Evergreen Species Research Articles

Global change progressively increases foliar nitrogen-phosphorus ratios in China's subtropical forests.

Globally increased nitrogen (N) to phosphorus (P) ratios (N/P) affect the structure and functioning of terrestrial ecosystems, but few studies have addressed the variation of foliar N/P over time in subtropical forests. Foliar N/P indicates N versus P limitation in terrestrial ecosystems. Quantifying long-term dynamics of foliar N/P and their potential drivers is crucial for predicting nutrient status and functioning in forest ecosystems under global change. We detected temporal trends of foliar N/P, quantitatively estimated their potential drivers and their interaction between plant types (evergreen vs. deciduous and trees vs. shrubs), using 1811 herbarium specimens of 12 widely distributed species collected during 1920-2010 across China's subtropical forests. We found significant decreases in foliar P concentrations (23.1%) and increases in foliar N/P (21.2%). Foliar N/P increased more in evergreen species (22.9%) than in deciduous species (16.9%). Changes in atmospheric CO2 concentrations ( ), atmospheric N deposition and mean annual temperature (MAT) dominantly contributed to the increased foliar N/P of evergreen species, while , MAT, and vapor pressure deficit, to that of deciduous species. Under future Shared Socioeconomic Pathway (SSP) scenarios, increasing MAT and would continuously increase more foliar N/P in deciduous species than in evergreen species, with more 12.9%, 17.7%, and 19.4% versus 6.1%, 7.9%, and 8.9% of magnitudes under the scenarios of SSP1-2.6, SSP3-7.0, and SSP5-8.5, respectively. The results suggest that global change has intensified and will progressively aggravate N-P imbalance, further altering community composition and ecosystem functioning of subtropical forests.

REPRODUCTIVE ECOLOGY OF AN EVERGREEN DRY SEASON-BLOOMING TREE SPECIES, WALSURA TRIFOLIATA (A. JUSS.) HARMS (MELIACEAE)

Walsura trifoliata is an evergreen dry season-blooming hermaphroditic tree species. The flowers are nectariferous and characterized by urceolate androecium, strong protandry and secondary pollination mechanism, protruded bifid stigma displaying receptivity, self-compatibility and facultative xenogamy without the function of spontaneous autogamy. The floral traits indicate generalist pollination syndrome and adaptation for entomophily, with bees effecting mostly geitonogamy and wasps and butterflies effecting mostly xenogamy. Fruit-set is highest in xenogamy. Fruit is a globular drupe with 1-2 seeds embedded in fleshy aril. Seed dispersal modes include zoochory, barochory and hydrochory. The study shows that the function of generalist pollination syndrome, entomophily, facultative xenogamy and polychory enable this tree species to achieve highest fruit-set, maintain genetic variation through cross-pollination, and disperse its seeds to different distances in the forest ecosystem.

Species traits related to the invasion of woody plants in Patagonian deciduous forests.

The comparison of ecological, phenological, morphological and developmental traits between exotic invasive species and coexisting native species contributes to understand the driving mechanisms of successful invasions. This study aimed to examine which of these traits are related to the invasion of woody plants in the understory of deciduous North Patagonian forests of Argentina. We compared the phenology, shoot growth rate, number of leaves, biomass allocation, leaf herbivory, and recruitment type of two exotic deciduous trees, Crataegus monogyna and Sorbus aucuparia, with those of four coexisting native woody species (one deciduous, one semi-deciduous, and two evergreen species). Spring shoot growth took place several weeks earlier in both exotic species and in the deciduous native species than in the other native species; growth rates were higher in the exotics. Compared to coexisting native species, both exotic species developed shoots that were as long as or longer, had lower biomass allocation to leaves and higher allocation to roots, suffered lower leaf damage by herbivores and exhibited higher seed than vegetative recruitment. This study supports the idea that a combination of phenological, growth rate and mass allocation traits allow exotic species to preempt resources, thus favouring invasion processes.

Gas exchange and 13C-based estimates of intrinsic water-use efficiency show different responses to CO2 enrichment: a global meta-analysis of experimental studies

ABSTRACT Tree intrinsic water-use efficiency (iWUE) is a key characteristic of ecosystem functions central to the global cycles of carbon, water, and energy. Gas exchange and stable carbon isotope compositions have been widely used to assess iWUE. However, it remains unclear to what extent the iWUE estimates obtained using different approaches are comparable, particularly in combination with changes in temperature, precipitation, and experimental duration. Herein, the responses of different estimators of iWUE (as A/g s or through isotopic composition of leaves or tree rings) to elevated CO2 concentrations (eCO2) were assessed through a meta-analysis of 361 observations from 98 independent experiments. Our results show that (1) different proxies for iWUE provide inconsistent estimates of the response of iWUE to eCO2. (2) Throughout the growing season, the average response of g s to eCO2 was smaller than the single-point values estimated by gas exchange and the eCO2-induced reduction in g s was stronger for evergreen species than for deciduous species. (3) Precipitation, rather than temperature, significantly affected the responses of 13C-based estimates of iWUE to eCO2. (4) There was no significant response of leaf 13C-based iWUE estimates to eCO2. (5) The importance of photorespiration in elevated CO2 enhancement responses may be overestimated in evergreen species.

Sub-alpine shrub classification using UAV images: Performance of human observers vs DL classifiers

In recent years, the automatic analysis of natural environment images acquired with unmanned aerial vehicles (UAV) has rapidly gained popularity. UAVs are specially important in mountainous forests where access is difficult and large areas need to be surveyed. In Zao mountains in northeastern Japan, regenerated fir saplings are competing with sub-alpine vegetation shrubs after a severe fir tree mortality caused by bark beetle infestation. A detailed survey of vegetation distribution is key to improve our understanding of species succession and the influence of climate change in that process. To that end, we evaluated the suitability of deep-learning-based automatic image classification of UAV images in order to map sub-alpine vegetation succession in large areas and the potential of fir regeneration.In order to assess the contribution of this technology in this research field, we first conducted an observer study to assess the difficulty for humans of the task of classifying vegetation from images. Afterwards, we compared the observers' accuracy to four state-of-the art deep learning networks for automatic image classification. The best observer accuracy of 55% demonstrates the limitations of species classification using only images. Furthermore, a detailed analysis of the sources of error showed that even though humans could differentiate between deciduous and evergreen species with an accuracy of 96%, identifying the correct species within each group proved much more challenging. In contrast, deep learning networks achieved accuracy values in the range of 70–80% for species classification, clearly demonstrating capabilities beyond human experts. Our experiments also indicated that the performance of these networks was significantly influenced by the similarity between the datasets used to fine-tune them and evaluate them. This fact highlights the importance of building publicly available images databases to further improve the results.Nevertheless, the results presented in this paper show that the analysis of UAV-acquired with deep learning networks can usher in a new type of large-scale study, spanning tenths or even hundreds of hectares with high spatial resolution (of a few cms per pixel), providing the ability to assess challenging vegetation dynamics problems that go beyond the ability of conventional fieldwork methodologies.

Analysis of the inflection points of height-diameter models

The inflection point is an important feature of sigmoidal height-diameter (H-D) models. It is often cited as one of the properties favoring sigmoidal model forms. However, there are very few studies analyzing the inflection points of H-D models. The goals of this study were to theoretically and empirically examine the behaviors of inflection points of six common H-D models with a regional dataset. The six models were the Wykoff (WYK), Schumacher (SCH), Curtis (CUR), Hossfeld IV (HOS), von Bertalanffy-Richards (VBR), and Gompertz (GPZ) models. The models were first fitted in their base forms with tree species as random effects and were then expanded to include functional traits and spatial distribution. The distributions of the estimated inflection points were similar between the two-parameter models WYK, SCH, and CUR, but were different between the three-parameter models HOS, VBR, and GPZ. GPZ produced some of the largest inflection points. HOS and VBR produced concave H-D curves without inflection points for 12.7% and 39.7% of the tree species. Evergreen species or decreasing shade tolerance resulted in larger inflection points. The trends in the estimated inflection points of HOS and VBR were entirely opposite across the landscape. Furthermore, HOS could produce concave H-D curves for portions of the landscape. Based on the studied behaviors, the choice between two-parameter models may not matter. We recommend comparing several three-parameter model forms for consistency in estimated inflection points before deciding on one. Believing sigmoidal models to have inflection points does not necessarily mean that they will produce fitted curves with one. Our study highlights the need to integrate analysis of inflection points into modeling H-D relationships.

Nutritional changes in trees during drought‐induced mortality: A comprehensive meta‐analysis and a field study

AbstractBoth macronutrients and micronutrients are essential for tree growth and development through participating in various ecophysiological processes. However, the impact of the nutritional status of trees on their ability to withstand drought‐induced mortality remains inconclusive. We thus conducted a comprehensive meta‐analysis, compiling data on 11 essential nutrients from 44 publications (493 independent observations). Additionally, a field study was conducted on Pinus sylvestris L. trees with varying drought‐induced vitality loss in the “Visp” forest in southern Switzerland. No consistent decline in tree nutritional status was observed during tree mortality. The meta‐analysis revealed significantly lower leaf potassium (K), iron (Fe), and copper (Cu) concentrations with tree mortality. However, the field study showed no causal relationships between nutritional levels and the vitality status of trees. This discrepancy is mainly attributed to the intrinsic differences in the two types of experimental designs and the ontogenetic stages of target trees. Nutrient reductions preceding tree mortality were predominantly observed in non‐field conditions, where the study was conducted on seedlings and saplings with underdeveloped root systems. It limits the nutrient uptake capacity of these young trees during drought. Furthermore, tree nutritional responses are also influenced by many variables. Specifically, (a) leaf nutrients are more susceptible to drought stress than other organs; (b) reduced tree nutrient concentrations are more prevalent in evergreen species during drought‐induced mortality; (c) of all biomes, Mediterranean forests are most vulnerable to drought‐induced nutrient deficiencies; (d) soil types affect the direction and extent of tree nutritional responses. We identified factors that influence the relationship between tree nutritional status and drought survival, and proposed potential early‐warning indicators of impending tree mortality, for example, decreased K concentrations with declining vitality. These findings contribute to our understanding of tree responses to drought and provide practical implications for forest management strategies in the context of global change.

Leaf traits are good predictors of woody species distribution after bamboo expansion in a mountain forest

The expansion of bamboo into neighboring plant communities is a common phenomenon in nature reserves. However, the role of climate factors and plant functional traits in the distribution of woody species after bamboo expansion remains unclear. Six functional traits of leaves of 180 individuals of 52 species, soil properties and air temperature were measured along an elevational gradient with different bamboo densities on Mt. Fanjingshan, Tongren City, Guizhou. Then, the direct and indirect effects of climate, soil properties, leaf traits and bamboo density on woody species distribution were detected. Our results showed that leaf traits were represented by two independent dimensions. The first dimension (PC1) is represented by the trade-off between the pairs leaf P, leaf N and leaf dry matter content, leaf C, representing nutrient use efficiency (NUE). The second dimension (PC2) was positively associated with leaf area, specific leaf area and leaf N, representing the leaf economics spectrum (LES). Climate, soil, leaf traits and bamboo density significantly explained 18% and 21% of the variance in species importance values for all species and evergreen species, respectively, but not for deciduous species. Air temperature had a positive indirect impact on the species importance value of all species via a negative direct impact on PC2, and air temperature affected the evergreen species importance value in two indirect ways: the first was to affect the species importance value positively and indirectly via PC2; the second was to affect the species importance value positively and indirectly through PC2 and PC1. However, bamboo expansion alone had no significant direct or indirect effects on species distribution. These results suggest that leaf traits are good predictors of woody species distribution after bamboo expansion in a mountain forest, and the effects of bamboo expansion are dependent on tree growth type, air temperature and leaf traits.

Using coniferous plants in the landscape design of Absheron

In improving the environment, one of the main and decisive factors is landscaping. Among them, evergreen trees and shrubs play an important role. They form the basis for protecting the environment from industrial pollution and creating conditions for cultural recreation of the population. The protection of the biosphere from pollution that negatively affects human health, the protection of natural resources and their rational use in the modern era has acquired serious importance and, as a problem of national importance, worries the public. It was revealed that landscaping has a high dust-collecting capacity. Coniferous, evergreen trees and shrubs especially have this ability. Currently, in the gardens and parks of Baku there are a significant number of species and forms of plants that can be successfully used for further landscaping of the city. But this number of tree and shrub species that are stable under these conditions is absolutely insufficient for the growing area of green spaces every day. It is necessary to expand introduction work in this area, paying special attention to the introduction of new evergreen species and forms of trees and shrubs into culture. For this purpose, research work is being carried out in the “Landscape architecture” laboratory.

Evaluation of a Novel Fungicidal Extract from Blue Spruce, Picea pungens

Aqueous extracts from 22 species of evergreen plants and 32 accessions of spruce ( Picea A. Dietr.) were screened using an in vitro assay to determine their antifungal activity against Calonectria henricotiae, one of the causal agents of boxwood blight. Most of the evergreen species and all the spruce accessions showed significant antifungal activity ( P < 0.05); in particular, the extract from one accession of Picea pungens Engelm. had significant effective fungistatic and fungicidal activity ( P < 0.05), both in vitro and when tested on detached boxwood leaves and whole boxwood plants. The extraction process was simple, consisting of autoclaving fresh leaves in water, and, once extracted, the active compound was stable in aqueous solution and when lyophilized and reconstituted. Further investigations will focus on the potential of this extract as an alternative to traditional fungicides for use in a wide range of crops and in diverse applications, from controlling fungal infections in the landscape to preventing postharvest losses in fruit and vegetable crops.

The LHS scheme and wood density define functional groups of woody species in the Brazilian semiarid? Capturing functional syndromes in the Caatinga.

For the Caatinga vegetation, it has not yet been definitively established which adaptive strategies best define the functional groups of woody plants and which syndromes emerge from the relationships between functional traits to achieve success in a semi-arid tropical region. To fill some of these gaps, we analyzed a specific set of characteristics that make up the LHS scheme of the plant ecological strategy (leaf-heigh-seed). The LHS scheme captures the functional niche of plants regarding the functional traits specific leaf area (SLA), plant height (HE), and seed mass (SM). We associate wood density (WD) to this scheme because this trait is a key feature for the identification of functional strategies in seasonally dry vegetation such as the Caatinga. We measured these characteristics in eight woody species and classified them according to their leaf phenology into deciduous and evergreen. The experiment was carried out between December 2017 and November 2018 in Caatinga areas located in the municipality of Barra de Santana, PB, a semiarid region of Brazil. Using cluster analysis, principal component analysis (PCA) and Pearson correlation analyses, we found significant relations between SLA and SM, and HE and WD. The SLA was the main predictor of plant strategy in the Caatinga. According to this characteristic, we identified two functional groups: species with a low SLA and species with a high SLA. We also recognized differences between deciduous and evergreen species based on the same trait. The traits measured, which represent the axes of the plant ecological strategy scheme LHS and wood density, are efficient in the discrimination of functional groups in the Brazilian semiarid. These groups relate to leaf phenology of woody species in this vegetation.

Near-infrared digital hemispherical photography enables correction of plant area index for woody material during leaf-on conditions

Indirect optical measurement techniques enable efficient and non-destructive estimation of plant area index (PAI). However, because they cannot distinguish between foliage and other canopy elements, corrections are needed to determine leaf area index (LAI), which is typically the property of interest. In this study, we investigate near-infrared digital hemispherical photography (DHP) as a means of estimating and correcting for woody material. Using data collected at a deciduous broadleaf forest site, we show that near-infrared DHP could successfully estimate effective wood area index (WAIe) and wood area index (WAI) during leaf-on conditions, providing similar mean values (WAIe = 0.88, WAI = 1.53) to those determined from visible DHP during leaf-off conditions (WAIe = 0.87, WAI = 1.38). This information was used to correct estimates of effective PAI (PAIe) and PAI, enabling effective LAI (LAIe) and LAI to be derived with low RMSD (0.33 for LAIe and 0.76 for LAI), NRMSD (12% for LAIe and 19% for LAI), and bias (−0.01 for LAIe and −0.16 for LAI). Not correcting for woody material led to overestimation of LAIe by 31% on average and 46% in the worst observed case, and the degree of overestimation was further enlarged for LAI (42% on average and 61% in the worst observed case). In agreement with previous studies, the effects of clumping and woody area were found to be partly compensatory. On average, PAIe provided a reasonable approximation of LAI without correction, though overestimation of 52% and underestimation of 20% occurred at the lowest and highest LAI values, respectively. Compared to WAIe and WAI measurement using leaf-off visible DHP, near-infrared DHP offers two crucial advantages: i) data collection can be conducted at the same time as leaf-on PAIe and PAI measurements, and ii) it is likely that the approach could provide an indirect WAIe and WAI measurement option for evergreen species.

Estimation of Oak Leaf Functional Traits for California Woodland Savannas and Mixed Forests: Comparison between Statistical, Physical, and Hybrid Methods Using Spectroscopy

Key leaf functional traits, such as chlorophyll and carotenoids content (Cab and Cxc), equivalent water thickness (EWT), and leaf mass per area (LMA), are essential to the characterization and monitoring of ecosystem function. Spectroscopy provides access to these four leaf traits by relying on their specific spectral absorptions over the 0.4–2.5 µm domain. In this study, we compare the performance of three categories of estimation methods to retrieve these four leaf traits from laboratory directional-hemispherical leaf reflectance and transmittance measurements: statistical, physical, and hybrid methods. To this aim, a dataset pooling samples from 114 deciduous and evergreen oak trees was collected on four sites in California (woodland savannas and mixed forests) over three seasons (spring, summer and fall) and was used to assess the performance of each method. Physical and hybrid methods were based on the PROSPECT leaf radiative transfer model. Physical methods included inversion of PROSPECT from iterative algorithms and look-up table (LUT)-based inversion. For LUT-based methods, two distance functions and two sampling schemes were tested. For statistical and hybrid methods, four distinct machine learning regression algorithms were compared: ridge, partial least squares regression (PLSR), Gaussian process regression (GPR), and random forest regression (RFR). In addition, we evaluated the transferability of statistical methods using an independent dataset (ANGERS Leaf optical properties database) to train the regression algorithms. Thus, a total of 17 estimations were compared. Firstly, we studied the PROSPECT leaf structural parameter N retrieved by iterative inversions and its distribution over our oak-specific dataset. N showed a more pronounced seasonal dependency for the deciduous species than for the evergreen species. For the four traits, the statistical methods trained on our dataset outperformed the PROSPECT-based methods. More particularly, statistical methods using GPR yielded the most accurate estimates (RMSE = 5.0 µg·cm−2; 1.3 µg·cm−2; 0.0009 cm; and 0.0009 g·cm−2 for Cab, Cxc, EWT, and LMA, respectively). Among the PROSPECT-based methods, the iterative inversion of this model led to the most accurate results for Cab, Cxc, and EWT (RMSE = 7.8 µg·cm−2; 2.0 µg·cm−2; and 0.0035 cm, respectively), while for LMA, a hybrid method with RFR (RMSE = 0.0030 g·cm−2) was the most accurate. These results showed that estimation accuracy is independent of the season. Considering the transferability of statistical methods, for the four leaf traits, estimation performance was inferior for estimators built on the ANGERS database compared to estimators built exclusively on our dataset. However, for EWT and LMA, we demonstrated that these types of statistical methods lead to better estimation accuracy than PROSPECT-based methods (RMSE = 0.0016 cm and 0.0013 g·cm−2 respectively). Finally, our results showed that more differences were observed between plant functional types than between species or seasons.

Assessment of the Air Cleaning Performance and Humidity and Temperature Control by Five Evergreen Woody Plants

Indoor air quality (IAQ) directly affects human health. The increase in PM and CO2 concentration indoors caused an increase in the prevalence of sick building syndrome (SBS) symptoms. Plants could contribute to reducing particulate matter (PM) and CO2. This study identifies the most efficient evergreen plant species for improving indoor air quality by assessing the ability of five different indigenous Korean evergreen plant species to reduce PM and CO2 and regulate humidity and temperature under indoor environmental conditions in acrylic chambers. The clean air delivery rates (CADR) were calculated to evaluate the efficacy of plants in reducing PM and CO2. We assessed the performance of removing the five study plants on PM1 (~0.68–3.01 m3/h/leaf area), PM2.5 (~0.73–3.08 m3/h/leaf area), PM10 (~0.67–3.04 m3/h/leaf area), and CO2 (~0.48–1.04 m3/h/leaf area). The species Ilex pedunculosa, Pittosporum tobira, and Gardenia jasminoides were the most effective at reducing PM. The CADR of CO2 also differed among the five plant species and corresponded to their photosynthetic rate. Viburnum odoratissimum var. awabuki, which had the high photosynthetic rate, was most effective at reducing CO2. By contrast, PM reduction was correlated with plant leaf structure. Plants with a high leaf density can accumulate more PM. The plants were also able to control temperature and humidity. The average temperature of the control chamber was higher, and the humidity was lower than that of the plant chambers. In this study, the five evergreen species effectively reduced air pollutants and can be used to improve IAQ.

Herbaceous species and dry forest species have more acquisitive leaf traits than woody species and wet forest species

Abstract Life forms are key to understand the changes in species composition and vegetation types in space and with succession over time. We asked how life forms from dry and wet regions differ in their leaf traits and trait hyperspace (i.e. trait variation) in early tropical forest succession on abandoned agricultural fields. We compared 324 early successional species from six life forms (herbs, grasses, vines, lianas, shrubs and trees) that occur in the first 5 years of succession on abandoned fields in Ghanaian wet and drought deciduous tropical forests. We measured 12 leaf traits that are important for carbon, water and nutrient use. A principal component analysis showed that 46% of trait variation is captured by a two‐dimensional spectrum of plant form and function: a leaf economics spectrum underpinning fast‐slow growth strategies, and a leaf size spectrum related to plant size and heat balance, which underlie species sorting along environmental gradients in space and time (during succession). Herbaceous and woody life forms had different leaf economics strategies: herbaceous species had more acquisitive trait values (e.g. higher leaf nutrient concentrations) that increase resource capture and use efficiency whereas woody species had more conservative trait values (e.g. higher leaf mass per area) that increase resource conservation. Regardless of life forms, dry forest species and deciduous species had more acquisitive trait values than wet forest species and evergreen species as they maximize their growth during the shorter growing season. The trait hyperspace was larger for woody life forms especially in wet forests. Synthesis. Herbaceous species had ‘faster’ leaf economics trait values and, hence, rapid carbon gain, explaining their success earlier in succession. In contrast, woody species had ‘slower’ resource conservation trait values that increase persistence, thus explaining their success later in succession. Deciduous species especially in a dry region had higher leaf nitrogen and phosphorus concentration to attain faster carbon gain to cope with a seasonally harsh environment. The trait hyperspace was generally smaller in the dry forest, as there are more deciduous species, and as a result, there is less variation in leaf lifespan and associated traits. Read the free Plain Language Summary for this article on the Journal blog.

Factors influencing the difference in dissolved ion inputs to the forest floor between deciduous and coniferous stands: comparison under high and low atmospheric deposition conditions

It is necessary to clear the relationship between physical and vegetation factors on the processes governing dissolved ion inputs to the forest floor to estimate correctly the values of atmospheric input to the forest. This study identified the factors influencing the differences in dissolved ion inputs to the forest floor between coniferous evergreen and broad-leaved deciduous species by analyzing the phenological variations of dry deposition and canopy exchange calculated by the canopy budget model under a high-deposition site near the city of Tokyo and a low-deposition site 84 km further away. At low-deposition site, vegetation factors such as capture efficiency did not explain the differences in Na+ or Cl− dry deposition. Leaf physiological characteristics influenced the differences in the Mg2+ and Ca2+ canopy leaching values, and phenology, leaf wettability, and diffusion processes from water film into leaves influenced the differences in NH4+ and NO3− input processes between tree types. At the high-deposition site, differences in the dry deposition of Na+, SO42−, Cl−, Mg2+, Ca2+, NH4+, and NO3− between tree types were influenced by differences in capture efficiency between coniferous and broad-leaved canopies in the leafed period and by the absence of leaves in deciduous species after leaf fall. These results indicated that atmospheric deposition affected the capture efficiency of coniferous trees for dry deposition and enhanced the difference of dissolved ion inputs to the forest floor between coniferous and deciduous species.

Positive interactions in shaping neighborhood diversity during secondary forests recovery: Revisiting the classical paradigm

Secondary forests recovery, following disturbances, plays a pivotal role in ecosystem dynamics and biodiversity recovery. Given the rising frequency and intensity of anthropogenic disturbances within forest ecosystems, understanding the mechanisms underlying secondary succession is vital for the effective restoration and conservation of compromised ecosystems. In the classical secondary succession paradigm, early-arriving species are gradually replaced by their later-arriving counterparts. However, over time, valuable historical insights into the involvement of pioneer species become obscured and challenging to discern, particularly in community-scale studies. Consequently, this obscurity has predominantly directed contemporary research predominantly towards examining the consequences of species replacement by later-arriving counterparts during secondary succession. Concurrently, the mechanisms by which pioneer species facilitate or impede the establishment of diversity among later-arriving species remain insufficiently clarified. In this study, we established a 6-ha dynamic forest plot within a secondary forest that has undergone nearly four decades of restoration. Specifically, we utilized the individual species-area relationship (ISAR) framework to evaluate the neighborhood diversity structure of 49 evergreen and 20 deciduous species identified within our evergreen broad-leaved forest plot. Our findings indicate that deciduous tree species undergo a transition from diversity accumulator to repeller in diversity structuring as they progress through different life history stages. On the other hand, evergreen trees either engage in diversity accumulator or neutral. Through repeated plot surveys, we established a comprehensive dataset encompassing the mortality and regeneration of evergreen and deciduous tree species from 2014 to 2020. Spatial covariance models were employed to quantify the distinct effects of density dependence on deciduous and evergreen tree species. The results demonstrate significant negative density dependence mortality and self-thinning in deciduous species at all life history stages. Conversely, adult evergreen tree species facilitate the survival of their seedlings and saplings. In contrast to the classical paradigm that primarily focuses on the replacement of pioneer species by successor species, our findings reveal: (i) self-inhibition mechanisms that shape the neighborhood diversity spatial patterns among deciduous tree species, (ii) self-promotion or neutral mechanisms that influence the diversity spatial patterns of evergreen tree species, and (iii) early-arriving tree species that play a role in facilitating the establishment and diversity of late-arriving counterparts. These results not only signify the significant role of late-arriving species in the natural recovery of secondary forests but also propose that integrating the mechanisms of facilitation, inhibition, and neutral interactions into the classic forest succession paradigm could reshape our interpretation of interactions within plant communities across historical, current, and future timeframes. Such comprehension holds implications for forest management policies and conservation practices.

Higher vascular plant abundance associated with decreased ecosystem respiration after 20 years of warming in the forest–tundra ecotone

Abstract The on‐going climate warming is promoting shrub abundance in high latitudes, but the effect of this phenomenon on ecosystem functioning is expected to depend on whether deciduous or evergreen species increase in response to warming. To explore effects of long‐term warming on shrubs and further on ecosystem functioning, we analysed vegetation and ecosystem CO2 exchange after 20 years of warming in the forest–tundra ecotone in subarctic Sweden. A previous study conducted 9 years earlier had found increased evergreen Empetrum nigrum ssp. hermaphroditum in the forest and increased deciduous Betula nana in the tundra. Following current understanding, we expected continued increase in shrub abundance that would be stronger in tundra than in forest. We expected warming to increase ecosystem respiration (Re) and gross primary productivity (GPP), with a greater increase in Re in tundra due to increased deciduous shrub abundance, leading to a less negative net ecosystem exchange and reduced ecosystem C sink strength. As predicted, vascular plant abundances were higher in the warmed plots with a stronger response in tundra than in forest. However, whereas B. nana had increased in abundance since the last survey, E. hermaphroditum abundance had declined due to several moth and rodent outbreaks during the past decade. In contrast to predictions, Re was significantly lower in the warmed plots irrespective of habitat, and GPP increased marginally only in the forest. The lower Re and a higher GPP under warming in the forest together led to increased net C sink. Re was negatively associated with the total vascular plant abundance. Our results highlight the importance of disturbance regimes for vegetation responses to warming. Climate warming may promote species with both a high capacity to grow under warmer conditions and a resilience towards herbivore outbreaks. Negative correlation between Re and total vascular plant abundance further indicate that the indirect impacts of increased plants on soil microclimate may become increasingly important for ecosystem CO2 exchange in the long run, which adds to the different mechanisms that link warming and CO2 fluxes in northern ecosystems. Read the free Plain Language Summary for this article on the Journal blog.

A Simulation Study of the Impact of Urban Street Greening on the Thermal Comfort in Street Canyons on Hot and Cold Days

The urban heat island effect has become a widely concerning issue worldwide. Many researchers have made great efforts to improve the summer thermal comfort of urban street canyons by optimizing street greening. Relatively less research has focused on how to improve the thermal comfort of street canyons by optimizing street greening during cold days. Many researchers have proposed strategies to improve the summer thermal comfort of street canyons using road greening. This may have a significant negative impact on the winter thermal comfort of street canyons due to the lack of consideration of the impact on hot and cold days simultaneously, especially when the road green space is mainly composed of evergreen tree species. We aimed to explore the impacts of urban street greening on thermal comfort on hot and cold days at the same time. We used Zhutang West Road in Changsha, China, as an example and built six different models to explore the impacts of the street vegetation types, number of street trees, tree heights, crown widths, and Leaf Area Index on the thermal comfort of the street canyon. In addition, we also considered the impact of different building features and wind directions on the thermal comfort of the street canyon. We employed ENVI-met (version 5.5.1) to simulate different urban street greening models. The results show that the model with a high tree canopy density, tall trees, large and dense crowns, and sufficient building shade has good thermal comfort on hot days (the average physiological equivalent temperature (PET) is 31.1 °C for the study period) and bad thermal comfort on cold days (the PET is 13.3 °C) when it is compared with the other models (the average PETs are 36.2 °C, 31.5 °C, 41.5 °C, 36.2 °C, and 35.5 °C, respectively, on hot days and for other models). In addition, the model with a very large number of short hedges has a positive impact on thermal comfort during hot days (the PET is 31.1 °C). The PET value of another comparable model which does not have hedges is 31.5 °C. Even if the model with a small building area has good ventilation, the small building shade area in the model has a more obvious impact and the model has relatively good thermal comfort during cold days (the PET is 14.2 °C) when it is compared to models with bigger building areas (the PET is 13.9 °C). In summer, when the wind is parallel to the direction of the street canyon, the wind speed in the street canyon is high and the model has relatively good thermal comfort (the PET is 35.5 °C) compared with another model which has different wind direction and lower wind speed at the street canyon (the PET is 36.2 °C). In winter, when the wind is perpendicular to the direction of the street canyon, buildings and trees have a strong windproof effect and this is beneficial to the improvement of thermal comfort (the PET is 15.3 °C for this model and 13.9 °C for another comparable model). This research lays a solid foundation and encourages people to think about the impact of building and tree composition and configuration on the thermal comfort of street canyons during hot and cold days simultaneously.

Tracking photosynthetic phenology using spectral indices at the leaf and canopy scales in temperate evergreen and deciduous trees

Vegetation photosynthetic phenology is an important indicator to characterize the biological responses of terrestrial carbon cycle to climate change. Remote sensing-derived spectral indices have been used to estimate photosynthetic phenology of terrestrial ecosystems, yet there are large uncertainties due to differences in leaf structure and canopy function between evergreen and deciduous trees. In this study, we used in-situ measured meteorology, the maximum rate of leaf-level CO2 assimilation (Amax), chlorophyll fluorescence and canopy color changes in evergreen and deciduous species to evaluate and compare the abilities of spectral indices for photosynthetic phenology modeling. Seasonal variation in Amax is used as a proxy for photosynthetic phenology. Several indices were used, including the normalized difference vegetation index (NDVI), near-infrared reflectance vegetation index (NIRv), photochemical reflectance index (PRI), chlorophyll/carotenoid index (CCI), green-red vegetation index (GRVI), and green chromaticity coordinates (Gcc). We found that NIRv and PRI estimated phenological periods for Cedrus deodara and three deciduous trees all differed from Amax by less than 5 days, and all were linearly related to Amax (R2 > 0.6). CCI had less potential for Amax modeling, while NDVI had the largest error in predicting Amax. Gcc was a more accurate proxy for photosynthetic phenology than GRVI at the canopy scale. In addition, we found that the variability of different spectral indices in tracking photosynthetic phenology of evergreen and deciduous species was related to non-photochemical quenching processes. Especially for the fraction of absorbed light quenched by dynamic NPQ (ɸNPQ) and the fraction of absorbed light quenched by sustained NPQ (ɸf,D), they contribute more than 40 % to the variations of the NIRv and PRI spectral signals. Therefore, NIRv and PRI provide powerful tools for monitoring photosynthetic phenology, and future exploration of NIRv and PRI at larger spatial scales will favor the global plant phenology and carbon uptake modeling.