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Amid urbanization, studying leaf functional traits of woody plants in urban environments is essential for understanding how urban green spaces function and how they can be effectively managed sustainably. In this study, we investigated the effects of different growing conditions on the morpho-physiological traits of Populus laurifolia and Ulmus pumila across five contrasting urban sites. The leaf area (LA), leaf length (LL), leaf width (LW), leaf biomass (LB), specific leaf area (SLA), leaf chlorophyll concentration, chlorophyll fluorescence parameters, leaf water potential at predawn (Ψpd) and midday (Ψmd), leaf performance index (PIabs), and phenotypic plasticity index (PPI) were compared across five contrasting urban sites. The soil chemical and physical properties were also compared between sites. There were significant differences in soil physicochemical characteristics between sites. We found significant effects of site on most of the morpho-physiological traits measured, except for Ψmd. The leaf chlorophyll concentration of P. laurifolia and U. pumila varied significantly between sites. The Ψpd was significantly different between years and sites. In U. pumila, the mean PPI for morphological traits (0.20) was lower than that for physiological traits (0.21). In conclusion, we revealed significant variations in the morpho-physiological traits of P. laurifolia and U. pumila across the five urban sites. Hence, long-term, large-scale studies are recommended to examine how diverse species respond to different urban growing conditions and to include other ecologically important plant traits for a better understanding of urban trees in a changing environment. [ABSTRACT FROM AUTHOR]

Bilberry (Vaccinium myrtillus L.) expansion in subalpine and alpine ecosystems is increasing due to climate change and reduced land management. This review examines bilberry traits, environmental responses, and ecosystem impacts. As a stress-tolerant chamaephyte, bilberry thrives in acidic, nutrient-poor soils across various habitats. It propagates effectively through rhizomes and demonstrates a phalanx growth form. Bilberry's growth and distribution are influenced by elevation, soil structure, pH, water availability, and nitrogen content. Mycorrhizal associations play a crucial role in nutrient uptake. The species modifies the microclimate, facilitates litter accumulation, and influences soil microbial communities, affecting nutrient turnover and biodiversity. Bilberry shows moderate tolerance to herbivory and frost, with the ability to recover through rapid emergence of new ramets. However, severe or repeated disturbances can significantly impact its abundance and reproductive success. Climate warming and atmospheric nitrogen deposition have accelerated bilberry growth in treeline ecotones. The management of bilberry expansion requires a nuanced approach, considering its resilience, historical land-use changes, and environmental factors. The goal should be to limit, not eliminate, bilberry, as it is a natural part of subalpine communities. Long-term comparative monitoring and experimental manipulation are necessary for effective management strategies. [ABSTRACT FROM AUTHOR]

Plastic traits are argued to favor the establishment of invasive alien plants and to evolve during the invasion process, so that invasions may be favored by both plasticity and evolutionary changes in plasticity. Despite this aspect being pivotal to understanding invasion processes, no information is available about the effect of residence time on the evolution of phenotypic plasticity of aliens to produce locally adapted phenotypes. Therefore, we aimed to evaluate changes in the morpho-functional traits of the invasive alien Ambrosia trifida L. over time. Specifically, we grew A. trifida plants under laboratory (at different temperatures: 10 °C, 20 °C and 25 °C) and field conditions by using seeds collected from 2011 to 2020 from an Eastern European population. Data about seedling emergence, vegetative (laboratory and field) and reproductive (field) traits were collected, e.g., maximum plant height (cm), total dry biomass (g), number of flowers (n) and number of new seeds (n). Analysis of variance (ANOVA), linear regressions and a plasticity index were applied to assess differences in plant performances when grown from seeds of different ages. An auto-regressive integrated moving average (ARIMA) model was applied to predict future trends of some key plant traits (maximum height, total dry biomass and number of new seeds). Overall, the time of seedling emergence was not statistically different among seeds of different age, and regression analyses exhibited a positive relationship between residence time (seed age) and vegetative and reproductive parameters of A. trifida. Only male flower production exhibited a negative trend over time. At all temperatures (especially at 25 °C), the vegetative parameters increased with the decrease in residence time. The plasticity index of the measured traits tended to decrease over time for most traits both in the field and in the laboratory trials. The ARIMA model predicted that plant traits will continue to increase in size over time by 2030, suggesting further plastic adaptation of A. trifida. The results highlighted that residence time influences the evolution of phenotypic plasticity of A. trifida, which has strengthened its adaptability to the new conditions over a decade, also demonstrating a great adaptive and invasion potential for the future. [ABSTRACT FROM AUTHOR]

Maize northern leaf blight (MNLB), characterized by a bottom-up progression, is a prevalent and damaging disease affecting maize growth. Early monitoring is crucial for timely interventions, thus mitigating yield losses. Hyperspectral remote sensing technology is an effective means of early crop disease monitoring. However, traditional single-angle vertical hyperspectral remote sensing methods face challenges in monitoring early MNLB in the lower part of maize canopy due to obstruction by upper canopy leaves. Therefore, we propose a multiangle hyperspectral remote sensing method for early MNLB monitoring. From multiangle hyperspectral data (−60° to 60°), we extracted and selected vegetation indices (VIs) and plant traits (PTs) that show significant differences between healthy and diseased maize samples. Our findings indicate that besides structural PTs (LAI and FIDF), other PTs like Cab, Car, Anth, Cw, Cp, and CBC show strong disease discrimination capabilities. Using these selected features, we developed a disease monitoring model with the random forest (RF) algorithm, integrating VIs and PTs (PTVI-RF). The results showed that PTVI-RF outperformed models based solely on VIs or PTs. For instance, the overall accuracy (OA) of the PTVI-RF model at 0° was 80%, which was 4% and 6% higher than models relying solely on VIs and PTs, respectively. Additionally, we explored the impact of viewing angles on model accuracy. The results show that compared to the accuracy at the nadir angle (0°), higher accuracy is obtained at smaller off-nadir angles (±10° to ±30°), while lower accuracy is obtained at larger angles (±40° to ±60°). Specifically, the OA of the PTVI-RF model ranges from 80% to 88% and the Kappa ranges from 0.6 to 0.76 at ±10° to ±30°, with the highest accuracy at −10° (OA = 88%, Kappa = 0.76). In contrast, the OA ranges from 72% to 80% and the Kappa ranges from 0.44 to 0.6 at ±40° to ±60°. In conclusion, this research demonstrates that PTVI-RF, constructed by fusing VIs and PTs extracted from multiangle hyperspectral data, can effectively monitor early MNLB. This provides a basis for the early prevention and control of MNLB and offers a valuable reference for early monitoring crop diseases with similar bottom-up progression. [ABSTRACT FROM AUTHOR]

Until the late 20th century, the idea of identifying wildfires in deep time was not generally accepted. One of the basic problems was the fact that charcoal-like wood fragments, so often found in sedimentary rocks and in coals, were termed fusain and, in addition, many researchers could not envision wildfires in peat-forming systems. The advent of Scanning Electron Microscopy and studies on modern charcoals and fossil fusains demonstrated beyond doubt that wildfire residues may be recognized in rocks dating back to at least 350 million years. Increasing numbers of studies on modern and fossil charcoal assemblages from the 1970s through the 1990s established the potential importance of wildfires in the fossil record, using Carboniferous examples in particular. Since the 1990s, extensive progress has been made in understanding modern wildfires and their byproducts. New techniques to study ancient charcoals have allowed considerable progress to be made to integrate modern and ancient fire studies, both before and after the evolution of mankind. Four important developments have made a reassessment of Carboniferous wildfires necessary: the recognition of the role of atmospheric oxygen in controlling the occurrence of wildfire; the development of new microscopical techniques allowing more detailed anatomical data to be obtained from charcoal; the integration of molecular studies with the evolution of fire traits; and new developments in or understanding of post-fire erosion/deposition systems. [ABSTRACT FROM AUTHOR]

Lindernia dubia (L.) Pennell is a species with invasive behavior outside of its native range of distribution (America), linked mainly to aquatic habitats. This annual species has been acknowledged as a weed in rice paddies in Europe and Asia. Due to the impacts of this invasive plant, some authors have even listed this species as a global invader. The present work focused on spontaneous plant species occurring in seedlings of Typha domingensis Pers. grown in central Spain for the establishment of constructed wetlands. Weed inventory revealed the presence of L. dubia as a dominant spontaneous species in this crop environment. A suite of mesocosm experiments were designed to study the population density of L. dubia versus that of the other dominant plant species, and to determine traits associated with its weedy potential. The results showed that L. dubia presents competitive attributes such as morphological variability, early flowering, long seeding time, short growth cycle, small and light seeds and a high seed production and germination rate (25 °C), meaning a high reproductive capacity in a cycle of about three months for plant growth in non-limiting conditions. The data obtained from this work provide a basis for understanding the weedy potential of L. dubia, and for management decisions of a potentially invasive species, which has been little investigated in Europe [ABSTRACT FROM AUTHOR]

Carbon stocks provide information that is essential for analyzing the role of forests in global climate mitigation, yet they are highly vulnerable to wildfires in Mediterranean ecosystems. These carbon stocks' exposure to fire is usually estimated from specific allometric equations relating tree height and diameter to the overall amount of aboveground carbon storage. Assessments of vulnerability to fire additionally allow for specific fire resistance (bark thickness, crown basal height) and post-fire recovery traits (cone mass for regeneration, and fine branches or leaves mass for flammability) to be accounted for. These traits are usually considered as static, and their temporal dynamic is rarely assessed, thus preventing a full assessment of carbon stocks' vulnerability and subsequent cascading effects. This study aimed to measure the pools of carbon stocks of individual trees varying between 30 and 96 years old in the Djbel Mansour Aleppo pine (Pinus halepensis) forest in semi-arid central Tunisia in the southern range of its distribution to fit a sigmoid equation of the carbon pools and traits recovery according to age as a vulnerability framework. Allometric equations were then developed to establish the relationships between fire vulnerability traits and dendrometric independent variables (diameter at breast height, height, and live crown length) for further use in regional vulnerability assessments. The total carbon stocks in trees varied from 29.05 Mg C ha−1 to 92.47 Mg C ha−1. The soil organic carbon stock (SOC) at a maximum soil depth of 0–40 cm varied from 31.67 Mg C ha−1 to 115.67 Mg C ha−1 at a soil depth of 0–70 cm. We could identify an increasing resistance related to increasing bark thickness and basal crown height with age, and enhanced regeneration capacity after 25 years of age with increasing cone biomass, converging toward increasing vulnerability and potential cascading effects under shorter interval fires. These results should be considered for rigorous forest carbon sequestration assessment under increasing fire hazards due to climate and social changes in the region. [ABSTRACT FROM AUTHOR]

Biodiversity and sustainable development in Sub-Saharan Africa (SSA) are considerably impacted by invasive alien plants (IAPs). Increasing plant invasions in SSA threaten agricultural productivity, biodiversity conservation, and other socioeconomic activities, which in turn put the United Nations Sustainable Development Goals (SDGs) in peril. In order to effectively combat IAPs, understanding their functional traits (morphological, physiological, and phenological traits) and integrating them into remote sensing (RS) is vital. While functional traits influence IAPs' fitness to invade and establish in a new geographical range, RS aids in studying them remotely, delineating and mapping them, and predicting their potential invasions. The information on this study topic was gathered by reviewing various existing studies published between 2000 and 2024. Based on this review, it was deduced that the majority of IAPs are fast-growing (or acquisitive), with a shorter leaf lifespan, bigger leaves, and higher plant height, ultimately resulting in a higher resource acquisition ability. We established further that in SSA, there are limited studies on IAP functional traits and their integration in RS. Many studies conducted in the region focus mostly on IAP distribution. Evidence from prior studies revealed that functional trait remote sensing (FTRS)-based research not only improves detection and mapping but also predicts whether a certain alien plant can become invasive or expand its distribution range. Thus, using the FTRS approach could help IAP management in SSA, ultimately achieving the SDGs. Our review discusses IAP implications in SSA (e.g., Angola, Tanzania, Benin, Kenya, Uganda, Rwanda, Zambia, Burundi, Zimbabwe, Botswana, Malawi, etc.) and for the achievement of SDGs; functional traits and their impact on alien invasions; and the importance of incorporating functional traits into RS. [ABSTRACT FROM AUTHOR]

The reproduction of rare and endangered plant species is one of the most important factors determining the stability and survival of their populations, and knowledge of the barriers to successful reproduction is essential for species conservation. Habitat loss and slow reproduction due to low fruit set are usually considered the main threats to Cephalanthera longifolia and C. rubra (Orchidaceae). The aim of this study was to analyse the natural fruit set of these species during three consecutive years in Lithuania in the northern part of the temperate zone of Europe. Six populations of C. longifolia and three populations of C. rubra were studied each year from 2021 to 2023. During the study period, 49.3% to 54.4% of C. longifolia and 40.0% to 54.3% of C. rubra individuals produced no fruit. Over the three-year period, fruit set in individual populations of C. longifolia ranged from 5.2% to 19.5%, whereas fruit set in populations of C. rubra ranged from 4.1% to 18.8%. Significant weak or moderate correlations were found between plant height, inflorescence length and the number of flowers in the inflorescence and fruit set of both species. Flower position in the inflorescence had a significant effect on fruit set in both species, and the fruit set rate of lower flowers was higher than that of upper flowers. Significant but weak correlations were found between the fruit set and most of the environmental factors analysed. The results of this study suggest that the fruit set of C. longifolia and C. rubra is dependent on insect pollination of the flowers, which in turn is affected by habitat conditions. [ABSTRACT FROM AUTHOR]

This study investigates the effects of forest aging on ectomycorrhizal (EcM) fungal community and foraging behavior and their interactions with plant–soil attributes. We explored EcM fungal communities and hyphal exploration types via rDNA sequencing and investigated their associations with plant–soil traits by comparing younger (~120 years) and older (~250 years) temperate forest stands in Northeast China. The results revealed increases in the EcM fungal richness and abundance with forest aging, paralleled by plant–soil feedback shifting from explorative to conservative nutrient use strategies. In the younger stands, Tomentella species were prevalent and showed positive correlations with nutrient availability in both the soil and leaves, alongside rapid increases in woody productivity. However, the older stands were marked by the dominance of the genera Inocybe, Hymenogaster, and Otidea which were significantly and positively correlated with soil nutrient contents and plant structural attributes such as the community-weighted mean height and standing biomass. Notably, the ratios of longer-to-shorter distance EcM fungal exploration types tended to decrease along with forest aging. Our findings underscore the integral role of EcM fungi in the aging processes of temperate forests, highlighting the EcM symbiont-mediated mechanisms adapting to nutrient scarcity and promoting sustainability in plant–soil consortia. [ABSTRACT FROM AUTHOR]

American ginseng (Panax quinquefolius) is widely used due to its medicinal properties. Ontario is a major producer of cultivated American ginseng, where seeds were originally collected from the wild without any subsequent scientific selection, and thus the crop is potentially very diverse. A collection of 162 American ginseng plants was harvested from a small area in a commercial garden and phenotyped for morphological traits, such as root grade, stem length, and fresh and dry weights of roots, leaves, stems, and seeds. All of the traits showed a range of values, and correlations were observed between root and stem weights, root dry weight and leaf dry weight, as well as root and leaf fresh weights. The plants were also genotyped using single nucleotide polymorphisms (SNPs) at the PW16 locus. SNP analysis revealed 22 groups based on sequence relatedness with some groups showing no SNPs and others being more diverse. The SNP groups correlated with significant differences in some traits, such as stem length and leaf weight. This study provides insights into the genetic and phenotypic diversity of cultivated American ginseng grown under similar environmental conditions, and the relationship between different phenotypes, as well as genotype and phenotype, will aid in future selection programs to develop American ginseng cultivars with desirable agronomic traits. [ABSTRACT FROM AUTHOR]

Street trees provide ecosystem services such as heat mitigation, improved community well-being, and biodiversity conservation. At the wildland–urban interface (WUI), high-flammability street trees also provide a conflicting ecosystem disservice, heightening risks of wildfire spread into urban areas. We addressed this service–disservice conflict by assessing shoot flammability patterns in 10 street tree species, to identify low-flammability species that can potentially mitigate wildfire risks at the WUI. We found significant differences among species in flammability attributes including time-to-flame (TTF), flame duration (FD), number of flaming events (nF), and flame temperature (FT), and identified low-flammability species for each attribute. Overall, species' rankings from least to most flammable differed considerably across the four attributes. For example, native water gum (Tristaniopsis laurina) had the slowest TTF, but had the longest FD. Among nine shoot traits, we found that high leafing intensity was the most frequent trait correlated with flammability. In particular, high leafing intensity was significantly related to fast TTF and high FT. Lack of coordination among flammability attributes suggests that, in general, selection of low-flammability street tree species should consider how each flammability attribute differentially contributes to wildfire spread risk. Nonetheless, native Tuckeroo (Cupaniopsis anacardioides) emerged as a potential candidate for further exploration as a low-flammability street tree as it had comparatively long TTF, short FD, and low nF. We found no consistent evidence that exotic species were less flammable than native species, and suggest that native trees be the focus of further research to identify low-flammability street trees. [ABSTRACT FROM AUTHOR]

The efficiency of hyper- and multispectral imaging (HSI and MSI) has gained considerable attention in research on plant phenotyping. This is due to their ease of use while being considered a nondestructive technology. Unlike current point-scanned spectroscopy, both HSI and MSI extract spatial and spectral information while covering a wide range of a plant body. Moreover, it is necessary to equip the extracted information with multivariate calibration techniques, followed by model evaluation. To date, the application of HSI and MSI for monitoring plant growth under a controlled environment is emerging and showing a good trend. Our systematic literature review discusses spectroscopy imaging techniques and their chemometric approaches as a sustainable sensor technology to detect plant traits. In conclusion, we also explore the possibility of carrying out HSI and MSI during plant trait analysis. [ABSTRACT FROM AUTHOR]

The analysis of plant trait composition has raised significant interest among freshwater ecologists as a complementary approach for assessing the effects of environmental change on ecosystem functions. In this study, we investigated patterns of functional traits of the aquatic macrophyte assemblages of 74 lotic ecosystems of Greece, and we identified associations between species traits and environmental variables (hydromorphological and physicochemical parameters) through testing the hypothesis that the environmental features determine the spatial structure of traits. We allocated 12 traits to a total of 39 hydrophyte species, and we conducted RLQ and fourth corner analysis to explore relationships between species, trait composition, and environmental gradients. Based on the results of the RLQ, a hierarchical cluster analysis was conducted to identify groups of plants that share common trait characteristics. Plants were discriminated into five discrete groups based mostly on their life form (e.g., free-floating, rooted submerged etc.) and their ecological preference for nitrogen levels. Hydromorphological parameters had a higher contribution than physicochemical variables in explaining the total variance of the trait data, with water abstraction, channel substrate, and hydrologic alteration being the most important. Our analysis did not reveal significant bivariate relationships between single traits and environmental parameters, although the five groups of macrophyte assemblages appeared to associate with certain environmental gradients. Free-floating and emergent plants were related to higher concentrations of nutrients, whereas rooted submerged plants were related to higher oxygen concentration and increased pH. In addition, free-floating plants were highly associated with metrics of hydromorphological change. Our findings showed clear discrimination of macrophytes based on their functional composition and association of traits with environmental gradients. Thus, further research could explore whether macrophyte functional groups can serve as indicators of environmental change and the overall ecosystem health. [ABSTRACT FROM AUTHOR]

Human disturbance, such as trampling, is an integral component of global change, yet we lack a comprehensive understanding of its effects on alpine ecosystems. Many alpine systems are seeing a rapid increase in recreation and in understudied regions, such as the Coast Mountains of British Columbia, yet disturbance impacts on alpine plants remain unclear. We surveyed disturbed (trail-side) and undisturbed (off-trail) transects along elevational gradients of popular hiking trails in the T'ak't'ak'múy'in tl'a In'inyáxa7n region (Garibaldi Provincial Park), Canada, focusing on dominant shrubs (Phyllodoce empetriformis, Cassiope mertensiana, Vaccinium ovalifolium) and graminoids (Carex spp). We used a hierarchical Bayesian framework to test for disturbance by elevation effects on total plant percent cover, maximum plant height and diameter (growth proxies), and buds, flowers, and fruits (reproduction proxies). We found that trampling reduces plant cover and impacts all species, but that effects vary by species and trait, and disturbance effects only vary with elevation for one species' trait. Growth traits are more sensitive to trampling than reproductive traits, which may lead to differential impacts on population persistence and species-level fitness outcomes. Our study highlights that disturbance responses are species-specific, and this knowledge can help land managers minimize disturbance impacts on sensitive vegetation types. [ABSTRACT FROM AUTHOR]

The responses of dominant species to plant–soil feedback (PSF) are well established; however, the changes in the PSF of companion species remain unclear. This study aims to assess the direction and intensity of PSF, determine the main factors influencing it, and interpret the ecological significance of PSF in companion species within the context of grassland community succession. Three typical companion species, namely Artemisia sacrorum, Artemisia capillaris, and Artemisia giraldii, were planted in soils at three grassland community succession stages (early, middle, and late) on the Loess Plateau. Our results indicate that during both plant growth periods, the shoot biomass of A. sacrorum, A. capillaris, and A. giraldii in early- and late-stage soils was higher than that in the middle-stage soil, suggesting consistent growth of the three companion species during the two growth periods. However, plant growth simultaneously led to a reduction in soil nutrient content and microbial biomass, resulting in an overall decrease in the biomass of the three species, indicating a negative PSF effect in companion species. In conclusion, the negative PSF observed in all three associated species explains the temporary dominance of companion species during succession. This study enhances our understanding of the mechanisms driving PSF in community succession. [ABSTRACT FROM AUTHOR]

Ensuring food security requires the publication of data in a timely manner, but often this information is not properly documented and evaluated. Therefore, the combination of databases from multiple sources is a common practice to curate the data and corroborate the results; however, this also results in incomplete cases. These tasks are often labor-intensive since they require a case-wise review to obtain the requested and completed information. To address these problems, an approach based on Selenium web-scraping software and the multiple imputation denoising autoencoders (MIDAS) algorithm is presented for a case study in Ecuador. The objective was to produce a multidimensional database, free of data gaps, with 72 species of food crops based on the data from 3 different open data web databases. This methodology resulted in an analysis-ready dataset with 43 parameters describing plant traits, nutritional composition, and planted areas of food crops, whose imputed data obtained an R-square of 0.84 for a control numerical parameter selected for validation. This enriched dataset was later clustered with K-means to report unprecedented insights into food crops cultivated in Ecuador. The methodology is useful for users who need to collect and curate data from different sources in a semi-automatic fashion. [ABSTRACT FROM AUTHOR]

Plant phenotyping studies the complex characteristics of plants, with the aim of evaluating and assessing their condition and finding better exemplars. Recently, a new branch emerged in the phenotyping field, namely, high-throughput phenotyping (HTP). Specifically, HTP exploits modern data sampling techniques to gather a high amount of data that can be used to improve the effectiveness of phenotyping. Hence, HTP combines the knowledge derived from the phenotyping domain with computer science, engineering, and data analysis techniques. In this scenario, machine learning (ML) and deep learning (DL) algorithms have been successfully integrated with noninvasive imaging techniques, playing a key role in automation, standardization, and quantitative data analysis. This study aims to systematically review two main areas of interest for HTP: hardware and software. For each of these areas, two influential factors were identified: for hardware, platforms and sensing equipment were analyzed; for software, the focus was on algorithms and new trends. The study was conducted following the PRISMA protocol, which allowed the refinement of the research on a wide selection of papers by extracting a meaningful dataset of 32 articles of interest. The analysis highlighted the diffusion of ground platforms, which were used in about 47% of reviewed methods, and RGB sensors, mainly due to their competitive costs, high compatibility, and versatility. Furthermore, DL-based algorithms accounted for the larger share (about 69%) of reviewed approaches, mainly due to their effectiveness and the focus posed by the scientific community over the last few years. Future research will focus on improving DL models to better handle hardware-generated data. The final aim is to create integrated, user-friendly, and scalable tools that can be directly deployed and used on the field to improve the overall crop yield. [ABSTRACT FROM AUTHOR]

Solanum elaeagnifolium, one of the world's most widespread invasive weeds, thrives in the regions of Tunisia with a semi-arid climate. An enhanced understanding of its biological traits could be useful for its management. For this purpose, S. elaeagnifolium vegetative propagation, flowering, fruiting, and spread patterns were assessed under semi-arid environmental conditions at Chott Mariem (Tunisia) over three years (2013–2015). Our results revealed that S. elaeagnifolium showed an active vegetative growth phase during the spring (March–May). Thereafter, the plant stopped its vegetative growth in June–August in favor of flowering and fruiting. The vegetative growth resumed during September–October and declined in November, announcing its dormant period. Thanks to its vigorous rhizomatous system, S. elaeagnifolium was able to emit offshoots within a radius of 1.5 m from parent shoots by 30 months after its establishment. These findings could inform and improve dedicated management control options for S. elaeagnifolium. Silverleaf nightshade should be controlled before the full-flowering stage in spring and following the first autumnal rainfall to prevent vegetative propagation and fruiting. [ABSTRACT FROM AUTHOR]

Plant life history and functional characteristics play an important role in determining the invasive potential of plant species and have implications for management approaches. We studied the distribution of 24 alien plant taxa in a protected area in relation to different land-uses by applying ordination analyses and generalized linear models. Taxa richness is best explained by the presence of built-up areas, followed by residential areas, marshlands, and agricultural lands with semi-natural formations. The diversity of land-use within the grid cell proved to be an important explanatory factor, being the only significant variable explaining the richness of wood perennials and vines. The richness of annual herbs and seed-dispersed taxa is explained by a similar set of variables, with the exception of residential areas. The richness of invasive species is explained only by agricultural land and the diversity of land-use. The richness of taxa with predominant vegetative dispersal is best explained by built-up, marshland, and seminatural areas along with land-use diversity. When we consider only the presence of plant groups within grid cells, the results are similar. The results of similar studies may provide an important tool for defining sustainable practices and overall conservation management in protected areas. [ABSTRACT FROM AUTHOR]

Seed traits (ST) influence seedling establishment, population dynamics, community composition and ecosystem function and reflect the adaptability of plants and the environmental conditions they experienced. There has been a historical and global accumulation of studies on ST, but with few pertaining to visual and quantitative analyses. To understand the trends in the field of ST research in the past 30 years, we conducted a bibliometric analysis based on the Science Citation Index-Expanded (SCI-E) database. The analysis provided annual publications, time trends for keywords, the most productive journals, authors, institutions and countries, and a comprehensive overview of the ST field. Our results showed that in the past 30 years, the number of publications in ST research has increased at an average annual growth rate of 9.1%, while the average number of citations per paper per year showed a rapid increase–slow increase–decrease trend. Keyword analysis showed that "germination" was the most popular research section. Crop Science ranked first among the top journals and Theoretical and Applied Genetics had greater influence in this area and more citations than other journals. The 10 most productive institutions were mostly located in the United States, China and Australia. Furthermore, the three countries also had the largest number of publications and citations. Our analysis showed that the research interests in ST have evolved from genetics and agricultural science to ecological research over the last thirty years; as more fields embrace ST research, there are opportunities for international and interdisciplinary collaborations, cooperative institutions and new advances in the field. [ABSTRACT FROM AUTHOR]

The stress gradient hypothesis (SGH) states that plant-plant interactions shift from competition to facilitation in increasing stress conditions. In salt marshes, edaphic properties can weaken the application of the SGH by amplifying the intensity of flooding and controlling plant zonation. We identified facilitative and competitive interactions along flooding gradients and tested the role of edaphic properties in exacerbating stress and shaping plant-plant interactions. Morphological traits of two target halophytes (Limonium narbonense and Sarcocornia fruticosa), flooding intensity, soil texture and soil organic C were recorded. The relative plant fitness index was assessed for the two species based on the relative growth in plurispecific rather than monospecific plant communities. Plant fitness increased with increasing stress supporting the SGH. L. narbonense showed larger fitness in plurispecific stands whereas S. fruticosa performed better in conspecific stands. Significant intra- or interspecific interactions were observed along the stress gradient defined by the combination of flooding and clay content in soil. When considering the limited soil organic C as stressor, soil properties were more important than flooding in defining plant-plant interactions. We highlight the need for future improvements of the SGH approach by including edaphic stressors in the model and their possible interactions with the main abiotic drivers of zonation. [ABSTRACT FROM AUTHOR]

Dissolved organic carbon (DOC) is one of the most important components in the global carbon cycle, which is largely influenced by climate and plant traits. Although previous studies have examined the impacts of climatic factors (e.g., mean annual temperature (MAT) and precipitation (MAP)) or plant traits (e.g., leaf area index, leaf nitrogen) on DOC, the relative importance of climate and plant traits on DOC flux remains unclear on a global scale. In this study, we compiled 153 pairs of DOC observational data from 84 forest sites to explore the relative importance of climate and plant traits on DOC flux with a linear mixed model, variance partitioning, and random forest approaches. Our results showed that DOC fluxes from throughfall and the litter layer were higher in broadleaved forests than those in coniferous forests. Throughfall-DOC flux increased significantly with MAT and MAP in coniferous forests, but that from the litter layer showed no significant correlations with climate factors. In broadleaved forests, throughfall-DOC flux increased with potential evapotranspiration (PET), while that from the litter layer was positively correlated with MAT. Meanwhile, throughfall-DOC flux had negative relationships with specific leaf area (SLA), leaf nitrogen content (LN), and leaf phosphorus content (LP) in broadleaved forests, but it showed a positive correlation with SLA in coniferous forests. Litter-layer-DOC flux increased with LN in broadleaved forests, but this correlation was the opposite in coniferous forests. Using the variance partitioning approach, plant traits contributed to 29.0% and 76.4% of the variation of DOC from throughfall and litter layer, respectively, whereas climate only explained 19.1% and 8.3%, respectively. These results indicate that there is a more important contribution by plant traits than by climate in driving the spatial variability of global forest DOC flux, which may help enhance forest management as a terrestrial carbon sink in the future. Our findings suggest the necessity of incorporating plant traits into land surface models for improving predictions regarding the forest carbon cycle. [ABSTRACT FROM AUTHOR]

The herb layer of temperate forests contributes to long-term forest ecosystem functioning and provisioning of ecosystem services. Therefore, a thorough understanding of its dynamics in the face of environmental changes is essential. This paper focuses on the species and functional diversity of the herb layer of riparian forests to verify how these two community components changed over time and under strict protection. The understory vegetation was surveyed on 42 semi-permanent plots in three time periods between 1960 and 2020. The overall pattern in vegetation changes that related to species richness and diversity, functional structure, and habitat conditions was analyzed using ordination and permutation techniques. We found significant changes in species composition and the functional structure of herbaceous vegetation over the last six decades. Forests were enriched with nutrient-demanding and alien species. A significant increase in functional diversity and the proportion of species with high SLA and canopy height was also observed, whereas changes in habitat conditions were insignificant. The observed trends indicate that the strict protection of forest communities within small and isolated reserves does not fully protect their species composition. Forest reserves should be surrounded by unmanaged forests and spatially connected to allow species mobility. [ABSTRACT FROM AUTHOR]

The degree of completeness of large-scale floristic inventories is often difficult to judge. We compared prior vascular plant species inventories of the Mediterranean island of Limnos (North Aegean, Greece) with 231 recent records from 2016–2021. Together with the recent records, the known number of vascular plant species on the island is 960 native taxa, 63 established neophytes, and 27 species of as yet casual status for a total of 1050 taxa. We looked at a number of traits (plant family, size, flower color, perceptibility, habitat, reproduction period, rarity, and status) to investigate whether they were overrepresented in the dataset of the newly found taxa. Overrepresentation was found in some plant families (e.g., Poaceae and Chenopodiaceae) and for traits such as hydrophytic life form, unobtrusive flower color, coastal as well as agricultural and ruderal habitats, and late (summer/autumn) reproduction period. Apart from the well-known fact of esthetic bias, we found evidence for ecological and perceptibility biases. Plant species inventories based on prior piecemeal collated data should focus on regionally specific species groups and underrepresented and rare habitats. [ABSTRACT FROM AUTHOR]

Deliblato Sands is the single largest expanse of sand in Europe. It is the most fire-prone area of Serbia due to the absence of surface water, sandy soils, specific microclimate conditions, and vegetation composition. Post-fire regeneration is a long-term process that includes many aspects of vegetation regrowth and habitat recovery. In the third year following one of the disastrous fires, the growth dynamics of two geophyte species in unburned and burned sites were studied. During the growing season, burned and unburned populations of Crocus reticulatus Steven ex Adam and Iris pumila L. were assessed for growth parameters (biomass production, specific leaf area, leaf area index) and leaf-level ecophysiological traits (photosystem II efficiency, chlorophyll amount, relative water content). Species acclimated differently to changed abiotic and biotic site conditions after the fire event. C. reticulatus burned and unburned populations differed significantly in terms of flowering phenology and ecophysiological traits, whereas I. pumila burned and unburned populations differed significantly in terms of growth parameters. The findings support the assertion that geophytes are generally well adapted to environmental disturbances. Species, however, responded differently to fire-induced changes in the physicochemical and biotic environment, depending on their ecological requirements and adaptive capacity. [ABSTRACT FROM AUTHOR]

Purposefully planted trees and shrubs can provide multiple benefits when appropriately planned and designed. Tools to help select species that will function more effectively than other species for ecosystem services, production, and aesthetic purposes are generally lacking. To address this challenge, we developed an interactive plant selection tool entitled Tree Advisor that rates woody species for a wide range of different purposes based on plant attributes. In this prototype decision support tool, 90 species of trees and shrubs are rated for 14 different purposes in the northern and central Great Plains region of the United States. A rating algorithm was developed based on the scientific literature regarding plant functions and related attributes that determine relative performance of a species for each purpose. User input and best practices for developing effective decision support tools informed the tool development process. Based on user feedback, the tool supports multifunctional planning and enables a user to quickly develop a short list of the better species to use which can then be refined by the user based on suitability under local site conditions, commercial availability, and availability of locally adapted cultivars and hybrids. This tool development approach can serve as a model for producing multifunctional woody plant selection tools for other ecoregions. [ABSTRACT FROM AUTHOR]

Green plants provide the foundation for the structure, function, and interactions among organisms in both tropical and temperate zones. To date, many investigations have revealed patterns and mechanisms that generate plant diversity at various scales and fromdiverse ecological perspectives. However, in the era of climate change, anthropogenic disturbance, and rapid urbanization, new insights are needed to understand how plant species in these forest habitats are changing and adapting. Here, we recognize four themes that link studies from Asia and Europe presented in this Special Issue: (1) genetic analyses of diverse plant species; (2) above- and below-ground forest biodiversity; (3) trait expression and biological mechanisms; and (4) interactions of woody plants within a changing environment. These investigations enlarge our understanding of the origins of diversity, trait variation and heritability, and plant–environment interactions from diverse perspectives. [ABSTRACT FROM AUTHOR]

This study aimed to determine the impact of invasive Rosa rugosa Thunb. on the plant communities of the Baltic coastal dunes. The study was carried out in 22 sites scattered along the Hel Peninsula (Poland). Each site consisted of a pair of plots: a plot with the invader vegetation and an adjacent plot with the resident vegetation (control plot). For each plot, botanical data (the abundance of individual species, total species richness and the richness of species belonging to different functional groups) were collected and basic soil parameters were measured. According to the analysis of the control plot species composition, the study sites can be divided into two groups, including the plant communities characteristic of the yellow dunes (Elymo-Ammophiletum arenariae association, EA; N = 11 sites) and those characteristic of the grey dunes (Helichryso-Jasionetum litoralis association, HJ; N = 11 sites). R. rugosa influenced these two communities differently. In the EA sites, it displaced many species, leading to a significant decrease in the species richness. In the HJ sites, it caused a shift in the species composition; although it outcompeted some species (e.g., zoochores), it also created conditions for the existence of others (e.g., graminoids, a plant group that, interestingly, was negatively affected by the invader in the EA sites). Changes in the plant communities probably resulted not only from the direct impacts of R. rugosa on the plants (by shading and occupying space) but also from invader-induced soil alternations (an increase in the organic layer thickness and an increase in pH and the content of some nutrients). [ABSTRACT FROM AUTHOR]

Estimating plant traits in herbaceous plant assemblages from spectral reflectance data requires aggregation of small scale trait variations to a canopy mean value that is ecologically meaningful and corresponds to the trait content that affects the canopy spectral signal. We investigated estimation capacities of plant traits in a herbaceous setting and how different trait-aggregation methods influence estimation accuracies. Canopy reflectance of 40 herbaceous plant assemblages was measured in situ and biomass was analysed for N, P and C concentration, chlorophyll, lignin, phenol, tannin and specific water concentration, expressed on a mass basis (mg·g-1). Using Specific Leaf Area (SLA) and Leaf Area Index (LAI), traits were aggregated to two additional expressions: mass per leaf surface (mg·m-2) and mass per canopy surface (mg·m-2). All traits were related to reflectance using partial least squares regression. Accuracy of trait estimation varied between traits but was mainly influenced by the trait expression. Chlorophyll and traits expressed on canopy surface were least accurately estimated. Results are attributed to damping or enhancement of the trait signal upon conversion from mass based trait values to leaf and canopy surface expressions. A priori determination of the most appropriate trait expression is viable by considering plant growing strategies. [ABSTRACT FROM AUTHOR]

An understanding of the climate conditions governing spatial variation in the reproductive performance of plants can provide important information about the factors characterizing plant community structure, especially in the context of climate change. This study focuses on the effect of climate on the sexual reproductive output of Dactylis glomerata L., a perennial grass species widely distributed throughout temperate regions. An indirect space-for-time substitution procedure was used. Sixty mountain populations of the same target species were surveyed along an elevation gradient, and then, a relevant climate model was used to infer a potential response to climate change over time. Within each population, information on the number of stems, seed number and seed mass were collected. Resource investment in reproduction (RIR) was quantified as seed number × seed mass. A clear variation was found in the reproductive performance of D. glomerata along the elevational gradient: RIR improved with increasing temperature. The best model included only one term: the maximum temperature of the warmest month. This study demonstrates that mountain ecosystems offer particularly good opportunities to study climate effects over relatively short distances and suggests that warming will enhance D. glomerata's reproductive output throughout its elevational range. Furthermore, it can be hypothesized that a potential migration of D. glomerata toward higher altitudes may occur in response to accelerated climate change. [ABSTRACT FROM AUTHOR]

Moving toward more sustainable sources for managing phosphorus (P) nutrition in agroecosystems, organic phosphorus (Po) derived from organic inputs and soil is increasingly considered to complement mineral P fertilizer. However, the dynamics of P added by organic input in soil-plant systems is still poorly understood and there is currently no clear information on how the Po composition of these amendments determines P availability through interactions with the soil microbiome and root traits. Here, we review the main mechanisms of rhizosphere microbiome and root traits governing the dynamics of organic input/soil-derived Po pools in the soil-plant system. We discuss the extent to which the major forms of Po derived from organic input/soil can be used by plants and how this could be improved to provide efficient utilization of organic inputs as potential P sources. We provide new insights into how a better understanding of the interactions between Po forms, root traits, and rhizosphere microbiomes can help better manage P fertilization, and discuss recent advances in the mobilization and recovery of Po from organic inputs. We then develop proposed strategies in agroecology that could be used to improve Po utilization, specifically by better linking plant traits and Po forms, and developing new cropping systems allowing more efficient Po recycling. [ABSTRACT FROM AUTHOR]

Studies on plant growth and trait variation along environmental gradients can provide important information for identifying drivers of plant invasions and for deriving management strategies. We used seeds of the annual plant invader Ambrosia artemisiifolia L. (common ragweed) collected from an agricultural site in Northern Italy (226 m. a.s.l; Mean Annual Air Temperature: 12.9 °C; precipitations: 930 mm) to determine variation in growth trajectories and plant traits when grown along a 1000-m altitudinal gradient in Northern Italy, and under different temperature conditions in the growth chamber (from 14/18 °C to 26/30 °C, night/day), using a non-liner modeling approach. Under field conditions, traits related to plant height (maximum height, stem height, number of internodes) followed a three-parameter logistic curve. In contrast, leaf traits (lateral spread, number of leaves, leaf length and width) followed non-monotonic double-Richards curves that captured the decline patterns evident in the data. Plants grew faster, reaching a higher maximum plant height, and produced more biomass when grown at intermediate elevations. Under laboratory conditions, plants exhibited the same general growth trajectory of field conditions. However, leaf width did not show the recession after the maximum value shown by plants grown in the field, although the growth trajectories of some individuals, particularly those grown at 18 °C, showed a decline at late times. In addition, the plants grown at lower temperatures exhibited the highest value of biomass and preserved reproductive performances (e.g., amount of male inflorescence, pollen weight). From our findings, common ragweed exhibits a high phenotypic plasticity of vegetative and reproductive traits in response to different altitudes and temperature conditions. Under climate warming, this plasticity may facilitate the shift of the species towards higher elevation, but also the in situ resistance and (pre)adaptation of populations currently abundant at low elevations in the invasive European range. Such results may be also relevant for projecting the species management such as the impact by possible biocontrol agents. [ABSTRACT FROM AUTHOR]

Bromus valdivianus Phil. (Bv) is a water stress-tolerant species, but its competitiveness in a diverse pasture may depend on defoliation management and soil moisture levels. This glasshouse study examined the effect of three defoliation frequencies, based on accumulated growing degree days (AGDD) (250, 500, and 1000 AGDD), and two soil water levels (80–85% of field capacity (FC) and 20–25% FC) on Bv growth as monoculture and as a mixture with Lolium perenne L. (Lp). The treatments were applied in a completely randomised block design with four blocks. The above-ground biomass of Bv was lower in the mixture than in the monoculture (p ≤ 0.001). The Bv plants in the mixture defoliated more infrequently (1000 AGDD) showed an increase in root biomass under 20–25% FC compared to 80–85% FC, with no differences measured between soil water levels in the monoculture. Total root length was highest in the mixture with the combination of infrequent defoliation and 20–25% FC. Conversely, frequent defoliation treatments resulted in reduced water-soluble carbohydrate reserves in the tiller bases of plants (p ≤ 0.001), as they allocated assimilates mainly to foliage growth. These results provide evidence that B. valdivianus can increase its competitiveness relative to Lp through the enhancement of the root growth and the energy reserve in the tiller base under drought conditions and infrequent defoliation in a mixture. [ABSTRACT FROM AUTHOR]

Simple Summary: The pepper weevil is an economically important pest that causes major damage to fruits of chili pepper varieties selected for consumption. However, the impact of this pest on wild and ornamental peppers remains unknown. Therefore, we studied the effect of chili domestication on the feeding and oviposition behavior of pepper weevil when exposed to wild chili, ornamental varieties, and varieties used for consumption. More specifically, we examined how changes in fruit and flower size, fruit thickness, spiciness level, and fruit position as a result of the domestication of chili peppers affected their susceptibility to this specialist pepper pest. In addition, we recorded that fruits and flowers from wild and ornamental plants were less susceptible to pepper weevil attacks than those from chili varieties selected for consumption. Our results have important implications for chili pepper breeders and could guide the selection of new resistant varieties against this pest. The pepper weevil, Anthonomus eugenii, Cano (Coleoptera: Curculionidae), is one of the most destructive pests of chili pepper. It causes extensive damage on varieties selected for consumption. However, the occurrence of this pest on wild and ornamental peppers remains unknown. We investigated the consequences of chili domestication on the feeding and oviposition of A. eugenii on fruits and flowers. We used plants of one wild accession, Bird Eye Pepper, five ornamental varieties (Pops Yellow, Black Pearl, Sedona Sun, Chilli Chilli, and Salsa Deep), and two domesticated varieties selected for consumption (Scotch Bonnet and Jalapeño). First, we characterized the plants according to their fruit and flower sizes, pericarp thickness, capsaicin level, fruit position, and flower color. Then, we evaluated the susceptibility of fruits and flowers to A. eugenii. Overall, domestication increased fruit and flower sizes and pericarp thickness, altered capsaicin levels, and altered fruit position and flower color. Weevils laid more eggs and caused more feeding damage on varieties selected for consumption than on wild and ornamental plants. Our results add to the growing literature on the consequences of crop domestication on herbivores. This knowledge could be integrated into breeding programs to select varieties resistant against the pepper weevil. [ABSTRACT FROM AUTHOR]

The 2018–2019 Central European drought had a grave impact on natural and managed ecosystems, affecting their health and productivity. We examined patterns in hyperspectral VNIR imagery using an unsupervised learning approach to improve ecosystem monitoring and the understanding of grassland drought responses. The main objectives of this study were (1) to evaluate the application of simplex volume maximisation (SiVM), an unsupervised learning method, for the detection of grassland drought stress in high-dimensional remote sensing data at the ecosystem scale and (2) to analyse the contributions of different spectral plant and soil traits to the computed stress signal. The drought status of the research site was assessed with a non-parametric standardised precipitation–evapotranspiration index (SPEI) and soil moisture measurements. We used airborne HySpex VNIR-1800 data from spring 2018 and 2019 to compare vegetation condition at the onset of the drought with the state after one year. SiVM, an interpretable matrix factorisation technique, was used to derive typical extreme spectra (archetypes) from the hyperspectral data. The classification of archetypes allowed for the inference of qualitative drought stress levels. The results were evaluated using a set of geophysical measurements and vegetation indices as proxy variables for drought-inhibited vegetation growth. The successful application of SiVM for grassland stress detection at the ecosystem canopy scale was verified in a correlation analysis. The predictor importance was assessed with boosted beta regression. In the resulting interannual stress model, carotenoid-related variables had among the highest coefficient values. The significance of the photochemical reflectance index that uses 512 nm as reference wavelength (PRI512) demonstrates the value of combining imaging spectrometry and unsupervised learning for the monitoring of vegetation stress. It also shows the potential of archetypical reflectance spectra to be used for the remote estimation of photosynthetic efficiency. More conclusive results could be achieved by using vegetation measurements instead of proxy variables for evaluation. It must also be investigated how the method can be generalised across ecosystems. [ABSTRACT FROM AUTHOR]

Mapping and monitoring of Arctic vegetation biochemical and biophysical properties is gaining importance as global climate change is disproportionately affecting this region. Previous studies using remote sensing to model Arctic vegetation biochemical and biophysical properties have generally involved empirical modelling with nadir looking broadband sensors and have typically been conducted at the field scale in one study area. Satellite hyperspectral remote sensing has not been previously investigated for retrieving leaf and canopy biochemical and biophysical properties of Arctic vegetation across multiple sites using either empirical or physically-based modelling approaches. Furthermore, multi-angle hyperspectral sensors (CHRIS/PROBA), which can provide insight into vegetation reflectance anisotropy and potentially improve vegetation parameter estimation, have also not been investigated for this purpose. In this study, three modelling approaches previously investigated with field spectroscopy data (Kennedy et al., 2020) were used with CHRIS Mode-1 imagery to predict leaf chlorophyll content, plant area index and canopy chlorophyll content across a bioclimatic gradient in the Western Canadian Arctic. Modelling approaches included: parametric linear regression based on vegetation indices (VI), non-parametric machine learning Gaussian processes regression (GPR) and inversion of the PROSAIL radiative transfer model using a look-up table approach (LUT). CHRIS imagery was acquired with −55°, −36°, 0°, +36°, +55° view zenith angles (VZA) between 2011 and 2014 over three field sites extending from the Richardson Mountains in central Yukon, Canada to the north end of Banks Island, Northwest Territories, Canada. Field measurements were acquired within several weeks of satellite acquisitions. GPR had the best model fit (mean cross-validated (cv) coefficient of determination, r2cv = 0.61 across all vegetation variables, sites and VZAs vs. 0.59 for the simple ratio, SR) and predictive performance (normalized root mean square error, NRMSEcv = 0.13 vs. 0.14 for SR). The revised optimized soil adjusted VI (ROSAVI) performance was slightly poorer (r2cv = 0.51; NRMSEcv = 0.15). The physically-based PROSAIL model performed poorer than all empirical models (r2 = 0.50; NRMSE = 0.18). This ranking of model performance is similar to that found in the previous field spectroscopy study, where empirical model fits and predictive performance were only slightly worse. With respect to view angle performance, NRMSE varied only slightly, indicating no distinct advantage for any one VZA. Overall, strong potential has been demonstrated for empirical modelling of Arctic vegetation chlorophyll and plant area index using hyperspectral data combined with band selection/optimization procedures in the Arctic. Recently launched and future hyperspectral satellites, including next generation airborne sensors, will likely provide improvements to the model performance reported here. [ABSTRACT FROM AUTHOR]

The study aimed to assess the effect of informal tourist trails on the abiotic conditions and floristic composition of deciduous forest undergrowth in an urban area. The study was carried out in the Wolski Forest in Kraków (Poland) in 2020 using a total of 400 plots (1 m × 1m) situated in close (CL) and further (FU) vicinity of informal (<50 cm in width) and formal (≥150 cm in width) tourist trails in the forest interior and forest edge sites.Agreater content of N-NH4, P, and K occurred in the forest interior sites, while greater light intensity, species number, total plant cover, and stem height were found in the forest edge sites. Greater light intensity and a higher percentage of total and damaged plant cover were recorded in CLplots, while a greater height of plants was seen in FUplots. The number of species was higher in plots located along informal trails than in plots along formal trails. The dominance of therophytes and autochorous species along informal trails in the forest interior sites might be a result of successful diaspore dispersal by people walking, while the substantial share of zoochorous species along formal trails suggests their dissemination by dogs accompanying visitors. The dominance of forest and ruderal taxa in the forest interior sites suggests unfavourable conditions for the germination of meadow and grassland species. The higher cover-abundance of alien plants in CL plots along informal trails and FU plots along formal traits suggests that alien plants growing near the formal trails are more exposed to mechanical damage. [ABSTRACT FROM AUTHOR]

Climate change variation on a small scale may alter the underlying processes determining a pattern operating at large scale and vice versa. Plant response to climate change on individual plant levels on a fine scale tends to change population structure, community composition and ecosystem processes and functioning. Therefore, we reviewed the literature on plant response and resilience to climate change in space and time at different scales on the Tibetan Plateau. We report that spatiotemporal variation in temperature and precipitation dynamics drives the vegetation and ecosystem function on the Tibetan Plateau (TP), following the water–energy dynamics hypothesis. Increasing temperature with respect to time increased the net primary productivity (NPP) on most parts of the Tibetan Plateau, but the productivity dynamics on some parts were constrained by 0.3 °C decade−1 rising temperature. Moreover, we report that accelerating studies on plant community assemblage and their contribution to ecosystem functioning may help to identify the community response and resilience to climate extremes. Furthermore, records on species losses help to build the sustainable management plan for the entire Tibetan Plateau. We recommend that incorporating long-term temporal data with multiple factor analyses will be helpful to formulate the appropriate measures for a healthy ecosystem on the Tibetan Plateau. [ABSTRACT FROM AUTHOR]

Rainforest conversion to woody croplands impacts the carbon cycle via ecophysiological processes such as photosynthesis and autotrophic respiration. Changes in the carbon cycle associated with land-use change can be estimated through Land Surface Models (LSMs). The accuracy of carbon flux estimation in carbon fluxes associated with land-use change has been attributed to uncertainties in the model parameters affecting photosynthetic activity, which is a function of both carboxylation capacity (Vcmax) and electron transport capacity (Jmax). In order to reduce such uncertainties for common tropical woody crops and trees, in this study we measured Vcmax25 (Vcmax standardized to 25 °C), Jmax25 (Jmax standardized to 25 °C) and light-saturated photosynthetic capacity (Amax) of Elaeis guineensis Jacq. (oil palm), Hevea brasiliensis (rubber tree), and two native tree species, Eusideroxylon zwageri and Alstonia scholaris, in a converted landscape in Jambi province (Sumatra, Indonesia) at smallholder plantations. We considered three plantations; a monoculture rubber, a monoculture oil palm, and an agroforestry system (jungle rubber plantation), where rubber trees coexist with some native trees. We performed measurements on leaves at the lower part of the canopy, and used a scaling method based on exponential function to scale up photosynthetic capacity related traits to the top of the canopy. At the lower part of the canopy, we found (i) high Vcmax25 values for H. brasiliensis from monoculture rubber plantation and jungle rubber plantation that was linked to a high area-based leaf nitrogen content, and (ii) low value of Amax for E. guineensis from oil palm plantation that was due to a low value of Vcmax25 and a high value of dark respiration. At the top of the canopy, Amax varied much more than Vcmax25 among different land-use types. We found that photosynthetic capacity declined fastest from the top to the lower part of the canopy in oil palm plantations. We demonstrate that photosynthetic capacity related traits measured at the lower part of the canopy can be successfully scaled up to the top of the canopy. We thus provide helpful new data that can be used to constrain LSMs that simulate land-use change related to rubber and oil palm expansion. [ABSTRACT FROM AUTHOR]

The advent of up-to-date hyperspectral technologies, and their increasing performance both spectrally and spatially, allows for new and exciting studies and practical applications in agriculture (soils and crops) and vegetation mapping and monitoring atregional (satellite platforms) andwithin-field (airplanes, drones and ground-based platforms) scales. Within this context, the special issue has included eleven international research studies using different hyperspectral datasets (from the Visible to the Shortwave Infrared spectral region) for agricultural soil, crop and vegetation modelling, mapping, and monitoring. Different classification methods (Support Vector Machine, Random Forest, Artificial Neural Network, Decision Tree) and crop canopy/leaf biophysical parameters (e.g., chlorophyll content) estimation methods (partial least squares and multiple linear regressions) have been evaluated. Further, drone-based hyperspectral mapping by combining bidirectional reflectance distribution function (BRDF) model for multi-angle remote sensing and object-oriented classification methods are also examined. A review article on the recent advances of hyperspectral imaging technology and applications in agriculture is also included in this issue. The special issue is intended to help researchers and farmers involved in precision agriculture technology and practices to a better comprehension of strengths and limitations of the application of hyperspectral measurements for agriculture and vegetation monitoring. The studies published herein can be used by the agriculture and vegetation research and management communities to improve the characterization and evaluation of biophysical variables and processes, as well as for a more accurate prediction of plant nutrient using existing and forthcoming hyperspectral remote sensing technologies. [ABSTRACT FROM AUTHOR]

To evaluate the potential of multi-angle hyperspectral sensors for monitoring vegetation variables in Arctic environments, empirical and physical modelling using field data was implemented for the retrieval of leaf and canopy chlorophyll content (LCC, CCC) and plant area index (PAI) measured at four sites situated across a bioclimatic gradient in the Western Canadian Arctic. Field reflectance data were acquired with an ASD FieldSpec (305–1075 nm) and used to simulate CHRIS Mode1 spectra (411–997 nm). Multi-angle measurements were taken corresponding to CHRIS view zenith angles (VZA) (−55°, −36°, 0°, +36°, +55°). Empirical modelling compared parametric regression based on vegetation indices (VIs) to non-parametric Gaussian Processes Regression (GPR). In physical modelling, PROSAIL was inverted using numerical optimization and look-up table (LUT) approaches. Cross-validation of the empirical models ranked GPR as best, followed by simple ratio (SR) with optimally selected NIR and red wavelengths, and then ROSAVI using its published wavelengths (mean r2cv = 0.62, 0.58, and 0.54, respectively across all sites, variables, and VZAs). However, the best predictive performance was achieved by SR followed by GPR and ROSAVI (NRMSEcv = 0.12, 0.16, 0.16, respectively). PROSAIL simulated the multi-angle top-of-canopy reflectance well with numerical optimization (r2 = ~0.99, RMSE = 0.004 ± 0.002), but best performing LUT models of LCC, CCC and PAI were poorer than the empirical approaches (mean r2 = 0.48, mean NRMSE = 0.22). PROSAIL performed best at the high Arctic sparsely vegetated site (r2 = 0.57–0.86 for all parameters). Overall, the best performing VZA was −55° for empirical modelling and 0° and ±55° for physical modelling; however, these were not significantly better than the other VZAs. Overall, this study demonstrates that, for Arctic vegetation, nadir narrowband reflectance data used to derive simple empirical VIs with optimally selected bands is a more efficient approach for modelling chlorophyll and PAI than more complex empirical and physical approaches. [ABSTRACT FROM AUTHOR]

Seed bank survival underpins plant population persistence but studies on seed bank trait-environment interactions are few. Changes in environmental conditions relevant to seed banks occur in desert ecosystems owing to solar energy development. We developed a conceptual model of seed bank survival to complement methodologies using in-situ seed bank packets. Using this framework, we quantified the seed bank survival of two closely related annual desert plant species, one rare (Eriophyllum mohavense) and one common (Eriophyllum wallacei), and the seed bank–environment interactions of these two species in the Mojave Desert within a system that emulates microhabitat variation associated with solar energy development. We tracked 4860 seeds buried across 540 seed packets and found, averaged across both species, that seed bank survival was 21% and 6% for the first and second growing seasons, respectively. After two growing seasons, the rare annual had a significantly greater seed bank survival (10%) than the common annual (2%). Seed bank survival across both species was significantly greater in shade (10%) microhabitats compared to runoff (5%) and control microhabitats (3%). Our study proffers insight into this early life-stage across rare and common congeners and their environmental interactions using a novel conceptual framework for seed bank survival. [ABSTRACT FROM AUTHOR]

Intensive agriculture uses a lot of nitrogen fertilizers to increase crop productivity. These crops are in competition with soil-denitrifying microorganisms that assimilate nitrogen in the form of nitrate and transform it into N2O, a greenhouse gas, or N2. However, certain plant species exude secondary metabolites, called procyanidins, which inhibit denitrifiers and increase the nitrate pool in the soil available for plant nutrition. This phenomenon is called biological denitrification inhibition. Previously, we showed that the addition of exogenous procyanidins to a lettuce crop induces denitrifier inhibition and increases nitrate content in the soil, affecting lettuce morphological traits. Here, the effects of procyanidin amendments in the field on a more long-term and nitrogen-consuming crop species such as celery were tested. The effects of procyanidin amendment on celery growth with those of conventional ammonium nitrate amendments were, therefore, compared. Denitrification activity, nitrate concentration, the abundance of denitrifying bacteria in the soil, and traits related to celery growth were measured. It was shown that the addition of procyanidins inhibits denitrifiers and increases the soil nitrate level, inducing an improvement in celery morphological traits. In addition, procyanidin amendment induces the lowest nitrogen concentration in tissues and reduces N2O emissions. [ABSTRACT FROM AUTHOR]

Globally, fire regimes are being altered by changing climatic conditions. New fire regimes have the potential to drive species extinctions and cause ecosystem state changes, with a range of consequences for ecosystem services. Despite the co-occurrence of forest fires with drought, current approaches to modelling flammability largely overlook the large body of research into plant vulnerability to drought. Here, we outline the mechanisms through which plant responses to drought may affect forest flammability, specifically fuel moisture and the ratio of dead to live fuels. We present a framework for modelling live fuel moisture content (moisture content of foliage and twigs) from soil water content and plant traits, including rooting patterns and leaf traits such as the turgor loss point, osmotic potential, elasticity and leaf mass per area. We also present evidence that physiological drought stress may contribute to previously observed fuel moisture thresholds in south-eastern Australia. Of particular relevance is leaf cavitation and subsequent shedding, which transforms live fuels into dead fuels, which are drier, and thus easier to ignite. We suggest that capitalising on drought research to inform wildfire research presents a major opportunity to develop new insights into wildfires, and new predictive models of seasonal fuel dynamics. [ABSTRACT FROM AUTHOR]

Remotely-sensed Vegetation Indices (VIs) are often tightly correlated with terrestrial ecosystem CO2 uptake (Gross Primary Production or GPP). These correlations have been exploited to infer GPP at local to global scales and over half-hour to decadal periods, though the underlying mechanisms remain incompletely understood. We used satellite remote sensing and eddy covariance observations at 10 sites across a California climate gradient to explore the relationships between GPP, the Enhanced Vegetation Index (EVI), the Normalized Difference Vegetation Index (NDVI), and the Near InfraRed Vegetation (NIRv) index. EVI and NIRv were linearly correlated with GPP across both space and time, whereas the relationship between NDVI and GPP was less general. We explored these interactions using radiative transfer and GPP models forced with in-situ plant trait and soil reflectance observations. GPP ultimately reflects the product of Leaf Area Index (LAI) and leaf level CO2 uptake (Aleaf); a VI that is sensitive mainly to LAI will lack generality across ecosystems that differ in Aleaf. EVI and NIRv showed a strong, multiplicative sensitivity to LAI and Leaf Mass per Area (LMA). LMA was correlated with Aleaf, and EVI and NIRv consequently mimic GPP's multiplicative sensitivity to LAI and Aleaf, as mediated by LMA. NDVI was most sensitive to LAI, and was relatively insensitive to leaf properties over realistic conditions; NDVI lacked EVI and NIRv's sensitivity to both LAI and Aleaf. These findings carry implications for understanding the limitations of current VIs for predicting GPP, and also for devising strategies to improve predictions of GPP. [ABSTRACT FROM AUTHOR]