Although trait analyses have become more important in community ecology, trait-environment correlations have rarely been studied along successional gradients. We asked which environmental variables had the strongest impact on intraspecific and interspecific trait variation in the community and which traits were most responsive to the environment. We established a series of plots in a secondary forest in the Chinese subtropics, stratified by successional stages that were defined by the time elapsed since the last logging activities. On a total of 27 plots all woody plants were recorded and a set of individuals of every species was analysed for leaf traits, resulting in a trait matrix of 26 leaf traits for 122 species. A Fourth Corner Analysis revealed that the mean values of many leaf traits were tightly related to the successional gradient. Most shifts in traits followed the leaf economics spectrum with decreasing specific leaf area and leaf nutrient contents with successional time. Beside succession, few additional environmental variables resulted in significant trait relationships, such as soil moisture and soil C and N content as well as topographical variables. Not all traits were related to the leaf economics spectrum, and thus, to the successional gradient, such as stomata size and density. By comparing different permutation models in the Fourth Corner Analysis, we found that the trait-environment link was based more on the association of species with the environment than of the communities with species traits. The strong species-environment association was brought about by a clear gradient in species composition along the succession series, while communities were not well differentiated in mean trait composition. In contrast, intraspecific trait variation did not show close environmental relationships. The study confirmed the role of environmental trait filtering in subtropical forests, with traits associated with the leaf economics spectrum being the most responsive ones.

/pdf/leaf-trait-environment-relationships-in-a-subtropical-3imrcxozrj.pdf

Leaf Trait-Environment Relationships in a Subtropical Broadleaved Forest in South-East China

Evaluating the effectiveness of existing nature reserve systems for the conservation of tropical forests is an urgent task to save the remaining biodiversity. Here, we tested the effectiveness of the reserve system on Hainan Island by conducting a three-way comparison of changes in forest area in locations within the reserves, adjacent to the reserves, and far outside of the reserves. We used a general linear model to control for the effects of covariates (historical forest area, elevation, slope, and distance to nearest roads), which may also be correlated with the changes in forest area, to better explain the effectiveness of the reserve system. From 2000 to 2010, the forest area inside Hainan’s nature reserve system showed an increase while adjacent unprotected areas and the wider, unprotected landscape both experienced deforestation. However, the simple inside-outside comparisons may overestimate the protective effect of the reserve system. Most nature reserves (>60%) showed increasing fragmentation. And the risk of rapid deforestation remained high at low elevations, where remaining forests tend to be easily logged and converted to commercial plantations. Future conservation efforts should pay more attention to those sites with less challenging environmental conditions.

/pdf/effectiveness-of-nature-reserve-system-for-conserving-2icyplfw8v.pdf

Effectiveness of Nature Reserve System for Conserving Tropical Forests: A Statistical Evaluation of Hainan Island, China

How might we model an ecosystem

The interest in social media sentiment analysis and opinion mining for public security events has increased over the years. The availability of social media platforms for communication provides a valuable source of information for sentiment analysis and opinion mining research. The content shared across the media gives potential input to the physical environment and social phenomena related to public security threats. The input has been used to: monitor public security threats or emergency events, analyzing sentiment and opinionated data for threat management and the detection of public security threat events using geographic location-based sentiment analysis. However, a systematic survey that describes the trends and latest developments in this domain is unavailable. This paper presents a survey of social media sentiment analysis and opinion mining for public security. This paper aims to: understand the progress of the current state-of-the-art, identify the research gaps, and propose potential future directions. In total, 200 articles published from 2016 to 2023 were considered in this survey. The taxonomy shows the key attributes and limitations of the work presented in the surveyed articles. Subsequently, the potential future direction of work on sentiment analysis in the public security domain is suggested for interested researchers. 

Social media sentiment analysis and opinion mining in public security: Taxonomy, trend analysis, issues and future directions

We evaluated the frequently assumed but rarely tested hypothesis that in tropical and subtropical forests species form discontinuities along gradients in trait variation, which can be detected to classify species into ecologically meaningful and statistically defined groups. We also tested the hypothesis that the dominant conifer Araucaria angustifolia have a contrasting trait syndrome from the pool of angiosperms. Data were collected in subtropical mixed conifer-hardwood forests in southern Brazil. Eleven trait variables (relative growth rates, growth rates under favourable conditions, annual mortality rates, seed length, seed dispersal mode, wood density, maximum height, crown depth, stem slenderness, specific leaf area, and leaf blade length) were measured for 66 large tree species. The conifer Araucaria angustifolia differed significantly in most traits and vital rates from the angiosperm distributions. The Simple Structure Index criterion was used to identify the optimum number of non-hierarchical k-means groups. This index was largest for a solution with five groups. Non-hierarchical groups were more strongly related with the resource capture and height gradients than groups formed by hierarchical clustering. We propose the recognition of seven ecological species groups in the studied forests depending on growth rates, leaf size, wood density, height, stem slenderness, dispersal, and crown depth: Conifers, Palms, Pioneers, Large-seeded Pioneers, Wind-dispersed Large trees, Large shade-tolerant trees, and Small Shade-tolerant trees. The classification produced was coherent with the ecological strategies present in the community and represents a subdivision of Westoby’s leaf-height-seed plant strategy scheme.

Detecting ecological groups from traits: a classification of subtropical tree species based on ecological strategies

Identification of functional groups in an old-growth tropical montane rain forest on Hainan Island, China

How does the Net primary productivity respond to the extreme climate under elevation constraints in mountainous areas of Yunnan, China?

Investigating functional plant traits is essential for understanding plant responses and adaptations to global climate change and ecosystem functions. Synchronous observations of multiple plant traits across multiple sites are rare. Here, we obtained community, functional trait, and environmental data for different forest vegetation types in China’s tropical, subtropical, warm-temperate, and cold-temperate zones. Using principal component (PC) analysis, we constructed a composite–habitat gradient axis of biotic and abiotic factors across different climatic zones, differentiated functional trait compositions along the axis and their driving factors, and reached three main conclusions. (1) At the community level, the community-weighted mean and variance of each trait level differed across the climatic zones. Specific leaf areas and leaf phosphorus contents decreased with increasing PC1 values, whereas community-weighted means and variances of leaf dry-matter contents, leaf nitrogen-to-phosphorus ratios, and wood densities significantly increased with increasing PC1 values. However, the leaf nitrogen content varied along the PC1 axis. Both the community-weighted skewness and kurtosis of functional traits increased significantly with increasing PC1 values for the composite habitat gradient across the climatic zones. (2) The weighted mean, variance, skewness, and kurtosis of each functional trait exhibited different patterns on the composite habitat gradient PC2 axis than on the PC1 axis across the climatic zones, and the correlation was weak. (3) Most functional traits correlated significantly with the community-weighted mean and variance, kurtosis, and skewness. Therefore, the different functional trait compositions of forest communities in different climatic zones reflected trait convergence caused by the environment and trait differences caused by species competition in response to local-scale filtering.

/pdf/variation-in-the-functional-traits-of-forest-vegetation-7a3plmxv.pdf

Variation in the Functional Traits of Forest Vegetation along Compound Habitat Gradients in Different Climatic Zones in China

Community assembly research has mostly focused on areas with single vegetation types; however, the abiotic and biotic factors affecting community assembly act across regions. Integrating biotic and abiotic factors into “compound” habitats has gained attention as an emerging strategy to analyze spatial and temporal patterns of biodiversity. We used a compound habitat approach to explore the relative roles of habitat filtering, biotic competition, and stochastic processes in the forest community assembly of four climatic zones (tropical, subtropical, temperate, and cold temperate forests). Specifically, we combined biotic and abiotic factors in four compound ecological gradients by principal component analysis (PCA), which we used to assess the geographic and phylogenetic distribution of multiple woody plant functional traits. We found that forest functional and phylogenetic diversity shifted from clustered to overdispersed along the first compound habitat gradient (PC1) across climate zones. This finding indicates that competitive exclusion strongly affected the community assembly in tropical and subtropical forests, while habitat filtering played a key role in cold temperate forests; these mechanisms may both exist and interact in temperate forests. We also found that both habitat filtering and biotic competition affected forest community assembly across climatic regions in China. Our results elucidate the underlying mechanisms driving geographical differentiation of forest vegetation across climatic zones, and bolster empirical evidence for the conservation of forest biodiversity in China. Further research is also needed to explore whether the patterns found in this paper are prevalent in different locations in different climatic zones in China.

/pdf/community-assembly-of-forest-vegetation-along-compound-1qf556bd.pdf

Community Assembly of Forest Vegetation along Compound Habitat Gradients across Different Climatic Regions in China

The occurrence of major health events can have a significant impact on public mood and mental health. In this study, we selected Shanghai during the 2019 novel coronavirus pandemic as a case study and Weibo texts as the data source. The ERNIE pre-training model was used to classify the text data into five emotional categories: gratitude, confidence, sadness, anger, and no emotion. The changes in public sentiment and potential influencing factors were analyzed with the emotional sequence diagram method. We also examined the causal relationship between the epidemic and public sentiment, as well as positive and negative emotions. The study found: (1) public sentiment during the epidemic was primarily affected by public behavior, government behavior, and the severity of the epidemic. (2) From the perspective of time series changes, the changes in public emotions during the epidemic were divided into emotional fermentation, emotional climax, and emotional chaos periods. (3) There was a clear causal relationship between the epidemic and the changes in public emotions, and the impact on negative emotions was greater than that of positive emotions. Additionally, positive emotions had a certain inhibitory effect on negative emotions.

/pdf/changes-in-public-sentiment-under-the-background-of-major-2vkqrjh6.pdf

Changes in Public Sentiment under the Background of Major Emergencies—Taking the Shanghai Epidemic as an Example

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