Search Results (995)

Ash dieback, together with altered hydrological conditions and limited natural regeneration, threatens narrow-leaved ash (Fraxinus angustifolia Vahl) forests in Croatian floodplains. This study evaluated whether individual-tree attributes and stand structure were associated with crown damage and short-term radial-growth resilience. Ten stands in the middle Sava River floodplain were sampled using 41 circular plots. Stand density, basal area, and growing stock were estimated at the plot level. Diameter, height, crown dimensions, and crown damage were assessed on a subsample of 154 trees, from which increment cores were also collected. Ring-width measurements were used to calculate the Resilience index (Rs_3/6). Relationships among variables were evaluated using linear correlation and one-way analysis of variance was used for testing differences in crown damage and resilience index between categorized tree and stand variables. Mean crown damage was 24.4%, while the mean Rs_3/6 value of 0.90 indicated that radial growth had generally not returned to its previous level. Crown damage was negatively correlated with growth resilience. Trees in the 15–30 cm diameter class and the 21–40-year age class showed the lowest crown damage and highest resilience. The most favorable values of both indicators occurred at stand densities of 800–1200 trees ha⁻¹, while crown damage was lowest at basal areas below 15 m² ha⁻¹. Although the observed associations were moderate and should not be interpreted as causal effects, the combined use of crown condition and radial-growth recovery can support the identification of vigorous trees and inform adaptive, site-specific management of declining narrow-leaved ash stands. Full article

Rapid and non-destructive monitoring of soil total nitrogen (STN) is important for precision nutrient management in ecologically fragile agricultural systems. This study established a controlled spectral resampling experiment to simulate the multispectral responses of Sentinel-2, WorldView-3, GF-6, and Landsat-9 from laboratory ASD hyperspectral measurements of Hemerocallis citrina fields. Two-dimensional (DI, RI, and NDI) and three-dimensional (TBI1–TBI5) spectral indices were constructed and evaluated using eight machine learning algorithms across five phenological stages. The results demonstrate that: (1) Three-dimensional spectral indices exhibited substantially higher sensitivity to STN than conventional two-dimensional indices, with TBI3 showing the strongest overall correlation; among the simulated sensor configurations, GF-6 delivered the best mean performance due to its dual red-edge bands. (2) Genetic algorithm-optimized backpropagation neural network (GA-BPNN) effectively addressed the local-minima limitation of standard backpropagation neural networks (BPNNs) and displayed robust generalization under multi-sensor and multi-phenological scenarios. (3) Phenology-specific modeling reduced spectral heterogeneity caused by pooling across growth stages, increasing R² by 20.28% and decreasing RMSE by 18.35%, with leaf expansion and bolting identified as optimal estimation windows. These findings elucidate the spectral response potential explanations of STN across phenological stages and provide a reference for applying multi-source simulated remote sensing data to nutrient monitoring in specialty agricultural systems. Full article

Chamaecyparis thyoides forested peatlands in the mid-Atlantic USA store carbon and enhance biodiversity but have declined through altered hydrology. Ditched sites shifted to temporarily flooded hydrologic regimes and were replaced by other forest types. Sites exposed to sea level rise (SLR) have persisted with a seasonally flooded, saturated hydrologic regime, but are transitioning to ghost forests. The purpose of this study is to aid conservation efforts by analyzing climate variable correlations with seasonal growth. Chamaecyparis thyoides tree rings from a ditched site exhibited overall faster growth rates, and earlywood was more sensitive to climate variables (temperature and Palmer Drought Severity Index, PDSI) than latewood. At a site exposed to SLR, division of early- and latewood chronologies was performed at the age midpoint, and growth responses in prior (1939–1970) and recent periods (1970–2003) diverged. Temperature and PDSI correlations with growth occurred in both early- and latewood, and patterns shifted between prior and recent periods. Stressors may include the timing of soil anoxia and shifts in availability of nonstructural carbon at both sites, and salinity at the SLR-impacted site. Climate and growth correlations at the SLR site may represent a form of reference for hydrologic restoration of seasonally flooded, saturated hydrologic regimes. Full article

Background: The genus Anchusa L. includes plants used in Uyghur medicine for their anti-inflammatory and analgesic effects. However, in China, the botanical origin of HERBA ANCHUSAE (Niushecao, a Uyghur medicinal herb) is severely confused. Traditional identification methods and standard DNA barcodes do not work well for these close relatives. Chloroplast genomes are known to contain variable regions that can help distinguish species, yet no such study has been done for Anchusa. Therefore, We compared the complete chloroplast genomes of six Anchusa species and the main adulterants of Niushecao. Methods: We analyzed genome structure, repeat sequences, codon usage bias, and nucleotide diversity (Pi), as well as conducted comparative and phylogenetic analyses. Results: All genomes shared a typical ring-shaped quadripartite structure, ranged from 150,178 to 150,844 bp in size, and contained the same set of genes. Despite this overall conservation, we identified several highly variable spots, mostly located in non-coding intergenic spacer regions. Using two complementary approaches—sliding window analysis and mVISTA-based sequence visualization—we identified three overlapping regions (rbcL-psaI, petA-psbJ, and trnC-GCA-petN) as candidate DNA barcodes for species identification. Our phylogenetic tree showed that Anchusa strigosa Banks & Sol. is most closely related to the true medicinal species Anchusa azurea Mill. (Bootstrap support (BS) = 100%), while other look-alikes formed separate branches. Conclusions: These findings provide the first chloroplast genomic resources for this genus and offer potential molecular markers for authenticating Anchusa medicinal materials, laying a foundation for future development of molecular authentication methods. Full article

This study investigated the effects of thinning intensity on tree radial growth and physiological responses to drought in an approximately 43-year-old Pinus koraiensis plantation. To analyze tree-ring width, a total of sixty wood cores (5 mm) were collected from three thinning treatments applied in 2007: control (Con), light thinning (LT), and heavy thinning (HT). Drought vulnerability indices were examined across three distinct drought periods (2000–2001, 2007, and 2014–2016), and intrinsic water use efficiency (WUE_i) was estimated from stable carbon isotope analysis (Con vs. HT). Thinning increased basal area increment (BAI) in both the LT and HT groups, with the strongest and most persistent response observed in the HT group. During the 2007 drought, trees in thinned plots, particularly those in the HT group, showed higher resistance and resilience than trees in the Con group. The increased indices during the 2000 and 2007 drought periods predominantly reflected immediate thinning-induced growth release. WUE_i in the HT group increased relative to the Con group during both the 2007 and 2014–2016 drought periods; however, the underlying physiological mechanisms differed, with enhanced net photosynthetic capacity immediately after thinning in 2007 and a likely consistent reduction in stomatal conductance during the 2014–2016 drought. Although constrained by a non-replicated stand design, this site-specific long-term case study provides valuable insights into the multi-decadal growth and physiological trajectories of conifer plantations responding to climate stress. Full article

Data-driven surrogate methods are increasingly applied to real-time structural health monitoring of critical engineering systems, but their use is often limited by the computational cost of high-fidelity finite element (FEM) simulations. This work proposes an FEM-based machine learning framework combining FEM, Principal Component Analysis (PCA), and Random Forest regression to reconstruct full-field von Mises stress distributions of a hydropower regulating ring from a reduced set of proximity sensor measurements. A calibrated 3D FEM model generated a representative dataset of operating conditions using a Design of Experiments (DOE) sampling strategy, reducing the simulation space. The resulting stress fields were reduced using a single global PCA model, and the retained principal components were predicted by a single Random Forest model trained on the guide vane opening and four displacement sensors installed on the turbine unit. Stress reconstruction was obtained via inverse PCA transformation and validated against FEM results through a leave-one-opening-out cross-validation, in which each guide vane opening was entirely withheld from training. The method achieved an average PSNR of 17.4 dB and SSIM of 0.837 across the eleven withheld openings, with 8 to 9 PCA components sufficient to preserve over 95% of the cumulative explained variance. A sensitivity analysis of the ensemble size showed that 100 decision trees provide accuracy comparable to larger ensembles at lower computational cost, and a feature importance analysis revealed the guide vane opening as the dominant predictor, with the four sensors providing complementary, fine-grained corrections. The framework enables near real-time reconstruction, requiring approximately 1.5 s per condition versus several hours for FEM. These results show that combining physics-based modeling with machine learning enables efficient structural monitoring for predictive maintenance and operational decision-making in hydroelectric systems. Full article

Under moderate-to-high wind conditions, low-frequency wind direction modulation signals in X-band marine radar images are strongly coupled with wave textures, sea clutter, and blind-zone interference, which degrades wind direction retrieval accuracy. To address this problem, this study proposes a wind direction retrieval method based on two-dimensional dual-tree complex wavelet transform (2D-DTCWT), convolutional sparse coding (CSC), and maximum-energy radial rings. First, 2D-DTCWT is used to suppress wave textures and local noise in the wavelet domain while enhancing low-frequency wind direction modulation signals. Then, K–singular value decomposition (K-SVD) learns the energy distribution characteristics of wind signals, and CSC obtains the spatial response distribution of wind energy in radar images. Finally, the maximum-energy radial ring is adaptively identified, and azimuthal energy statistics within this ring are fitted using a cosine-squared function. The proposed method was evaluated using X-band marine radar data collected during sea trials in the coastal waters of Zhejiang, China. On the 900-sample main validation dataset, the proposed method achieved the highest correlation coefficient (CC) of 0.85 and an overall root mean square error (RMSE) of 4.24°, reducing the RMSE by 43.0% and 66.7% compared with conventional single-curve fitting and extended-bow-heading DWT, respectively. The results demonstrate improved robustness under both upwind and downwind blind-zone conditions. Full article

The potential for species distribution shifts in response to changing climate and altered fire regimes is a pressing concern across ecosystems. Species responses to climate and disturbance are expressed demographically as changes in survivorship and recruitment across gradients. We examined tree recruitment and radial growth response to climate along a biophysical gradient in a mixed-conifer forest in northern New Mexico, USA, in a watershed spanning from near the lower to upper elevation range for ponderosa pine (Pinus ponderosa var. scopulorum Engelm.) and Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco). We compared growth responses with climate variables and stand demographic patterns of the six major tree species present, to track shifts in species community composition and dominance. We found significant changes in species composition between mature trees and seedlings and saplings across Elevation–Aspect groups in several species, indicating incipient community change. Drought stress drove patterns of tree growth and species composition shifts at low elevations, while at higher elevations increased stand density following fire exclusion led to success of shade-tolerant species. Altered growth and demographic trends driven by drought and fire exclusion can serve as the mechanism for changing species distributions and community reorganization across landscape climatic gradients. Full article

Assessing long-term hydroclimatic variability in central Mexico is essential to understand regional water availability and groundwater recharge for urban centers such as Querétaro. This study developed a multi-century winter–spring precipitation reconstruction for the Sierra Gorda Biosphere Reserve (SGBR) using ring width chronologies of Douglas-fir, Pseudotsuga menziesii (Mirb.) Franco. Standard dendrochronological techniques were applied to develop a 284-year master chronology (1731–2015). Following the accepted Subsample Signal Strength criterion (SSS ≥ 0.85) for chronology reliability, the reconstruction was restricted to the 1744–2015 period, yielding a statistically robust 271-year December–April precipitation record. A bootstrapped ordinary least-squares regression model relating tree-ring indices to instrumental December–April precipitation was calibrated and validated using split-sample cross-validation, explaining 46% of the instrumental precipitation variance (R² = 0.46) and yielding positive verification statistics (RE = 0.38–0.58; CE = 0.37–0.57). Spatial field correlations against gridded climate data (CRU TS4.08) confirmed a broad regional hydroclimatic signal centered over the Sierra Madre Oriental. Continuous wavelet transform (CWT), spectral analysis, superposed epoch analysis (SEA), and wavelet coherence (WTC) revealed significant interannual (2–8 years) and decadal (10–20 years) variability associated with large-scale ocean–atmosphere climate modes, including the El Niño–Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), Atlantic Multidecadal Oscillation (AMO), and Tropical North Atlantic (TNA) index. The pronounced sensitivity of these conifer forests to pre-monsoonal moisture deficits highlights their vulnerability to projected warming and increasing spring evapotranspiration stress. Although the reconstruction is limited to pre-monsoonal (December–April) precipitation, it provides a robust centuries-long baseline for contextualizing regional hydroclimatic variability and supports water-resource management, groundwater conservation, and climate-adaptation strategies in central Mexico. Full article

Main memory carries data outside the processor’s trust boundary, so commodity systems-on-chip (SoCs) increasingly encrypt it; yet, in-line memory encryption engine itself becomes a differential power analysis (DPA) target whose key, if recovered, unlocks all of dynamic random-access memory (DRAM). We present PACE, a page-adaptive, cache-anchored memory encryption engine for RISC-V that makes nth-order DPA resistance practical and keeps cryptographic latency off the cache eviction critical path. PACE inserts a TileLink adapter between the last-level cache and the memory port and applies, per physical page, one of four policies (plaintext/confidentiality/confidentiality+integrity/+masking-order-d) selected from RISC-V page table bits through a memory-mapped control plane. Confidentiality uses counter mode whose per-line keystream is precomputed during cache residency; integrity is tree-free at the embedded operating point via on-chip counters and tags, with a live split counter block-MAC Bonsai Merkle tree for scale-out. DPA resistance is layered: ISAP-style fresh re-keying caps the data complexity per key at $q\approx 1$, and domain-oriented masking (DOM, d + 1 shares) protects the sole key processing block to order d. We implement PACE in Chisel on a Rocket SoC (Chipyard) and evaluate it with open-source tooling. A deterministic TileLink-level harness proves ciphertext-in-memory and detects tamper/replay/splice, and the live Tier-B engine (DRAM counters and per-line message authentication codes (MACs) plus an on-chip-rooted block-MAC tree) is validated from end to end on full Rocket and BOOM SoCs and on the FPGA; the masked Ascon-p S-box is proven order-d secure (d = 1, 2) under a glitch- and transition-aware model by three independent formal tools (COCO, PROLEAD, and SILVER, the last also deciding the full composability lattice and confirming exact glitch-robust order-2 probing security), with COCO extending the exact verdict to the highest synthesized order d = 3 (secure at probing orders 1–3); a simulated trace correlation power analysis (CPA) recovers the full key from an unprotected core and is defeated by masking, with a mutual information analysis confirming the $N\propto {\sigma }^{2(d+1)}$ trace amplification law. We further realize PACE on field-programmable gate array (FPGA) silicon: the engine plus an on-chip ring oscillator power sensor is placed, routed, timing-closed at 100 MHz, and programmed on a Xilinx XC7Z020, and we drive a fixed-vs-random Test Vector Leakage Assessment (TVLA) campaign read back entirely over a JTAG (Joint Test Action Group). A multi-core configuration and a Linux control-plane driver are likewise validated. Across synthetic access patterns and named application kernels (AES, SHA-256, matrix multiplication, pointer chasing) on both in-order Rocket and out-of-order BOOM, application-level overhead is within measurement noise of plaintext for cache resident workloads (masking, in particular, is cycle-identical to plain confidentiality), and we characterize the cost of each policy, masking order, and re-keying interval, demonstrating side-channel-hardened memory encryption on open RISC-V hardware. Full article

Norway spruce (Picea abies L.) growing in mountain forests is a sensitive indicator of environmental change, but its growth response may be strongly modified by local site conditions, which is important for sustainable forest management under climate change. This study examined two spruce populations in the upper montane zone of the Śnieżnik Massif, Eastern Sudetes, southwestern Poland: one growing on a raised bog (Sadzonki—TS) and the other on mineral soil (Owczarnia—OW). Tree-ring width (TRW) chronologies were developed from 59 sampled trees represented by increment cores and stem discs, covering 1781–2023 for TS and 1800–2023 for OW. Annual δ¹³C analysis was performed for a selected TS tree, and decadal wood geochemistry was analyzed for a selected disc. Spruces growing on the raised bog showed tree-ring widths that were less than half those of trees growing on mineral soil. TRW was mainly controlled by summer or spring–summer temperature, while precipitation had a stronger positive effect at the mineral-soil site. δ¹³C showed weak relationships with TRW but negative correlations with mean annual and summer temperature. Elevated concentrations of Na, K, Ca, Mg, Fe, Mn, Cu, Zn, and Pb occurred mainly in 1941–1950 and 1971–1980, indicating the influence of historical air pollution. The contrasting growth trends and health status of the two populations demonstrate that local habitat conditions strongly shape spruce responses to environmental change and should be considered in sustainable mountain forest conservation and adaptation strategies. Full article

Climate change is increasing drought frequency and severity in Central Europe, with consequences for the productivity and stability of mixed broadleaf forests. We analyzed annual radial growth of European beech (Fagus sylvatica L.) and sessile oak (Quercus petraea (Matt.) Liebl.) along a water-availability gradient on the Swabian Alb (southwestern Germany). At three nearby sites, 45 trees per species were sampled. Tree-ring chronologies were related to meteorological variables and integrated drought indices (PDSI/scPDSI, SMI). Extreme dry and wet years were identified from detrended growing-season indices, and event responses were quantified using resistance, recovery, and resilience metrics and their humid-year analogues. Annual growth variation was primarily site-driven rather than species-driven, highlighting strong control by local soil water availability. Correlation analyses showed that integrated drought and soil-moisture indices explained radial growth more consistently than single climate variables. Oak showed higher drought resistance than beech in several events, although the magnitude and significance of this difference depended on site and drought year. Resistance generally declined toward recent events, particularly at Site 2, while recovery tended to increase. Recovery did not consistently favor either species, and resilience remained broadly stable, except for a decline in beech during the most recent drought events. Overall, sensitivity to drought is jointly controlled by species identity and fine-scale site conditions: oak has a comparatively robust resistance advantage, whereas post-drought recovery and resilience are strongly context-dependent. These findings support site-specific species mixtures and silvicultural strategies to sustain forest function under increasing drought risk. Full article

To elucidate the response characteristics of radial growth and water use strategies in coniferous forests of cold-arid regions to drought stress, this study focused on Larix sibirica in different forestry areas of the Altai Mountains. Using dendrochronology and stable isotope techniques, we calculated the basal area increment (BAI) and intrinsic water-use efficiency (iWUE), and combined these with the standardized precipitation–evapotranspiration index (SPEI) to identify drought events, to investigate tree growth and water-use efficiency responses to climate variability. The results showed that drought years were characterized by reduced radial growth and increased iWUE in Larix sibirica across both forest regions, and tree-ring-derived intercellular CO₂ concentration (Ci) increased with rising atmospheric CO₂ concentrations, whereas the Ci/Ca ratio remained relatively stable throughout the study period. Scenario analysis revealed that, prior to 1980, the long-term trend in iWUE was more consistent with the constant Ci scenario, suggesting relatively strong stomatal regulation. After 1980, iWUE trends became more closely aligned with the constant Ci/Ca scenario, indicating that trees maintained a relatively stable Ci/Ca ratio to balance carbon assimilation and water loss. With increasing drought severity, drought resistance declined in both forest regions; however, substantial spatial differences were observed in drought responses. Under moderate drought conditions, trees in the Haba-River forest area exhibited higher resistance, whereas trees in the Hanaslin forest area showed greater recovery capacity and ecological resilience. Winter temperature, growing-season temperature, late-season temperature, and water availability were identified as key climatic factors influencing variations in the radial growth and iWUE of Larix sibirica. Overall, under the combined influences of rising atmospheric CO₂ concentrations and increasing water limitations, Larix sibirica exhibited adaptive adjustments in carbon–water regulation; however, enhanced iWUE did not fully compensate for the negative effects of drought on radial growth. These findings provide valuable insights into the responses and adaptive strategies of cold-arid forest ecosystems under ongoing climate change and offer scientific support for the conservation and sustainable management of Larix sibiric forests. Full article

Tree-ring chronologies are essential proxies for investigating ecosystem dynamics and reconstructing environmental variability, yet integrative approaches for assessing chronology quality and sampling representativeness across heterogeneous regions remain limited. We analyzed 190 tree-ring chronologies distributed across Mexico and developed two composite indicators: the Signal Quality Index (SQI), integrating internal coherence, interannual sensitivity, common growth signal strength, and the Sampling Representativeness Index (SRI), quantifying the statistical adequacy of sampling efforts. Both indices were standardized and evaluated using Moran’s I, Local Indicators of Spatial Association (LISA), Getis–Ord Gi* hotspot analysis, and correlations with climatic, hydrological, and edaphic variables. Results revealed a marked decoupling between chronology signal quality and sampling representativeness. SQI exhibited significant positive spatial autocorrelation, with clusters of high and low values associated with hydroclimatic gradients. It was strongly related to indicators of water availability and atmospheric evaporative demand, suggesting greater growth coherence under water-limited conditions. In contrast, SRI displayed weak spatial structure and largely non-significant relationships with environmental variables, indicating that representativeness is driven primarily by methodological decisions and sampling design. These findings highlight complementary ecological (SQI) and methodological (SRI) dimensions of dendrochronological networks and provide a practical framework for improving chronology evaluation, comparability, and network development across environmentally heterogeneous regions. Full article

Background: Extreme drought and flood events continuously threaten the stability of forest and crop production. Long-term hydrological records derived from tree-ring anatomical proxies provide critical evidence for revealing historical drought hazard differentiation. Methods: Cell wall thickness chronologies of Betula platyphylla (northern forest) and Picea koraiensis (southern agro-pastoral zone) were developed to reconstruct nearly 300-year annual runoff sequences. Pearson correlation, quadratic regression, wavelet transform and superposed epoch analysis (SEA) were applied to quantify hydrological evolution, periodic signals, large-scale climate forcing and statistical coupling between dry/wet extremes and historical yield reduction records. Results: The northern watershed showed stronger interannual runoff oscillation. Both regions entered persistent low-flow phases post-1950. Pacific Decadal Oscillation (PDO) acted as the dominant driver, while solar radiation exerted weak secondary regulation. Severe drought events corresponded closely to historical forest and grain yield losses, with far higher agricultural vulnerability in the southern agro-pastoral ecotone. Conclusions: This study reconstructed the long-term historical runoff of the Greater Khingan Range from the thickness of the cell wall, analyzed the different impacts of PDO on it, and clarified the differentiated effects of drought and flood on agricultural and forestry production losses and the interrelated impact of land use on hydrology and the value of agricultural output. Full article