Phosphorus (P) is an essential nutrient for living systems and is critical to the functioning of ecosystems. Permafrost areas have a huge reservoir of soil P that is currently not used very much; however, the direction and magnitude of changes in soil P stocks across the Tibetan alpine permafrost regions over recent decades remain unclear and the P budget has not been well assessed. Here we use a unique combination of a soil resampling method and a modified process-balanced model to assess the historical dynamics of soil P pools (0–30 cm depth) and the key flows of P in ecosystems across Tibetan alpine permafrost region. Compared with the 1980s, the soil P stock decreases dramatically by 36.1% in the 2020 s, decreasing from 346.5 to 221.4 Tg P (1 Tg = 1012 g) during the last three decades. Water erosion accounts for 82.3% of the total soil P outflow. Our projections suggest that the soil P stock will only be 20.3% of the 1980s stock by the end of this century, leading to an unprecedented crisis of P limitation in permafrost regions.

The beet webworm Loxostege sticticalis (Lepidoptera: Pyralidae), is an invasive and polyphagous pest, posing a severe threat to food security, agriculture, and animal production. In this study, we examined the biological parameters of L. sticticalis on four host plants: white goosefoot, Chenopodium album (Caryophyllales: Amaranthaceae), sunflower, Helianthus annuus L (Asterales: Compositae), wheat, Triticum aestivum L (Poales: Poaceae), and soybean, Glycine max (L.) Merr. (Fabales: Fabales). Our research found that, compared with white goosefoot, sunflowers, and wheat significantly lengthened larval development time. Additionally, adults feeding on sunflowers, wheat, and soybeans exhibited reduced egg-laying and oviposition periods. After feeding on wheat, key population parameters of the insect, including net reproductive rate (R0), intrinsic growth rate (r), and mean generation time (T), declined markedly. However, parameters r and λ still indicated positive population growth. These findings demonstrate the impact of different host plants on the biology of L. sticticalis and highlight the potential risks to its survival and spread when feeding on various hosts. They provide valuable information for pest monitoring and the development of control strategies.

The fall armyworm (FAW), Spodoptera frugiperda (Lepidoptera: Noctuidae), is an important invasive migratory pest that poses a serious threat to global food security. However, behavioral and physiological responses to seasonal changes in photoperiod have received little attention in FAW. Here, we present behavioral evidence that FAW under shorter photoperiods (12L:12D and 10L:14D) exhibited stronger flight capacity and pathogen resistance to Beauveria bassiana compared to those under longer photoperiods (16L:8D and 14L:10D), but weaker reproductive performance. After prolonged flight, shorter photoperiods facilitated the reproduction of flying females compared to the controls (nonflying moths), while longer photoperiods suppressed reproduction. Short photoperiod reduced larval mortality and pupal weight of FAW but increased adult emergence rate. Our results indicate that shorter photoperiods enhance the migration propensity for improved survival in FAW, and provide insights into how photoperiod controls seasonal changes in behavior and physiology that lead to seasonal adaptation in this globally important pest.

Urban change detection based on remote sensing images holds significant importance in environmental monitoring and emergency management. However, it poses several challenges including large disparity errors, diverse types of changes, and a substantial difference between the number of changed and unchanged areas. In this study, we propose an efficient model called BiUnet-Dense for extracting deep features by integrating the advantages of Bi-Unet, Dense Block, and long short-term memory (LSTM) networks. Building upon the classical architecture of U-Net, Bi-Unet utilizes bi-temporal images to compare and extract features. The incorporation of modified dense connections reduces network parameters while mitigating gradient disappearance through maximizing feature reuse. Additionally, LSTM facilitates information transmission from earlier to later using cell states to provide more meaningful feature vectors. We implemented our model on two datasets: Onera Satellite Change Detection (OSCD) and Change Detection Data of Guangzhou (CD_Data_GZ). Quantitative and qualitative results demonstrate that our method significantly improves detection effectiveness with enhanced F1-score and Kappa while effectively reducing false-positive detections as well as identifying labeling errors.

Accurate detection of rice pests helps farmers take timely control measures. This study compares different attention mechanisms for rice pest detection in complex backgrounds and demonstrates that a human vision-inspired Bionic Attention (BA) mechanism outperforms most traditional attention mechanisms in this task and is applicable to all major mainstream and novel models. Bionic Attention (BA) assists the main branch in recognition by additionally labeling important features of each rice pest category and inputting the additional category labels as bionic information into the network during the input stage. This study applies Bionic Attention to dominant entity classical and novel networks, including YOLOv5s, YOLOv8n, SSD, Faster R-CNN, YOLOv9-e, and YOLOv10-X, and compares it with classical attention mechanisms such as CBAM, SE, and SimAM to verify its feasibility. Meanwhile, this study introduces more detailed evaluation metrics to assess Bionic Attention, including Classification Error, Localization Error, Cls and Loc Error, Duplicate Detection Error, Background Error, and Missed GT Error. Experimental results show that Bionic Attention improves detection performance by indirectly enhancing the loss function, allowing the model to acquire more fine-grained information during the feature extraction stage, thereby improving detection accuracy.

This study investigates the nonlocality characteristics of output states produced by a universal quantum cloning machine, with particular emphasis on the Bell-CHSH inequality violations exhibited by the two-qubit reduced states of cloned outputs. Through systematic analysis, we identify the parameter regimes where these reduced states can effectively serve as quantum channels for teleportation protocols. Our results demonstrate that within specific operational ranges of the cloning machine parameters, the two-qubit reduced states are suitable for quantum teleportation but do not exhibit violations of Bell-CHSH inequalities. Furthermore, we quantitatively characterize the monogamy relations governing Bell-CHSH violations in quantum cloning states across different parameter configurations, revealing fundamental constraints on nonlocality distribution in cloned quantum systems.

Topological insulators (TIs) can be widely applied in the fields of ultrafast optical and spintronic devices owing to the existence of topologically protected gapless Dirac surface states. However, the study of ultrafast dynamics of carriers in TIs remains elusive. In this work, the carrier dynamics of Li-doped Bi2-xSe3 single crystals were investigated by femtosecond (fs) transient optical spectroscopy (ΔR/R(t) signals). The temperature dependence for the relaxation rates of the electron-electron interaction and electron-phonon coupling is consistent with the results of electrical transport, which indicates the carrier dynamics of TI is highly related with carrier concentrations. We find that the carrier type and concentration of Bi2Se3 can be tuned by Li doping, leading to a metal-insulation transition at low temperatures (T ≤ 55 K), indicating that electron-electron interactions are dominant at low temperature. For T > 55 K, electron-phonon coupling in the bulk carriers becomes the main electric transport mechanism.