AbstractThe use of artificial intelligence (AI) and machine learning (ML) has significantly enhanced ecological research in Asia by improving data processing, analysis, and pattern extraction. Analyzing 1550 articles, I show an overview of the use of AI and ML for Asian ecological research. Following the last 20 year trend, I found that the topics in Asian ecological research have transitioned from technical perspectives to more applied issues, focusing on biodiversity conservation, climate change, land use change, and societal impacts. Non‐Asian countries, on the other hand, have focused more on theoretical understanding and ecological processes. The difference between Asian and non‐Asian regions may have emerged due to the ecological challenges faced by Asian countries, such as rapid economic growth, land development, and climate change impacts. In both regions, deep learning related technology has been emerging (e.g., big data collection including image and movement). Within Asia, China has been the Asia‐leading country for AI/ML applications followed by Korea, Japan, India, and Iran. The number of computer science education programs in China has been increasing 3.5× times faster than that in the United States, indicating that a nationwide strategy for computer science development is key for ecological science with AI. Overall, the adoption of AI and ML technologies in ecological studies in Asia has propelled the field forward and opened new avenues for innovative research and conservation practices.

AbstractTropical lowland rainforests are considered to be ecologically important refugia of national and global significance, yet wide‐scale deforestation and degradation of tropical lowland rainforests lead to losses in biodiversity. Seed storage behavior information is required for the effective restoration of these forests. Here, we studied the seed storage behavior of 42 selected tropical lowland rainforest tree species from Sri Lanka with the aim to test the reliability of current experimental methods and predictive models to predict the desiccation sensitivity of seeds. Seed storage behavior was experimentally determined through the 100 seed method and the results were compared with three predictive models; thousand seed weight–moisture content (TSW–MC), seed coat ratio–seed mass (SCR–SM), and phylogenetic affiliation models. Based on the 100 seed method, 28 species were identified as desiccation sensitive and 14 species were identified as desiccation tolerant. Compared to the 100 seed method, the predictability of the SCR–SM model was 70%, whereas the TSW–MC and phylogenetic affiliation models showed 52% and 58% predictability, respectively. Due to its higher predictability, the SCR–SM model has a high potential to be an effective predictive tool of seed storage behavior. This study revealed that tropical lowland rainforests are dominated by trees producing desiccation‐sensitive seeds. Further, species dispersing seeds in the peak rainy season have desiccation‐sensitive seeds, while those dispersing seeds in the normal wet season have desiccation‐tolerant seeds. Another key finding was that 100% of the subcanopy species produce nonorthodox, that is, desiccation‐sensitive seeds, which gradually decrease from subcanopy to understory.

AbstractDisentangling the distribution patterns of biodiversity along altitudinal gradients and their drivers has been a hot topic in ecological research. Different forest strata show multiple distribution patterns influenced by different community assembly mechanisms. Here, we measure the dominant ecological processes affecting three forest strata (tree, shrub, and herb layers) along altitudinal gradients. We sampled plants with different forest strata in 21 plots located from 2500 to 3700 m in Lasha Mountain, northwestern Yunnan. The taxonomic alpha diversity of the herb layer showed a monotonic decreasing trend with increasing altitude, while the shrub layer was characterized by a single peak, and the tree layer showed no significant change with increasing altitude. We observed a decreasing pattern of phylogenetic diversity with increasing altitude in the herb layer, whereas phylogenetic diversity did not change in the tree and shrub layers. The phylogenetic structure of these three layers showed the same pattern: phylogenetic clustering at low altitudes and overdispersion at middle and high altitudes. The diversity and phylogenetic structure of the herb layer were driven by climate (average dry season precipitation) and topographic (slope and aspect) factors, while shrub layer diversity was mainly influenced by tree layer richness. Overall, the phylogenetic structure pattern of the three forest strata changed from clustered to overdispersed with increasing altitude, indicating that environmental filtering was the main driver at low altitudes, while interspecific competition dominated at middle and high altitudes.

AbstractThe relationship between biodiversity and ecosystem multifunctionality (EMF) is critical to understanding the dynamics of ecosystem services. Several studies have investigated alterations in multiple ecosystem functions under grassland degradation and its relationship with taxonomic diversity. However, how multidimensional biodiversity (taxonomic, functional, and phylogenetic diversity) and abiotic factors mediate EMF in degraded alpine meadows has yet to be well been explored. In this study, alpine meadows with different degrees of degradation were investigated in Maqu County, Gansu Province, China. The average and multi‐threshold methods were used to quantify EMF, while structural equation modeling (SEM) was used for statistical analysis. The results show that: (1) Degradation of alpine meadows has altered the species composition and diversity of plant communities. (2) Taxonomic, functional, and phylogenetic diversity were all significantly and positively correlated with EMF, and species richness, functional richness and Faith's PD effectively drive EMF within thresholds of 22%–75%, 20%–86% and 42%–72%, with maximum effects of 0.29, 0.33 and 0.12, respectively. (3) Degradation of alpine meadows directly and significantly reduced EMF, and mediated indirectly through plant diversity and soil abiotic factors. The multifunctionality index for different degrees of degradation showed non‐degraded (60.89) > light degraded (37.84) > moderate degraded (−14.17) > heavy degraded (−48.55). The results of this study reveal the relative importance of multidimensional plant diversity in predicting EMF of degraded alpine meadows, and potential mechanisms by which plant diversity and abiotic factors mediate the effects of alpine meadow degradation on EMF.

AbstractLong‐term monitoring of wild bee communities at fixed locations using a consistent sampling procedure has been rare, although declines in their diversity and abundance due to anthropogenic impacts are a major concern. At two sites in urban green areas in Sapporo city, northern Japan, where wild bee surveys were conducted in 1959, 1979, 1989, 2018, and 2019, the number of individuals of bee genera was recorded. Patterns of seasonal changes in bee abundance collected at weekly censuses differed between 1979–1989 and 2018–2019. The total bee abundance collected in annual surveys consisting of standardized censuses demonstrated 50% and 41% declines at the two sites from 1959–1989 to 2018–2019. Among the 16 genera found in the surveys, 3 abundant genera, Andrena, Lasioglossum, and Ceratina, always exhibited lower abundance in 2018–2019 than in 1959–1989 at both sites. The remarkable declines in wild bee abundance should be examined in relation to various possible factors of anthropogenic impacts.

AbstractPlants growing on karst soils, which are characterized by high pH (>7.5–8.0) and low phosphorus availability, often exhibit phosphorus deficiency. However, little is known about the soil nutrient availabilities and foliar nutrient concentrations of trees in karst ecosystems with lower soil pH (<7.0). In this study, we analyzed soil properties and nutrient concentrations of leaf litter from two secondary forests in the Asian monsoon temperate region of Japan, one on karst (limestone) soil and the other on non‐karst (sandstone) soil. We also compared the live leaf nutrient concentrations of four dominant tree species (Carpinus tschonoskii, Cornus macrophylla, Neolitsea sericea, and Quercus variabilis) found in both sites. The karst soil had a higher pH (6.5) than the non‐karst soil (5.6), as well as higher phosphorus concentrations and calcium availability, but lower potassium availability. The phosphorus concentrations measured using Truog ([NH4]2SO4) and Olsen (NaHCO3) extraction methods were both higher in the karst soil. The availabilities of ammonium and nitrate in the soil did not differ significantly between the sites. The concentrations of calcium, potassium, and phosphorus in the live leaves and leaf litter reflected their availability in the soil, and the litter nitrogen concentration was higher in the karst forest. Overall, this karst soil with a relatively low pH (6.5) was rich in phosphorus but poor in potassium. Karst soil may provide a large quantity of phosphorus for trees at low pH. Future research should investigate the change in phosphorus availability of karst soils at different degrees of weathering.

AbstractThe quantification of plant diversity–productivity relationships is essential for accurate productivity assessments. Global change drivers are altering resource availability and biodiversity. However, the extent to which multiple attributes of diversity (species, functions) buffer community productivity in response to the resource availability changes and the potential driver mechanisms of the diversity‐productivity relationship still needs to be the consensus. We investigated the ephemeral plant diversity–productivity relationships of different attributes along a precipitation gradient in the Gurbantunggut Desert, China. To evaluate the potential mechanisms by which diversity and functional composition affect aboveground productivity (niche complementarity and selection effect). Our results showed that (1) the variance of species richness (SR), Rao's quadratic entropy (RaoQ), community‐weighted mean of height (CWMH), and community‐weighted mean of leaf phosphorus concentration (CWMP) was larger among sites (variation between different sites) than subplots (variation between different subplots). Among subplots, the variance of community‐weighted mean of specific leaf area (CWMSLA), community‐weighted mean of leaf carbon concentration (CWMC), and community‐weighted mean of leaf nitrogen concentration (CWMN) was larger than the sites. (2) SR, RaoQ, CWMC, CWMN, CWMH, pH, and mean annual precipitation (MAP) collectively influenced the accumulation of aboveground biomass (AGB). (3) Species diversity and MAP have strongly affected AGB and accounted for 50% and 42%. The study confirms that SR is the optimal predictor of biomass in ephemeral plants. Complementation effects may be the primary mechanism explaining the relationship between biodiversity and productivity in the Gurbantunggut Desert, and thus the effect of plant diversity cannot be downplayed.

AbstractTrees in wetlands emit a significant amount of methane (CH4) into the atmosphere which is produced in the soil where anaerobic conditions prevail. However, only very few studies have considered the role of trees in the CH4 budget of mangrove forests. How tree CH4 emissions () vary between and within individuals, and how these emissions vary with the day/night alternation and the tidal cycle, have not yet been elucidated. We measured from buttress roots and stems on individuals of Bruguiera gymnorrhiza of different sizes. We also measured from trees and sediments over a 24‐h cycle. Higher was measured on the buttress roots than on the stems, with a decreasing trend with height along the stems on a majority of trees. exhibited large variations over a 24‐h cycle which were observed for the first time in this study. from sediment was twice higher at low tide compared to just before or after the flood period. from non‐submerged stem positions at high tide was four times higher during the day than during the night. On buttress roots and on stem portion which were submerged, high were measured at the beginning of the ebb tide even at night. A better understanding of variability from mangrove trees and its controls, at different time scales and along spatial gradients is needed for accurate estimation of CH4 budgets of mangrove forests.

AbstractConsistent individual behavioral differences from other members of local populations are called animal personality, and a suite of these correlated behaviors generates a behavioral syndrome. Differential selection patterns among personality types can be largely influenced by predatory behavior. Prey has a large arsenal of antipredator behaviors at their disposal; However, how closely these behaviors are linked to personality is almost unknown. Using a social model species, the Great Tit, Parus major, we investigated whether antipredator behavior in response to predators is correlated with personality. First, we determined if individual differences in exploratory behavior were consistent across trials, that is, whether they were repeatable. Second, we looked into how antipredator behavior was correlated to personality. Individuals were subjected to two repeated trials of standard personality assays followed by an alternative control (Rock Pigeon, Columba livia domestica) and predator display (Eurasian Sparrowhawk, Accipiter nisus) treatment. We found that exploratory behavior was repeatable across trials and had a greater tendency for positive correlation with antipredator behavior when a predator model was displayed. Individuals that swiftly explored novel environments were slower to react to predators than those who explored the novel room slowly. As a result, our findings provide some of the first experimental evidence for a link between exploratory and antipredator behavior, suggesting that personality traits may impact individual fitness.

AbstractEnvironmental heterogeneity can influence the formation of different vegetation types, even at small spatial scales. However, little is known about the factors that drive communities at local scales and species' mechanisms to adapt to different environments. Here, we investigated the influence of local environmental conditions and spatiality on the floristic variation of woody vegetation and ecological strategies of shrub‐tree species in the Brazilian savanna. We sampled adjacent sites in three substrate types—deep soil at high altitude (in Red Oxisol, with vegetation locally called Typical Cerrado—TCRO), deep soil, sandy and at low elevation (Typical Cerrado in Entisol Quartzipsamment—TCEQ), and shallow soil with rocky outcrops at high elevation (in Entisol Lithic, with vegetation known locally as Rupestrian Cerrado—RCEL). At each environment, we inventoried the vegetation, analyzed the physical–chemical soil properties, and recorded the elevation and geographic coordinates. For the most representative species of each site and the most common one among the environments, we evaluated the functional attributes (leaf nutrient concentration, specific leaf area, and maximum population heights). We showed that substrate type and elevation explain most of the floristic variation at the local scale and that the low nutritional demand constitutes the main strategy used by the species in RCEL, while in TCEQ and TCRO, species are more efficient in resource acquisition. Our results revealed that local ecological factors and processes drive species distribution. Therefore, variations in vegetation, even at the local scale must be considered to conserve biodiversity effectively.