Search Results (714)

The Tibetan Plateau is highly sensitive to global climate change and characterized by pronounced ecological fragility, making vegetation net primary productivity (NPP) a key indicator for assessing ecosystem functioning and regional ecological security. This study aims to characterize the spatiotemporal dynamics of NPP and to disentangle the multiple natural and land-use drivers shaping its variability across the Tibetan Plateau. MODIS-derived NPP data for the period 2001–2022 are integrated with multi-source datasets on climate, topography, normalized difference vegetation index (NDVI), and land use (CLCD), and analyzed using trend and correlation analyses, land-use transfer matrices, an optimal-parameter geographical detector, and partial least squares structural equation modeling (PLS-SEM). The results indicate that NPP exhibits a significant but fluctuating upward trend (0.52 gC·m⁻²·a⁻¹, p < 0.01), with higher values in the southeast and lower values in the northwest, the Yunnan Plateau evergreen broadleaf and pine forest region (VA5) and the southern Himalayan montane forest region (VA6) function as high-value centers, and regions such as the Kunlun high-cold desert region (HID1) represent low-value centers. The mutual conversion between forestland and grassland and bare land constitutes a key process driving regional NPP changes, with the net expansion of forestland making a substantial contribution to NPP increases (net gain of 2606.88 TgC). Geographic detector analysis indicates that NDVI (q = 0.741) and land use type (q = 0.741) are the primary factors governing the spatial differentiation of NPP, followed by precipitation, slope, and temperature. Moreover, interactions between any two factors enhance their explanatory power, with the interaction between aspect and land use type exhibiting the strongest effect (q approaching 1). PLS-SEM path analysis further quantifies the driving pathways, revealing that mean annual precipitation and land use type are the most direct drivers of NPP, while climatic and topographic factors influence NPP indirectly through their effects on vegetation cover and land use type. This study advances the understanding of the multifactorial driving mechanisms of ecosystem productivity on the Tibetan Plateau and provides a scientific basis for zoned and differentiated ecological restoration and climate adaptation strategies. Full article

The balance between gross primary productivity (GPP) and ecosystem respiration (ER) defines an ecosystem’s carbon sink-source status. Under global warming, hydrothermal conditions critically shape carbon fluxes, yet their differential impacts on GPP and ER remain insufficiently understood, especially across biomes. Elucidating these differences is essential for reducing uncertainties in terrestrial carbon cycle projections under ongoing climate change. Here, based on flux observations from global terrestrial sites with a focus on forest ecosystems, we selected mean annual temperature (MAT), latent heat flux (LH), vapor pressure deficit (VPD), soil water content (SWC), and annual precipitation as representative indicators of hydrothermal conditions, and employed mixed-effects models to examine how these key environmental drivers influence GPP and ER. After analyzing the fixed effects, LH and MAT promoted GPP more strongly than ER (slope = 0.5 > 0.253, slope = 0.595 > 0.392, respectively), whereas VPD suppressed GPP more than ER (slope = −0.658 < −0.499), yet accounted for a greater proportion of variance in ER than in GPP (R² = 0.14 > 0.07). Although SWC had a significant (p < 0.001) positive effect on GPP, the effect size was minimal, and its impact on ER was insignificant. R² decomposition showed that marginal R² values were similar for the GPP and ER models (0.43 and 0.44), whereas the GPP model exhibited a substantially higher conditional R² (0.82 vs. 0.63), indicating that MAT exerted a stronger influence on GPP than on ER across ecosystem types. The combined analysis of fixed and random effects indicated that MAT affected GPP more variably than ER across ecosystem types, with the strongest responses in mixed forests and savannas, intermediate responses in evergreen needleleaf forests, and the weakest responses in evergreen broadleaf forests. Overall, this study advances our understanding of how environmental factors differently influence GPP and ER, and incorporating these differences can improve predictions of forest carbon fluxes and climate-carbon feedbacks. Full article

Warm-temperate evergreen broad-leaved forests are distinguished from the deciduous broad-leaved forests in that their foliage is retained year-round and their specific leaf area is often higher than that of temperate evergreen coniferous forests. However, the implications of these traits for carbon and water fluxes and their coupling remain poorly understood. In this study, we quantified gross primary production (GPP), evapotranspiration (ET), water-use efficiency (WUE), and intrinsic WUE (IWUE) using seven years of eddy-covariance measurements from a warm-temperate evergreen broad-leaved forest in southern South Korea. We further evaluated the abiotic and biotic drivers of their seasonal variability using structural equation modeling. The forest acted as a carbon sink even during winter, with an annual GPP of 2176 ± 135 g C m⁻² yr⁻¹, ET of 596 ± 59 kg H₂O m⁻² yr⁻¹, a mean daily WUE of 4.15 ± 0.25 g C (kg H₂O)⁻¹, and a mean daily IWUE of 20.3 ± 3.0 g C hPa (kg H₂O)⁻¹. Among WUE components, the main driver of GPP during warm and humid periods was incoming shortwave radiation (RSDN) followed by air temperature (Tair), whereas ET was primarily controlled by Tair. Cold and dry seasons and main annual drivers of GPP and ET were Tair. Although the leaf area index (LAI) was increased by RSDN and Tair, it did not serve as a mediator affecting GPP and ET, contrary to our expectations. Differences in how GPP and ET responded to abiotic factors ultimately governed WUE and IWUE in this forest type, underscoring the importance of site-specific characteristics in evaluating ecosystem water-use efficiency. Full article

In species-rich forests, the integration of vegetative and reproductive traits defines plant ecological strategies and underpins community assembly. How these trait syndromes assemble into functional groups to facilitate species coexistence in ecotones remains unclear. To address this, we measured 17 key functional traits in 121 woody plant species, covering vegetative and reproductive traits, and used hierarchical clustering to classify these species into functional groups (FGs). We found the following: (1) The woody plant community exhibits distinct trait syndromes adapted to the ecotonal environment: evergreen species accounted for 84.3%, microphanerophytes dominated (95.04%), simple leaves and alternate phyllotaxy prevailed, and animal-mediated pollination (91.74%) and seed dispersal (77.69%) were the primary reproductive strategies. (2) The 121 species were classified into 10 optimal FGs based on integrated differences in vegetative traits (e.g., leaf morphology, life form, phyllotaxy) and reproductive traits (e.g., pollination/dispersal mode, inflorescence/fruit type). Most FGs were dominated by evergreen microphanerophytes, reflecting convergent adaptation to the subtropical ecotonal environment, while distinct adaptive strategies differentiated the groups: FG1 (solely Meliosma rigida) was distinguished by whorled phyllotaxy and large leaves, a specialization for high-light microhabitats; FG5, a unique deciduous group, comprised species (e.g., Nyssa sinensis) with alternate leaves and axillary inflorescences, adapting to seasonal resource fluctuations. (3) These FGs reflected adaptive strategies to diverse microhabitats: rare species in FG4 (e.g., Acer cordatum) adopted wind-dependent pollination/dispersal to cope with mountainous wind variability, while FGs 3, 7, 8, 10 relied on animal mutualism to ensure reproductive success, highlighting the role of plant–animal interactions in community structure. Our study clarifies the trait differentiation patterns and FG assembly mechanisms of woody plants in the mid-subtropical–south-subtropical ecotone. The integrated trait-based FG classification could provide insights into how species coexist via niche differentiation and offer a theoretical basis for biodiversity and ecosystem conservation. Full article

Soil microorganisms are important components of forest ecosystems and play a key role in biogeochemical cycling. Bamboo is invasive due to its strong clonal expansion ability, which often leads to changes in plant communities and soil environments, thus affecting soil microorganisms. However, the existing research focuses on the response of moso bamboo (Phyllostachys edulis) and soil fungi and bacteria, and little attention is paid to other bamboo species and their impact on soil protists. In this study, we examined the effects of Bambusa emeiensis expansion on the soil microbial communities in subtropical evergreen broad-leaved forests. B. emeiensis expansion significantly reduced plant diversity and soil pH (p < 0.05). The expansion of B. emeiensis did not significantly change the relative abundance of dominant bacteria and fungi groups in the soil, but significantly changed the community composition of protists, including a significant increase in the relative abundance of Cercozoa, while the Evosea_X group and Ciliophora decreased significantly (p < 0.05). While α-diversity remained unchanged across all microbial groups, only protist community structure differed significantly (p = 0.026). The main driver of protist variation was identified as plant diversity decline by redundancy analysis (R² = 0.760, p = 0.032). These results can be interpreted within a bottom-up regulatory framework, in which plant diversity is linked to changes in protist community composition. Overall, protists are an important group of organisms that help us understand the impact of bamboo growth on the environment. Their role in nutrient cycling and soil fertility suggests that changes in protist communities may have broader implications for ecosystem sustainability. This study provides a scientific reference for the ecological management of regional B. emeiensis and highlights the potential impact of protist community shifts on soil health and ecosystem resilience. Full article

In the current context of global warming, quantifying carbon fluxes between biosphere and atmosphere and identifying ecosystems as carbon sources or sinks is essential. The goal of this study is to quantify net carbon fluxes for the main forest types in peninsular Spain and characterize them as carbon sources or sinks. A hybrid methodology is proposed. First, net primary production (NPP) is obtained through machine learning using site properties, time metrics of meteorological series, and forest inventory data as inputs. The most accurate NPP estimates (R² ≥ 0.8 and relative RMSE ≤ 30%) were obtained by kernel ridge regression and gaussian process regression using latitude, elevation, time metrics of air temperature, precipitation and incoming solar radiation, and growing stock volume as inputs. Secondly, net ecosystem production (NEP) is obtained by subtracting heterotrophic respiration simulated by Biome-BGC from the previous NPP. All considered forest types presented small and mostly positive NPP and NEP values (greater for deciduous than for evergreen forests), thus generally acting as carbon sinks during the 2004–2018 period. Full article

Many native mammal species rely on the habitat elements provided by old-growth forests in the eastern United States (U.S.). Today, old-growth forests persist as remnant stands in the landscape. Historically, they included a mosaic of eastern forest types including mixed mesophytic, oak–hickory, southeastern evergreen, and hemlock-white pine-northern hardwood forests. Due to the rapid (<250 years) and almost complete (99% loss) removal of old-growth forests from eastern U.S. landscapes, research regarding the current and historic relationship between native mammals and old-growth forests is lacking. Using comparisons with better-studied old-growth forests in the western U.S., historical accounts of mammal distribution, and the habitat elements of eastern old-growth forest types, we aim to describe the mammals currently and historically supported by these rare forests in this scoping review. Full article

To clarify the spatial–temporal evolution patterns and climate-driven mechanisms of carbon sinks of forest ecosystems under climate change, we calculated the net ecosystem productivity (NEP) of forests in the Guangxi region using remote sensing and meteorological data from 2000 to 2023. By employing trend analysis, spatial clustering, the Hurst index, and climate contribution evaluation, we analyzed the spatial and temporal changes, sustainability, and the relative contribution of climate impacts on forest carbon sinks. The results are as follows: The carbon sink capacity of forests in Guangxi increased continuously from 2000 to 2023, at a rate of 3.57 g C·m⁻²·a⁻¹, reaching 39.19% higher in 2023 than in 2000. The carbon sink capacity was higher in the southwest and lower in the northeast, with hotspots mainly located in evergreen/deciduous broad-leaved forest areas. The Hurst index indicates that 84.44% of regions are likely to maintain this increasing trend, suggesting stability in forest carbon sink function. The climate contribution rate to forest carbon sinks was moderate, with significant temporal fluctuations. Temperature governed annual variation in forest carbon sinks, influencing up to 36.37% of the area. The annual average contribution rate of climate change to forest carbon sinks was 30.28%, but there were temporal fluctuations and spatial heterogeneity. Over time, climate contributions had a positive driving impact; however, extreme climate events tended to produce a negative effect. The pattern of forest carbon sinks in Guangxi showed a “heat sink-coupling” phenomenon, with 16.23% of the hotspots of forest carbon sinks coinciding with temperature control zones, highlighting the enhancing effect of temperature rise on carbon sinks against a background of water and heat synergy. This study provides a scientific basis for the assessment of forest carbon sink potential and climate suitability management in Guangxi. Full article

Plant phenology is a sensitive indicator of ecosystem responses to climate change, yet its dynamics and drivers in subtropical montane forests remain poorly understood. Based on the continuous phenological monitoring of 12 dominant tree species from 2008 to 2022 in a mid-subtropical evergreen broad-leaved forest on Ailao Mountains, China, this study analyzed phenological shifts and their climatic drivers. The results show that, (1) unlike the widely reported trends in northern mid-to-high latitudes, spring phenophases (budburst and leaf-out) did not exhibit significant advancing trends, while autumn phenophases (leaf coloration and fall) remained stable; (2) water availability played a dominant role in regulating spring phenology, with both budburst and leaf-out showing significant negative correlations with winter-spring precipitation, and responses varied significantly across hydrological year types; and (3) the life form strongly influenced phenological strategies, with evergreen species exhibiting earlier spring phenology than deciduous species. This study highlights that in seasonally humid subtropical montane forests, water availability exerts a stronger control on phenology than temperature. Our findings underscore the necessity of incorporating precipitation variability and functional trait differences into assessments of forest phenology and ecosystem functioning under future climate change, providing a scientific basis for the conservation and adaptive management of subtropical forests. Full article

Schima superba, belonging to the genus Schima of Theaceae, is a common large tree in evergreen broad-leaved forests in subtropical regions of China. As one of the largest transcription factor families in plants, MYB transcription factors play an important role in plant stress response by specifically binding to cis-acting elements in different gene promoter regions to accurately regulate gene expression. However, there are few studies on MYB transcription factors in S. superba. The MYB transcription factor family of S. superba was found and examined in this study using the genomic and transcriptome data of the S. superba. A set of 220 MYB transcription factors was identified from S. superba and classified into four subfamilies. These transcription factors were unevenly distributed on 18 chromosomes of S. superba. The conserved domains of the same subfamily members are highly similar to the conserved motifs. The collinearity analysis between species showed that there were few orthologous genes located on chromosome 18 of S. superba. Numerous elements linked to phytohormone response, stress adaptation, and growth control can be found in the promoter regions of the S. superba MYB transcription factor family, according to an analysis of the promoter cis-acting elements. Verification via qRT-PCR showed that among 15 SsMYBs genes tested, SsMYB24 expression peaked at 96 h of drought stress, followed by a rapid downregulation upon rewatering to initial levels. This expression pattern aligned with the transcriptome data. This study is helpful to further identify the function of SsMYB transcription factors and provide a new molecular mechanism for improving drought tolerance of S. superba. Full article

Symplocos is an ecologically important genus that plays vital roles in subtropical evergreen broad-leaved mountain forests, including contributing to nutrient cycling, providing shelter and habitats for various organisms, and supporting overall plant diversity across East and Southeast Asia. Many species exhibit high levels of endemism and sensitivity to environmental change. China, with its wide range of ecosystems and climatic zones, is home to 18 endemic Symplocos species. Studies revealed that global warming is driving shifts in species diversity, particularly in mountains. Our study explores the current and projected richness patterns of endemic Symplocos species in China under climate change scenarios, emphasizing the implications for conservation planning. We applied stacked species distribution models (SSDMs), using key bioclimatic and environmental variables to predict current and future habitat suitability for endemic Symplocos species, evaluated model performance through multiple accuracy metrics, and generated ensemble projections to assess richness patterns under climate change scenarios. To assess the spatial configuration and fragmentation patterns of the endemic species richness under current and future climate scenarios, landscape metrics were calculated based on classified richness maps. The produced models demonstrated high accuracy with AUC > 0.9 and TSS > 0.75, highlighting the critical role of bioclimatic variables, particularly precipitation and temperature, in shaping endemic Symplocos distribution. Our analysis identifies the current hotspots of Symplocos endemism along southeastern China, particularly in Zhejiang, Fujian, Jiangxi, Hunan, southern Anhui, and northern Guangdong and Guangxi. These areas are at high risk, with up to 35% of endemic Symplocos species richness predicted to be lost over the next 60 years due to climate change. The study predicts a high decrease in endemic Symplocos species richness, especially in South China (e.g., Fujian, Guangdong, Guizhou, Yunnan, southern Shaanxi), and mid-level decreases in East China (e.g., Heilongjiang, Jilin, eastern Inner Mongolia, Liaoning). Conversely, potential increases in endemic Symplocos species richness are projected in northern and western Xinjiang, western Tibet, and parts of eastern Sichuan, Guangxi, Hunan, Hebei, and Anhui, suggesting these regions may serve as future refugia for endemic Symplocos species. The analysis of the landscape structure and configuration revealed relatively minor but notable variations in the spatial structure of endemic Symplocos richness patterns under current and future climate scenarios. However, under the SSP585 scenario by 2080, the medium richness class showed a more pronounced decrease in aggregation index and increase in number of patches relative to other richness classes, suggesting that higher emissions may drive fragmentation of moderately rich areas, potentially isolating populations of Symplocos. These structural changes suggest a potential reduction in habitat quality and connectivity, posing significant risks to the persistence of endemic Symplocos populations, which underscores the urgent need for targeted smart-climate conservation strategies that prioritize both current hotspots and potential future refugia to enhance the resilience of endemic Symplocos forests and their ecosystems in the face of climate change. Full article

Increasing aridity and climate extremes are challenging the resilience of key Mediterranean species. Proxies that indicate plant water status, physiological condition and soil water availability are valuable tools for management planning. However, their reliability requires species-specific validation under dynamic environmental conditions. This study examined the relationship between predawn leaf water potential (Ψ_PD) and soil water potential (Ψ_S) in potted seedlings of two co-occurring Mediterranean evergreen oaks, Q. ilex and Q. suber, subjected to imposed soil drying under greenhouse conditions. We further quantified the occurrence and magnitude of predawn disequilibrium (PDD)—the mismatch between Ψ_PD and Ψ_S—and evaluated its association with soil water availability, plant water-status indicators, environmental factors, and physiological variables. In parallel, we assessed stomatal closure dynamics during the desiccation phase and characterised species-specific mortality patterns under progressive drought. Linear Mixed-Effects Models (LMMs), with pot identity included as a random factor, were fitted to assess the relationship between Ψ_PD and Ψ_S, as well as the occurrence of PDD and its potential drivers for each species. Stomatal conductance (g_s) responses to Ψ_S were evaluated using a paired t-test and an additional LMM. Finally, Generalised Linear Mixed-Effects Models (GLMMs) were used to analyse interspecific differences in mortality. We confirmed a tight relationship between Ψ_PD and Ψ_S, followed by a consistent PDD in both species, with magnitudes of 0.53 MPa for Q. ilex and 0.98 MPa for Q. suber, which increased significantly with drought severity. Our findings suggest that PDD under the studied conditions is primarily driven by soil water depletion and plant desiccation, as indicated by its negative correlation with water status parameters, as well as by its increase with progressive drought. Both oaks exhibited a water-saving strategy, with stomatal closure initiated around Ψ_S = −0.31 MPa (Q. ilex) and −0.42 MPa (Q. suber). Despite their physiological similarities, Q. suber showed higher mortality under imposed drought. These results encourage modelling the relationship between Ψ_PD and Ψ_S to accurately interpret plant and soil water needs in Mediterranean oaks, especially under soil water scarcity, and highlight species-specific responses critical for forest management and restoration under climate change. Full article

Coconut palms (Cocos nucifera L.) are a critical economic and ecological resource in Wenchang City, Hainan. Accurate mapping of their spatial distribution is essential for precision agricultural planning and effective pest and disease management. However, in tropical monsoon regions, persistent cloud cover, spectral similarity with other evergreen species, and redundancy among high-dimensional features hinder the performance of optical classification. To address these challenges, we developed a scalable multi-source remote sensing framework on the Google Earth Engine (GEE) with an emphasis on species-oriented feature design rather than generic feature stacking. The framework integrates Sentinel-1 SAR, Sentinel-2 MSI, and SRTM topographic data to construct a 42-dimensional feature set encompassing spectral, polarimetric, textural, and topographic attributes. Using Random Forest (RF) importance ranking and out-of-bag (OOB) error analysis, an optimal 15-feature subset was identified. Four feature combination schemes were designed to assess the contribution of each data source. The fused dataset achieved an overall accuracy (OA) of 92.51% (Kappa = 0.8928), while the RF-OOB optimized subset maintained a comparable OA of 92.83% (Kappa = 0.8975) with a 64% reduction in dimensionality. Canopy Water Index (CWI), Green Chlorophyll Index (GCI), and VV-polarized backscattering coefficient (${\mathsf{\sigma }}_{\mathrm{V}\mathrm{V}}$) were identified as the most discriminative features. Independent UAV validation (0.07 m resolution) in a 50 km² area of Chongxing Town confirmed the model’s robustness (OA = 90.17%, Kappa = 0.8617). This study provides an efficient and robust framework for large-scale monitoring of tropical economic forests such as coconut palms. Full article

Soil salinity affects large areas of the world and results in horticultural and biodiversity losses in tropical regions. Garcinia humilis (Vahl) C.D. Adams, fam. Clusiaceae, commonly known as achachairu, is a neotropical evergreen fruit tree native to the Amazonian forests in Bolivia. Its tolerance and responses to soil salinity exclusive of other stressors and within a range of salinity levels have not been reported. This study assessed the physiological, biochemical, and morphological responses of G. humilis to different levels of elevated soil salinity induced by saline irrigation. Physiological variables measured included net CO₂ assimilation (A_n), stomatal conductance of H₂O (g_s), intercellular CO₂ concentration, leaf chlorophyll index (LCI), and the ratio of variable to maximum chlorophyll fluorescence (F_v/F_m). Leaf and root nutrient analyses were performed to assess nutrient imbalances and the accumulation of toxic ions. Antioxidant responses, including superoxide dismutase, catalase, peroxidase, guaiacol peroxidase, ascorbate peroxidase, ascorbic acid, monodehydroascorbate reductase, dehydroascorbate reductase, glutathione, and glutathione reductase; reactive oxygen species (ROS) such as hydrogen peroxide and superoxide radical; and lipid peroxidation as indicated by malondialdehyde were also measured. The results indicate that G. humilis tolerates elevated soil salinity induced by saline irrigation with an electrical conductivity of at least 6 dS m⁻¹, which results in stress responses without fatal consequences. Soil salinity induced by saline irrigation of 6 dS m⁻¹ reduced A_n and g_s by approximately 50% during a 30-day period, but there was no evidence of physiological damage based on the LCI or F_v/F_m. The levels of Na⁺ and Cl⁻ did not reach toxic levels, and the plants were able to prevent damaging imbalances of plant nutrients, indicating an ion-avoidance strategy. Increased antioxidant response to soil salinity induced by saline irrigation possibly prevented ROS and lipid peroxidation damage. G. humilis appears to be moderately tolerant of soil salinity induced by saline irrigation of at least 30 days at 6 dS m⁻¹. Full article

Mountain forests play a key role in buffering local climate, yet their climate sensitivity is seldom mapped in a way that is directly usable for spatial planning. This study investigates how phenological thermal and vegetation variability are organized within the forested landscape of Namyangju, a mountainous region in central Korea, and derives spatial indicators of forest climate sensitivity. Using monthly, cloud-screened Landsat-8/9 land surface temperature (LST) and normalized difference vegetation index (NDVI) images over a recent multi-year period, we calculated phenological coefficients of variation for 34,123 forest grid cells and applied local clustering analysis to identify belts of high and low variability. Forest areas where LST and NDVI variability simultaneously occupied the upper tail of their distributions (top 5%/10%/20%) were interpreted as climate-sensitivity hotspots, whereas co-located coldspots were treated as microclimatic refugia. Across the mountainous terrain, sensitivity hotspots formed continuous belts along high-elevation ridges and steep, dissected slopes, while coldspots were concentrated in sheltered valley floors. Notably, the most sensitive belts were dominated by high-elevation conifer stands, despite the limited seasonal fluctuation typically expected in evergreen canopies. This pattern suggests that elevation strongly amplifies the coupling between thermal responsiveness and vegetation health, whereas valley-bottom forests act as stabilizers that maintain comparatively constant microclimatic and phenological conditions. We refer to these patterns as “forest climate-sensitivity belts,” which translate satellite observations into spatially explicit information on where climate-buffering functions are most vulnerable or resilient. Incorporating climate-sensitivity belts into forest plans and adaptation strategies can guide elevation-aware species selection in new afforestation, targeted restoration and fuel-load management in upland sensitivity zones, and the protection of valley refugia that support biodiversity, thermal buffering, and hydrological regulation. Because the framework relies on standard satellite products and transparent calculations, it can be updated as new imagery becomes available and transferred to other seasonal, mountainous regions, providing a practical basis for climate-resilient forest planning. Full article