Evergreen Broadleaf Trees Research Articles

Assessment of climatic influences on net primary productivity along elevation gradients in temperate ecoregions

Elevation gradients significantly influence net primary productivity (NPP), but the relationship between elevation, climate variables, and vegetation productivity remains underexplored, particularly in diverse ecological zones. This study quantifies the impact of elevation and climatic variables on NPP in northern Pakistan, hypothesizing that elevation modulates NPP through its influence on temperature and precipitation patterns. Using remote sensing data (MODIS ERA5) and advanced ecological models like the Eddy Covariance-Light Use Efficiency (EC-LUE) model and the Thornthwaite Memorial Model (TMM), we analyzed Gross Primary Productivity (GPP) dynamics across various vegetation types and elevations from 2001 to 2023. Our findings show a mean annual NPP of 323.46 g C m-2 a-1, with an annual increase of 5.73 g C m-2 a-1. Significant elevation-dependent variations were observed, especially in mid-elevation zones (401 to 1600 meters), where NPP increased at a rate of 0.174 g C m-2 a-1 per meter (R² = 0.808, p < 0.01). In contrast, higher elevations (2800-5200 meters) exhibited a decline in NPP, decreasing by -0.171 g C m-2 a-1 per meter (R² = 0.905, p < 0.001). Temperature and precipitation were key drivers, with precipitation positively correlating with NPP across all vegetation types, particularly in Evergreen Needleleaf and Broadleaf Trees. The EC-LUE model's GPP estimates closely matched MODIS data (R² = 0.82), demonstrating the model's reliability. These findings highlight the critical role of elevation and climatic factors in vegetation productivity and underscore the need for targeted ecological management and conservation strategies. The insights from this research are vital for global climate adaptation policies and sustainable development goals, contributing to ecological resilience and carbon sequestration efforts worldwide.

Range‐wide prediction of habitat suitability for king cobras under current and future scenarios

Abstract Ophiophagus hannah, commonly known as the king cobra, is listed as vulnerable by the International Union for Conservation of Nature (IUCN) and is protected under national laws in most countries. This charismatic species faces multiple threats, including habitat loss, human persecution, illegal trafficking, and climate change. Due to the king cobra's sensitivity to environmental conditions, its population status and trends are barely understood. This study used the MaxEnt algorithm to predict the potential distribution of king cobras across Asia, a method that has been successfully implemented in modeling distributions of various species in the region. The findings showed that Evergreen Broadleaf Trees emerged as the most influential variable for the distribution of Ophiophagus hannah with a 27.3% contribution, followed by the Mean Diurnal Range and Urban/Built‐up areas. Jackknife analysis identified the Mean Diurnal Range as having the highest testing gain. Approximately 413,268 km2 were found to have the most suitable climatic conditions for sustaining this species. Countries such as India, Myanmar, Bangladesh, Vietnam, Cambodia, Indonesia, and Malaysia were identified as having favorable conditions. Under the future climate scenario SSP5‐8.5, the extent of suitable habitats (maximum) for the king cobra is projected to decrease in the periods 2041–2060 and 2081–2100. This report provides valuable insights that could inform conservation strategies for O. hannah in these regions.

Optical flow of temperature reveals climate change patterns for agriculture and forestry

The study of climate change's impact on terrestrial ecosystems is crucial for achieving societal and economic sustainability and human well-being. Domains like agriculture and forestry respond to climate change similarly to other terrestrial natural biomes, experiencing reductions in productivity, migration, and loss of biodiversity. However, there is a research gap in understanding climate velocity for different land cover and land use types, which could reveal vulnerability patterns in agriculture and forestry. To address this gap, we present the first study of climate velocity for major land cover and land use classes with a focus on major crop growing regions and functional forest types at the continental level. To enable this analysis, we introduce a new approach for estimating climate velocity based on optical flow. This approach allows us to conduct a global study, improve ecosystem interconnection representation, and reduce the model's sensitivity to noisy data and parametrization. Our study highlights the significant vulnerability to climate change of agriculture as a land cover type with a climate velocity 15% higher than of other vegetation land cover classes. Furthermore, the analysis of climate velocity for functional tree types reveals the highest expected impact on deciduous and evergreen needleleaf trees primarily concentrated in regions with the highest climate velocity, especially in sub-polar and temperate climates. Conversely, tropical forests dominated by evergreen broadleaf tree types exhibits marked variations in climate velocity with the highest rates in South America and Africa and three times lower in Asia. Additionally, our analysis of climate velocity for agriculture shows that North American croplands experience the highest climate velocity exceeding the global average by 32%. This trend is consistent for major crop types such as soybean that have higher climate velocity than globally for 49%, rapeseed and sunflower for 39%, cotton for 35%, maize for 32%, and wheat for 30%. Notably, areas dedicated to cereals, sugar beet, and sunflowers are located in zones with climate velocities higher than the global average by 15%, 12%, and 9%, respectively. These patterns indicate potential shifts in the agriculture and forestry structures in the near future that coherent with recent climate change studies and will have significant impact on the socio-economic dimension of humanity sustainability.

A Novel Approach to Mapping the Spatial Distribution of Fruit Trees Using Phenological Characteristics

The lack of high-spectral and high-resolution remote sensing data is impeding the differentiation of various fruit tree species that share comparable spectral and spatial features, especially for evergreen broadleaf trees in tropical and subtropical areas. Here, we propose a novel decision tree approach to map the spatial distribution of fruit trees at a 10 m spatial resolution based on the growth stage features extracted from Sentinel-1A (S-1A) time-series synthetic aperture radar (SAR) data. This novel method was applied to map the spatial distribution of fruit trees in Maoming City, which is known for its vast cultivation of fruit trees, such as litchi, citrus, and longan. The results showed that the key to extracting information on the distribution of fruit trees lies in the fact that the fruit ripening and expansion period attenuates the information on the vegetation of fruit trees, a characteristic of the reproductive period. Under VH polarization, different fruit tree growth stage traits were more separable and easier to distinguish. The optimal features, such as Hv (high valley value of the 14 May, 26 May, and 7 June SAR data), Tb (difference between the 7 June and 14 January SAR data), Cr (high valley value of the 13 July, 25 July, and 6 August SAR data), and Lo (high valley value of the 23 September, 17 October, and 11 November SAR data), were constructed based on the optimal window. The thresholds for these features were set to 1, 1, 1.5, and 1, respectively. The classification model can effectively distinguish different fruit trees and extract distribution information with overall accuracy (OA) of 90.34% and a Kappa coefficient of 0.84. The proposed method extracts the spatial distribution information of different fruit trees more accurately and provides a reference for the extraction of more tropical and subtropical species.

Palynological and sedimentological evidence for early mid-Holocene hydroclimatic variability in the Ningshao Plain, East China

The southeastern coastal areas of China represent one of the most populous and economically developed regions in China, but they are often severely affected by flood hazards. Therefore, studying the phenomenon and mechanisms behind extreme rainfall changes in this region is of great significance for economic and social development. In this study, we present high-resolution pollen and grain-size records from the Shanglin Lake located in Zhejiang, eastern China, based which changes in the frequency of paleo-flood events were reconstructed and the climatic context was inferred. Our pollen records show that the content of evergreen broadleaf trees gradually increased during 8000–7000 cal. yr BP, reflecting the gradually increasing temperature in the growing season. The content of Altingia increased substantially during the periods of 7960–7860, 7600–7500, and 7200–7100 cal. yr BP, especially in the first and last periods, indicating the prevalence of an El Niño-like condition in the study area during the early mid-Holocene warm period. Grain-size record shows that the prolonged El Niño condition facilitated a significant increase in flood frequency. Our results suggest that, similar to that of today, the early mid-Holocene warm climate was the most important factor controlling extreme hydroclimatic changes in the middle and lower reaches of the Yangtze River.

Carbon use strategies in shoot and acorn growth of two evergreen broadleaf trees unraveled by seasonal carbohydrate measurements and carbon isotope analysis.

Woody species have evolved carbon (C) storage processes that meet needs for reserves associated with asynchronies between C supply and demand. However, our understanding of storage dynamics is still elusive in mature trees, especially when reproduction is involved. Integrated analyses of isotope ratios, concentrations, and biomass may enhance understanding of stored C fractions' dynamics and roles. Thus, we monitored starch and soluble sugars (SSs), C isotope ratios, and biomass, in leaves, twigs and reproductive organs of two mature evergreen broadleaf trees, Quercus glauca and Lithocarpus edulis, for two years. During the growing season, no starch was observed in twigs, while constant starch levels were observed in leaves. Increase in SSs for winter hardening was earlier in L. edulis than in Q. glauca, in line with L. edulis acorns' earlier ripening. Decrease in SSs and increase in starch occurred simultaneously in the next spring. In addition, sucrose accounted for less than 10% of total SSs in leaves of both species, whereas mannose accounted for up to 75% in Q. glauca and myo-inositol up to 23% in L. edulis, indicating species specific sugar composition. These results indicate that seasonal variation of SSs fraction was more reflective to climatic change and NSC storage was less influenced by reproduction. No starch was detected in acorn organs of either Q. glauca or L. edulis except in ripening seeds. The biomass of ripe acorns was 1.7- and 6.4-fold greater than that of current-year twigs in Q. glauca and L. edulis, respectively. Bulk twigs and reproductive organs were ca. 1.0‰ 13C enriched relative to bulk leaves, which was lower than in deciduous trees. These results indicate that new photo-assimilate is the predominant C source for reproductive growth. These findings provide new insights into the dynamics of C storage in relation to reproduction in evergreen broadleaf trees.

Parameter sensitivity analysis for a biochemically-based photosynthesis model

A challenge for the development of Land Surface Models (LSMs) is improving transpiration of water exchange and photosynthesis of carbon exchange between terrestrial plants and the atmosphere, both of which are governed by stoma in leaves. In the photosynthesis module of these LSMs, variations of parameters arising from diversity in plant functional types (PFTs) and climate remain unclear. Identifying sensitive parameters among all photosynthetic parameters before parameter estimation can not only reduce operation cost, but also improve the usability of photosynthesis models worldwide. Here, we analyzed 13 parameters of a biochemically-based photosynthesis model (FvCB), implemented in many LSMs, using two sensitivity analysis (SA) methods (i.e., the Sobol’ method and the Morris method) for setting up the parameter ensemble. Three different model performance metrics, i.e., Root Mean Squared Error (RMSE), Nash Sutcliffe efficiency (NSE), and Standard Deviation (STDEV) were introduced for model assessment and sensitive parameters identification. The results showed that among all photosynthetic parameters only a small portion of parameters were sensitive, and the sensitive parameters were different across plant functional types: maximum rate of Rubisco activity (Vcmax25), maximum electron transport rate (Jmax25), triose phosphate use rate (TPU) and dark respiration in light (Rd) were sensitive in broad leaf-evergreen trees (BET), broad leaf-deciduous trees (BDT) and needle leaf-evergreen trees (NET), while only Vcmax25 and TPU are sensitive in short vegetation (SV), dwarf trees and shrubs (DTS), and agriculture and grassland (AG). The two sensitivity analysis methods suggested a strong SA coherence; in contrast, different model performance metrics led to different SA results. This misfit suggests that more accurate values of sensitive parameters, specifically, species specific and seasonal variable parameters, are required to improve the performance of the FvCB model.

Interactive effects of elevated temperature and drought on plant carbon metabolism: A meta-analysis.

Elevated temperature (Te ) and drought often co-occur and interactively affect plant carbon (C) metabolism and thus the ecosystem C cycling; however, the magnitude of their interaction is unclear, making the projection of global change impacts challenging. Here, we compiled 107 journal articles in which temperature and water availability were jointly manipulated, and we performed a meta-analysis of interactive effects of Te and drought on leaf photosynthesis (Agrowth ) and respiration (Rgrowth ) at growth temperature, nonstructural carbohydrates and biomass of plants, and their dependencies on experimental and biological moderators (e.g., treatment intensity, plant functional type). Our results showed that, overall, there was no significant interaction of Te and drought on Agrowth . Te accelerated Rgrowth under well-watered conditions rather than under drought conditions. The Te × drought interaction on leaf soluble sugar and starch concentrations were neutral and negative, respectively. The effect of Te and drought on plant biomass displayed a negative interaction, with Te deteriorating the drought impacts. Drought induced an increase in root to shoot ratio at ambient temperature but not at Te . The magnitudes of Te and drought negatively modulated the Te × drought interactions on Agrowth . Root biomass of woody plants was more vulnerable to drought than that of herbaceous plants at ambient temperature, but this difference diminished at Te . Perennial herbs exhibited a stronger amplifying effect of Te on plant biomass in response to drought than did annual herbs. Te exacerbated the responses of Agrowth and stomatal conductance to drought for evergreen broadleaf trees rather than for deciduous broadleaf and evergreen coniferous trees. A negative Te × drought interaction on plant biomass was observed on species-level rather than on community-level. Collectively, our findings provide a mechanistic understanding of the interactive effects of Te and drought on plant C metabolism, which would improve the prediction of climate change impacts.

Field plus lab experiments help identify freezing tolerance and associated genes in subtropical evergreen broadleaf trees: A case study of Camellia oleifera.

The molecular mechanisms of freezing tolerance are unresolved in the perennial trees that can survive under much lower freezing temperatures than annual herbs. Since natural conditions involve many factors and temperature usually cannot be controlled, field experiments alone cannot directly identify the effects of freezing stress. Lab experiments are insufficient for trees to complete cold acclimation and cannot reflect natural freezing-stress responses. In this study, a new method was proposed using field plus lab experiments to identify freezing tolerance and associated genes in subtropical evergreen broadleaf trees using Camellia oleifera as a case. Cultivated C. oleifera is the dominant woody oil crop in China. Wild C. oleifera at the high-elevation site in Lu Mountain could survive below -30°C, providing a valuable genetic resource for the breeding of freezing tolerance. In the field experiment, air temperature was monitored from autumn to winter on wild C. oleifera at the high-elevation site in Lu Mountain. Leave samples were taken from wild C. oleifera before cold acclimation, during cold acclimation and under freezing temperature. Leaf transcriptome analyses indicated that the gene functions and expression patterns were very different during cold acclimation and under freezing temperature. In the lab experiments, leaves samples from wild C. oleifera after cold acclimation were placed under -10°C in climate chambers. A cultivated C. oleifera variety "Ganwu 1" was used as a control. According to relative conductivity changes of leaves, wild C. oleifera showed more freezing-tolerant than cultivated C. oleifera. Leaf transcriptome analyses showed that the gene expression patterns were very different between wild and cultivated C. oleifera in the lab experiment. Combing transcriptome results in both of the field and lab experiments, the common genes associated with freezing-stress responses were identified. Key genes of the flg22, Ca2+ and gibberellin signal transduction pathways and the lignin biosynthesis pathway may be involved in the freezing-stress responses. Most of the genes had the highest expression levels under freezing temperature in the field experiment and showed higher expression in wild C. oleifera with stronger freezing tolerance in the lab experiment. Our study may help identify freezing tolerance and underlying molecular mechanisms in trees.

Evaluation of the Community Land Model-Simulated Specific Leaf Area with Observations over China: Impacts on Modeled Gross Primary Productivity

Specific leaf area (SLA) is a key leaf functional trait associated with the ability to acquire light. Substantial variations in SLA have not been well described in the community land model (CLM) and similar terrestrial biosphere models. How these SLA variations influence the simulation of gross primary productivity (GPP) remains unclear. Here, we evaluated the mismatch in SLA between the CLM4.5 and observed data collected from China and quantified the impacts of SLA variation calculated from both observations and the default values across seven terrestrial biosphere models on modeled GPP using CLM4.5. The results showed that CLM4.5 tended to overestimate SLA values at the top and gradient of the canopy. The higher default SLA values could cause an underestimation of the modeled GPP by 5–161 g C m−2 yr−1 (1%–7%) for temperate needleleaf evergreen tree (NET), temperate broadleaf deciduous tree (BDT), and C3 grass and an overestimation by 50 g C m−2 yr−1 (2%) for temperate broadleaf evergreen tree (BET). Moreover, the observed SLA variation among species ranged from 21% to 59% for 14 plant functional types (PFTs), which was similar to the variation in default SLA values across models (9%–60%). These SLA variations would lead to greater changes in modeled GPP by 7%–19% for temperate NET and temperate BET than temperate BDT and C3 grass (2%–9%). Our study suggested that the interspecific variation in SLA and its responses to environmental factors should be involved in terrestrial biosphere models; otherwise, it would cause substantial bias in the prediction of ecosystem productivity.

Short term variation in leaf level water use efficiency in a tropical forest.

The representation of stomatal regulation of transpiration and CO2 assimilation is key to forecasting terrestrial ecosystem responses to global change. Given its importance in determining the relationship between forest productivity and climate, accurate and mechanistic model representation of the relationship between stomatal conductance (gs ) and assimilation is crucial. We assess possible physiological and mechanistic controls on the estimation of the g1 (stomatal slope, inversely proportional to water use efficiency) and g0 (stomatal intercept) parameters, using diurnal gas exchange surveys and leaf level response curves of six tropical broadleaf evergreen tree species. g1 estimated from ex-situ response curves averaged 50% less than g1 estimated from survey data. While g0 and g1 varied between leaves of different phenological stages, the trend was not consistent among species. We identified a diurnal trend associated with g1 and g0 that significantly improved model projections of diurnal trends in transpiration. The accuracy of modelled gs can be improved by accounting for variation in stomatal behavior across diurnal periods, and between measurement approaches, rather than focusing on phenological variation in stomatal behavior. Additional investigation into the primary mechanisms responsible for diurnal variation in g1 will be required to account for this phenomena in land surface models.

Genetic diversity and paternity analysis of Mytilaria laosensis hybrids using microsatellite markers provide insight into the breeding system

Mytilaria laosensis is an important evergreen broadleaf tree species in Southeast Asia and can provide excellent raw materials for pulp and fiberboard industrial production due to its fast growth and desirable wood properties. It produces hundreds of hermaphrodite flowers in a single inflorescence and controlled pollination through emasculation is difficult. In this study, we adopted hand-assisted pollination to investigate the seed set ratio and hybrid efficiency. A total of 65 cross combinations including 723 inflorescences were performed by using five female and eight male trees. The fruit-set rate varied greatly from 6.67% to 84.62% among different groups with an average of 23.68%. Moreover, new microsatellite markers were developed through transcriptome sequencing and ten polymorphic markers were screened out to examine the genetic variation and hybrid purity of 742 progeny. An average of 14.7 alleles was detected per locus. The parent population showed the highest expected heterozygosity of 0.77, while other hybrid populations exhibited different heterozygosity values from 0.46 to 0.71. Both principal coordinate analysis and phylogenetic tree revealed that these groups could be divided into five clusters and each cluster represented progeny which shared the same female parent. Paternity test showed that 18 offspring were sired by the designated pollen parents, while all other offspring were all heterozygous with pollens from non-target father. The results implied that outcrossing might be the predominant breeding system and self-incompatibility might exist in M. laosensis . This study provides useful reference for molecular-assisted hybrid breeding research and a practicable approach for new cultivar development in tree species. • The fruit-set rate varied greatly in different cross combinations of M. laosensis . • Ten highly efficient SSR markers were developed through transcriptome sequencing. • High genetic diversity level was detected among 52 hybrid groups. • The 18 offspring were sired by the designated parents and others were all heterozygous. • Self-incompatibility might exist in M. laosensis.

Review: Monitoring of land cover changes and plant phenology by remote‐sensing in East Asia

AbstractTo achieve a sustainable society and solve the problems caused by climate change and socioeconomic activities, it is necessary to monitor the spatial and temporal variability of ecosystem functions, services, and biodiversity at both regional and global scales. During the last decade, we have seen rapid and significant improvement in satellite and near‐surface remote‐sensing technologies. In this review, we describe how remote‐sensing observations are being used to effectively evaluate the spatial and temporal variability of land use and cover types and of plant phenology in East Asia. We discuss the current status, uncertainties, problems, and future perspectives for terrestrial ecosystem and biodiversity monitoring, and we address the multidisciplinary research by incorporating in situ and satellite observations for East Asia. Recent satellites with advanced optical sensors, such as MultiSpectral Instrument/Sentinel‐2A/2B, Advanced Himawari Imager/Himawari‐8, and PlanetScope, and satellites with synthetic aperture radar, such as Advanced Land Observing Satellite‐2, allow detailed monitoring of land use and cover type changes and plant phenology. These satellite sensors can provide images with high spatial (3–10 m) and high temporal (10 min to 5 days) resolution, at both large (≥1 km2) and small (&lt;1 km2) scales. In particular, researchers are expected to develop discrimination techniques that will enable these advanced satellite technologies to detect evergreen broadleaf trees and ways to estimate the geographic distribution of leaf traits. We encourage more collaborations among ecologists, engineers, and remote‐sensing scientists to share their abundant knowledge and experience and thereby improve the monitoring capabilities.

Embolism resistance explains mortality and recovery of five subtropical evergreen broadleaf trees to persistent drought.

Subtropical evergreen broadleaf forests (SEBF) are experiencing and expected to suffer more frequent and severe drought events. However, how the hydraulic traits directly link to the mortality and recovery of SEBF trees remains unclear. In this study, we conducted a drought-rewatering experiment on tree seedlings of five dominant species to investigate how the hydraulic traits were related to tree mortality and the resistance and recovery of photosynthesis (A) and transpiration (E) under different drought severities. Species with greater embolism resistance (P50 ) survived longer than those with a weaker P50 . However, there was no general hydraulic threshold associated with tree mortality, with the lethal hydraulic failure varying from 64% to 93% loss of conductance. The photosynthesis and transpiration of tree species with a greater P50 were more resistant to and recovered faster from drought than those with lower P50 . Other plant traits could not explain the interspecific variation in tree mortality and drought resistance and recovery. These results highlight the unique importance of embolism resistance in driving carbon and water processes under persistent drought across different trees in SEBFs. The absence of multiple efficient drought strategies in SEBF seedlings implies the difficulty of natural seedling regeneration under future droughts, which often occurs after destructive disturbances (e.g., extreme drought events and typhoon), suggesting that this biome may be highly vulnerable to co-occurring climate extremes.

Review: Vegetation history of Cryptomeria japonica in Japan since the last interglacial period

AbstractThe natural distribution of Japanese cedar (Cryptomeria japonica) has been disturbed by human activities, owing mainly to its value as timber; thus, its position in the vegetation zone of Japan is not clear. Therefore, it is important to determine the history of C. japonica forests before human influence. We reviewed the transitions in distribution and abundance of C. japonica in the Japanese Archipelago since the last interglacial period by using published pollen data. During the last interglacial, temperate deciduous broadleaf forests developed on northeastern Honshu Island, whereas on southwestern Honshu Island C. japonica populations increased, accompanied by warm‐temperate evergreen broadleaf trees. During the first half of the last glacial period, C. japonica forests developed throughout the Japanese Archipelago except on Hokkaido. Thereafter, 60,000–30,000 years ago, C. japonica covered the area around Lake Biwa and the Izu Peninsula. During the Last Glacial Maximum, C. japonica was most abundant on the Izu Peninsula, and small refugial populations were located along the coast of the Sea of Japan from southwestern to northeastern Honshu, and along the Pacific coast of Shikoku Island. During the Middle Holocene, C. japonica populations increased rapidly in southwestern Honshu. Two thousand years ago, before the intensification of human activities, C. japonica was widespread in warm‐ to cool‐temperate zones on the Sea of Japan side of Honshu, the Izu Peninsula, the Pacific coast of Shikoku Island, and Yakushima Island. This evidence indicates that C. japonica is one of the major tree species in the Japanese vegetation zone.

Monthly Dynamical Patterns of Nitrogen and Phosphorus Resorption Efficiencies and C:N:P Stoichiometric Ratios in Castanopsis carlesii (Hemsl.) Hayata and Cunninghamia lanceolata (Lamb.) Hook. Plantations

Trees can resorb nutrients to preserve and reuse them before leaves fall, which could efficiently adapt to environmental changes. However, the nutrient requirements of trees in different months with seasonal climate changes are often neglected. In this study, we selected plantations of an evergreen broadleaf tree (Castanopsis carlesii (Hemsl.) Hayata) and a coniferous tree (Cunninghamia lanceolate (Lamb.) Hook.) in the subtropics. The monthly dynamics of leaf nitrogen (N) and phosphorus (P) resorption efficiencies and C:N:P stoichiometric ratios were checked along a growing season from April to October 2021. Trees in both plantations exhibited efficient N and P resorption but with significant monthly variations. The N and P resorption efficiencies in the Cunninghamia lanceolata plantation ranged from 34.26% to 56.28% and 41.01% to 54.85%, respectively, and were highest in September. In contrast, N and P resorption efficiencies in the Castanopsis carlesii plantation ranged from 11.25% to 34.23% and 49.22% to 58.72%, respectively, and were highest in July. Compared with the Cunninghamia lanceolata, the C:N of the Castanopsis carlesii plantation was significantly lower, while its C:P was significantly higher in May and September. The Castanopsis carlesii plantation was strongly limited by P (the N:P ratios in mature leaves were higher than 20), whereas the Cunninghamia lanceolata plantation might be limited by both N and P (the N:P ratios in mature leaves were between 10 and 20). In addition, the statistical analyses revealed that temperature and precipitation were significantly associated with N and P resorption efficiencies, but the relationships were controlled by forest types. These findings highlight that efficient resorption of N and P may be beneficial in regulating nutrient limitation and balance in subtropical forest ecosystems. These results contribute to the understanding of N and P utilization strategies of trees and provide a theoretical basis for vegetation management in the subtropics.

Basin management inspiration from impacts of alternating dry and wet conditions on water production and carbon uptake in Murray-Darling Basin

The impacts of alternating dry and wet conditions on water production and carbon uptake at different scales remain unclear, which limits the integrated management of water and carbon. We quantified the response of runoff efficiency (RE) and plant water-use efficiency (PWUE) to a typical shift from dry to wet episode of 2003–2014 in Australia's Murray-Darling basin using good and specific data products for local application, including Australian Water Availability Project, Penman-Monteith-Leuning Evapotranspiration V2 product, MODIS MCD12Q1 V6 Land Cover Type and MODIS MOD17A3 V055 GPP product. The results show that there are significant power function relationships between RE and precipitation for basin and all ecosystems, while the PWUE had a negative quadratic correlation with precipitation and satisfied the significance levels of 0.05 for basin and the ecosystems except the grassland and cropland. The shrubs can achieve the best water production and carbon uptake under dry conditions, while the evergreen broadleaf trees and evergreen needleleaf trees can obtain the best water production and carbon uptake in wet conditions, respectively. These findings help integrated basin management for balancing water resource production and climate change mitigation.

Insect Herbivory Caused Plant Stress Emissions Increases the Negative Radiative Forcing of Aerosols.

Plant stress in a changing climate is predicted to increase plant volatile organic compound (VOC) emissions and thus can affect the formed secondary organic aerosol (SOA) concentrations, which in turn affect the radiative properties of clouds and aerosol. However, global aerosol‐climate models do not usually consider plant stress induced VOCs in their emission schemes. In this study, we modified the monoterpene emission factors in biogenic emission model to simulate biotic stress caused by insect herbivory on needleleaf evergreen boreal and broadleaf deciduous boreal trees and studied the consequent effects on SOA formation, aerosol‐cloud interactions as well as direct radiative effects of formed SOA. Simulations were done altering the fraction of stressed and healthy trees in the latest version of ECHAM‐HAMMOZ (ECHAM6.3‐HAM2.3‐MOZ1.0) global aerosol‐climate model. Our simulations showed that increasing the extent of stress to the aforementioned tree types, substantially increased the SOA burden especially over the areas where these trees are located. This indicates that increased VOC emissions due to increasing stress enhance the SOA formation via oxidation of VOCs to low VOCs. In addition, cloud droplet number concentration at the cloud top increased with increasing extent of biotic stress. This indicates that as SOA formation increases, it further enhances the number of particles acting as cloud condensation nuclei. The increase in SOA formation also decreased both all‐sky and clear‐sky radiative forcing. This was due to a shift in particle size distributions that enhanced aerosol reflecting and scattering of incoming solar radiation.

Species-specific efficiency in PM2.5 removal by urban trees: From leaf measurements to improved modeling estimates

The growing population in cities is causing a deterioration of air quality due to the emission of pollutants, causing serious health impacts. Trees and urban forests can contribute through the interception and removal of air pollutants such as particulate matter (PM). The dry deposition of PM by vegetation depends on air pollutant concentration, meteorological conditions, and specific leaf traits. Several studies explored the ability of different plant species to accumulate PM on leaf structures leading to the development of models to quantify the PM removal. The i-Tree Eco is the most used model to evaluate ecosystem services provided by urban trees. However, fine particulate matter (PM2.5) removal is still calculated with a poorly evaluated function of deposition velocity (which depends on wind speed and leaf area) without differentiating between tree species. Therefore, we present an improvement of the standard model calculation introducing a leaf trait index to distinguish the species effect on PM net removal. We also compared model results with measurements of deposited leaf PM by vacuum filtration. The index includes the effect of morphological and functional leaf characteristics of tree species using four parameters: leaf water storage, deposition velocity, resuspension rate and leaf washing capacity. Leaves of 11 common urban tree species were sampled in representative areas of the city of Ferrara (Italy) and at different times of the year from 2018 to 2021. This includes four deciduous broadleaf trees (Tilia cordata, Platanus acerifolia, Acer platanoides, Celtis australis), three evergreen broadleaf trees (Quercus ilex, Magnolia grandiflora, Nerium oleander), and four conifers (Thuja orientalis, Cedrus libani, Pinus pinaster, Picea abies). The results provide significant advancement in assessing PM removal using decision support tools such as models to properly select tree species for future urban tree planting programs aimed at improving air quality.

Using Consensus Land Cover Data to Model Global Invasive Tree Species Distributions.

Invasive tree species threaten ecosystems, natural resources, and managed land worldwide. Land cover has been widely used as an environmental variable for predicting global invasive tree species distributions. Recent studies have shown that consensus land cover data can be an effective tool for species distribution modelling. In this paper, consensus land cover data were used as prediction variables to predict the distribution of the 11 most aggressive invasive tree species globally. We found that consensus land cover data could indeed contribute to modelling the distribution of invasive tree species. According to the contribution rate of land cover to the distribution of invasive tree species, we inferred that the cover classes of open water and evergreen broadleaf trees have strong explanatory power regarding the distribution of invasive tree species. Under consensus land cover changes, invasive tree species were mainly distributed near equatorial, tropical, and subtropical areas. In order to limit the damage caused by invasive tree species to global biodiversity, human life, safety, and the economy, strong measures must be implemented to prevent the further expansion of invasive tree species. We suggest the use of consensus land cover data to model global invasive tree species distributions, as this approach has strong potential to enhance the performance of species distribution modelling. Our study provides new insights into the risk assessment and management of invasive tree species globally.