeply rooted in classic ecological literature and widely accepted to contribute to the latitudinal gradients of biodiversity. Tests in latitudinal insect-plant interaction have emphasized leaf-eating insects on a single or a few plant species rather than within an entire community and mixed accumulating evidence, leaving the biotic interaction hypothesis disputed. We aimed to test the hypothesis by quantifying insect seed predation in a pair of tropical and temperate forest communities with similar elevations. We applied a consistent study design to sample predispersal seeds with systematically set seed traps in 2019-2020 and examined internally feeding insects. The intensity of seed predation was measured and further applied to tropical versus temperate comparison at two levels (cross-species and community-wide). Our results showed every latitudinal pattern associated with different study levels and years, that is, negative (greater granivory in the tropics in community-wide comparison in 2020), positive (less granivory in the tropics in community-wide and cross-species comparison in 2019), and missing (similar level of granivory in the tropics in cross-species comparisons in 2020). The cross-species level analyses ignore differences among species in seed production and weaken or even lose the latitudinal trend detected by community-wide comparisons. The between-year discrepancy in tropical-temperate comparisons relates to the highly variable annual seed composition in the temperate forest due to mast seeding of dominant species. Our study highlights that long-term community-level researches across biomes are essential to assess the latitudinal biotic interaction hypothesis.

The Shift from Energy to Water Limitation in Local Canopy Height from Temperate to Tropical Forests in China

Canopy height greatly affects the biomass stock, carbon dynamics, and maintenance of biodiversity in forests. Previous research reported that the maximum forest canopy height (Hmax) at global and regional scales could be explained by variations in water or energy availability, that is, the water- or energy-related hypothesis. However, fundamental gaps remain in our understanding of how different drivers (i.e., water and energy) contribute to the Hmax at the local scale. In this study, we selected eight dynamic forest plots (20–30 ha) across a latitudinal gradient (from 21.6° N to 48.1° N) in China and measured the canopy structure using airborne light detection and ranging (LiDAR) data. Based on the LiDAR point cloud data, we extracted the maximum tree height (Hmax) in a 20 × 20 m quadrat as a proxy for canopy height, and the topographic wetness index (TWI) and digital terrain model-derived insolation (DTMI) were calculated as proxies for water and energy conditions. We used a linear mixed model and spatial simultaneous autoregressive error model to quantify how TWI and DTMI contributed to variations in Hmax at the local scale. We found that the positive effect of TWI was stronger in subtropical and tropical forests, highlighting that water was the main factor that drives the canopy height pattern in these regions. In contrast, although the effects of DTMI can be both positive and negative, its relative contribution was higher in temperate forest plots than in other forest types, supporting the idea that energy input is more critical for Hmax in temperate forests. Overall, our study revealed the directional change from energy to water limitation from temperate to subtropical and tropical forests. Our findings can offer important insights into forest management, especially under global climate change in the Anthropocene.

Applying a Portable Backpack Lidar to Measure and Locate Trees in a Nature Forest Plot: Accuracy and Error Analyses

Accurate tree positioning and measurement of structural parameters are the basis of forest inventory and mapping, which are important for forest biomass calculation and community dynamics analyses. Portable backpack lidar that integrates the simultaneous localization and mapping (SLAM) technique with a global navigation satellite system receiver has greater flexibility for tree inventory than terrestrial laser scanning, but it has never been used to measure and map forest structure in a large area (>101 hectares) with high tree density. In the present study, we used the LiBackpack DG50 backpack lidar system to obtain the point cloud data of a 10 ha plot of subtropical evergreen broadleaved forest, and applied these data to quantify errors and related factors in the diameter at breast height (DBH) measurements and positioning for more than 1900 individual trees. We found an average error of 4.19 cm in the DBH measurements obtained by lidar, compared with manual field measurements. The incompleteness of the tree stem point clouds was the main factor that caused the DBH measurement errors, and the field DBH measurements and density of the point clouds also had significant impacts. The average tree positioning error was 4.64 m, and it was significantly affected by the distance and route length from the measured trees to the data acquisition start position, whereas it was affected little by the habitat complexity and characteristics of tree stems. The tree positioning measurement error led to increases in the mean value and variability of paired-tree distance error as the sample plot scale increased. We corrected the errors based on the estimates of predictive models. After correction, the DBH measurement error decreased by 31.3%, the tree positioning error decreased by 44.3%, and the paired-tree distance error decreased by 56.3%. As the sample plot scale increased, the accumulated paired-tree distance error stabilized gradually.

Research on the Temporal and Spatial Distributions of Standing Wood Carbon Storage Based on Remote Sensing Images and Local Models

Background and Objectives: It is important to understand the temporal and spatial distributions of standing wood carbon storage in forests to maintain ecological balance and forest dynamics. Such information can provide technical and data support for promoting ecological construction, formulating different afforestation policies, and implementing forest management strategies. Long-term series of Landsat 5 (Thematic Mapper, TM) and Landsat 8 (Operational Land Imager, OLI) remote sensing images and digital elevation models (DEM), as well as multiphase survey data, provide new opportunities for research on the temporal and spatial distributions of standing wood carbon storage in forests. Methods: The extracted remote sensing factors, terrain factors, and forest stand factors were analyzed with stepwise regression in relation to standing wood carbon storage to identify significant influential factors, build a global ordinary least squares (OLS) model and a linear mixed model (LMM), and construct a local geographically weighted regression (GWR), multiscale geographically weighted regression model (MGWR), temporally weighted regression (TWR), and geographically and temporally weighted regression (GTWR). Model evaluation indicators were used to calculate residual Moran’s I values, and the optimal model was selected to explore the spatiotemporal dynamics of standing wood carbon storage in the Liangshui Nature Reserve. Results: Remote sensing factors, topographic factors (Slope), and stand factors (Age and DBH) were significantly correlated with standing wood carbon storage, and the constructed global models exhibited fitting effects inferior to those of the established local models. LMM is also used as a global model to add random effects on the basis of OLS, and R2 is increased to 0.52 compared with OLS. The local models based on geographically weighted regression, namely, GWR, MGWR, TWR, and GTWR, all have good performance. Compared with OLS, the R2 is increased to 0.572, 0.589, 0.643, and 0.734, and the fitting effect of GTWR is the best. GTWR can overcome spatial autocorrelation and temporal autocorrelation problems, with a higher R2 (0.734) and a more ideal model residual than other models. This study develops a model for carbon storage (CS) considering various influential factors in the Liangshui area and provides a possible solution for the estimation of long-term carbon storage distribution.

Simulation and Prediction of Fungal Community Evolution Based on RBF Neural Network

Simulation and prediction of the scale change of fungal community. First, using the experimental data of a variety of fungal decomposition activities, a mathematical model of the decomposition rate and the relationship between the bacterial species was established, thereby revealing the internal mechanism of fungal decomposition activity in a complex environment. Second, based on the linear regression method and the principle of biodiversity, a model of fungal decomposition rate was constructed, and it was concluded that the interaction between mycelial elongation and moisture resistance could increase the fungal decomposition rate. Third, the differential equations are used to quantify the competitive relationship between different bacterial species, divide the boundaries of superior and inferior species, and simulate the long-term and short-term evolution trends of the community under the same initial environment. And an empirical analysis is made by taking the sudden change of the atmosphere affecting the evolution of the colony as an example. Finally, starting from summer, combining soil temperature, humidity, and fungal species data in five different environments such as arid and semiarid, a three-dimensional model and RBF neural network are introduced to predict community evolution. The study concluded that under given conditions, different strains are in short-term competition, and in the long-term, mutually beneficial symbiosis. Biodiversity is important for the biological regulation of nature.

Assembly processes lead to divergent soil fungal communities within and among 12 forest ecosystems along a latitudinal gradient

Latitudinal gradients provide opportunities to better understand soil fungal community assembly and its relationship with vegetation, climate, soil and ecosystem function. Understanding the mechanisms underlying community assembly is essential for predicting compositional responses to changing environments. We quantified the relative importance of stochastic and deterministic processes in structuring soil fungal communities using patterns of community dissimilarity observed within and between 12 natural forests and related these to environmental variation within and among sites. The results revealed that whole fungal communities and communities of arbuscular and ectomycorrhizal fungi consistently exhibited divergent patterns but with less divergence for ectomycorrhizal fungi at most sites. Within those forests, no clear relationships were observed between the degree of divergence within fungal and plant communities. When comparing communities at larger spatial scales, among the 12 forests, we observed distinct separation in all three fungal groups among tropical, subtropical and temperate climatic zones. Soil fungal β-diversity patterns between forests were also greater when comparing forests exhibiting high environmental heterogeneity. Taken together, although large-scale community turnover could be attributed to specific environmental drivers, the differences among fungal communities in soils within forests was high even at local scales.

Species packing and the latitudinal gradient in beta-diversity

The decline in species richness at higher latitudes is among the most fundamental patterns in ecology. Whether changes in species composition across space (beta-diversity) contribute to this gradient of overall species richness (gamma-diversity) remains hotly debated. Previous studies that failed to resolve the issue suffered from a well-known tendency for small samples in areas with high gamma-diversity to have inflated measures of beta-diversity. Here, we provide a novel analytical test, using beta-diversity metrics that correct the gamma-diversity and sampling biases, to compare beta-diversity and species packing across a latitudinal gradient in tree species richness of 21 large forest plots along a large environmental gradient in East Asia. We demonstrate that after accounting for topography and correcting the gamma-diversity bias, tropical forests still have higher beta-diversity than temperate analogues. This suggests that beta-diversity contributes to the latitudinal species richness gradient as a component of gamma-diversity. Moreover, both niche specialization and niche marginality (a measure of niche spacing along an environmental gradient) also increase towards the equator, after controlling for the effect of topographical heterogeneity. This supports the joint importance of tighter species packing and larger niche space in tropical forests while also demonstrating the importance of local processes in controlling beta-diversity.

Biodiversity conservation in China: A review of recent studies and practices

Biodiversity conservation plays an important role in the sustainable development of human society. China had made significant progress in biodiversity conservation studies and practices. This paper reviews major achievements in China in the past decades, especially those since 2010. In terms of the science behind biodiversity conservation, Chinese scholars have made significant contributions to priority research subjects, including mechanisms for maintaining biological communities and the relationship between biodiversity and ecosystem functioning. Simultaneously, biodiversity conservation and management systems specific to China have been basically established. The Chinese Government and researchers have undertaken a number of investigations, scientific studies, and monitoring, and have established relevant databases. With efforts taken to protect and restore biodiversity and ecosystems, the concept of biodiversity has gradually become popular in China. This review is an attempt to share with the world the learning from China's progress towards becoming an ecological civilization and highlights that the efforts towards biodiversity conservation need to be organically integrated with sustainable development goals.

Internet of Things to network smart devices for ecosystem monitoring

Smart, real-time, low-cost, and distributed ecosystem monitoring is essential for understanding and managing rapidly changing ecosystems. However, new techniques in the big data era have rarely been introduced into operational ecosystem monitoring, particularly for fragile ecosystems in remote areas. We introduce the Internet of Things (IoT) techniques to establish a prototype ecosystem monitoring system by developing innovative smart devices and using IoT technologies for ecosystem monitoring in isolated environments. The developed smart devices include four categories: large-scale and nonintrusive instruments to measure evapotranspiration and soil moisture, in situ observing systems for CO₂ and δ¹³C associated with soil respiration, portable and distributed devices for monitoring vegetation variables, and Bi-CMOS cameras and pressure trigger sensors for terrestrial vertebrate monitoring. These new devices outperform conventional devices and are connected to each other via wireless communication networks. The breakthroughs in the ecosystem monitoring IoT include new data loggers and long-distance wireless sensor network technology that supports the rapid transmission of data from devices to wireless networks. The applicability of this ecosystem monitoring IoT is verified in three fragile ecosystems, including a karst rocky desertification area, the National Park for Amur Tigers, and the oasis-desert ecotone in China. By integrating these devices and technologies with an ecosystem monitoring information system, a seamless data acquisition, transmission, processing, and application IoT is created. The establishment of this ecosystem monitoring IoT will serve as a new paradigm for ecosystem monitoring and therefore provide a platform for ecosystem management and decision making in the era of big data.

Climate and food diversity as drivers of mammal diversity in Inner Mongolia

Traditionally, geographical distribution of biodiversity is assumed to be codetermined by multiple factors, for example, temperature, precipitation, environmental heterogeneity, and biotic interactions. However, few studies have simultaneously compared the relative roles of these factors in shaping the mammal diversity patterns for different feeding groups, that is, herbivores, insectivores, and carnivores. In this study, we assessed the relations between mammal diversity and current climate (mean annual temperature and precipitation), altitudinal range as well as mammal's food diversity in Inner Mongolia. Our results showed that the species richness for the three feeding guilds of mammals consistently increased with their food diversity, that is, species richness of plants, insects, and rodents. Mammal diversity also significantly decreased with mean annual temperature and precipitation. Random Forest models indicated that climate and food diversity were always included in the combinations of variables most associated with mammal diversity. Our findings suggest that while climate is an important predictor of large scale distribution of mammal diversity, biotic interactions, that is, food diversity, could also play important roles.

Bird species richness is associated with phylogenetic relatedness, plant species richness, and altitudinal range in Inner Mongolia

Bird species richness is mediated by local, regional, and historical factors, for example, competition, environmental heterogeneity, contemporary, and historical climate. Here, we related bird species richness with phylogenetic relatedness of bird assemblages, plant species richness, topography, contemporary climate, and glacial‐interglacial climate change to investigate the relative importance of these factors. This study was conducted in Inner Mongolia, an arid and semiarid region with diverse vegetation types and strong species richness gradients. The following associated variables were included as follows: phylogenetic relatedness of bird assemblages (Net Relatedness Index, NRI), plant species richness, altitudinal range, contemporary climate (mean annual temperature and precipitation, MAT and MAP), and contemporary‐Last Glacial Maximum (LGM) change in climate (change in MAT and change in MAP). Ordinary least squares linear, simultaneous autoregressive linear, and Random Forest models were used to assess the associations between these variables and bird species richness across this region. We found that bird species richness was correlated negatively with NRI and positively with plant species richness and altitudinal range, with no significant correlations with contemporary climate and glacial–interglacial climate change. The six best combinations of variables ranked by Random Forest models consistently included NRI, plant species richness, and contemporary‐LGM change in MAT. Our results suggest important roles of local ecological factors in shaping the distribution of bird species richness across this semiarid region. Our findings highlight the potential importance of these local ecological factors, for example, environmental heterogeneity, habitat filtering, and biotic interactions, in biodiversity maintenance.