Search Results (1,471)

Marine shelled organisms exhibit diverse growth strategies shaped by species-specific traits and environmental conditions that critically influence their ecological roles, particularly within Marine Animal Forests (MAF), which are structurally complex habitats and biodiversity-rich habitats. This review compiles and compares empirical growth data for 16 bivalve and gastropod species across seven families, classified as full MAF contributors (Pinna nobilis, Flexopecten glaber, Pecten maximus, and Placopecten magellanicus), partial MAF contributors (Cerastoderma edule, C. glaucum, Chamelea gallina, Ruditapes philippinarum, Mercenaria mercenaria, Panopea generosa, Anadara kagoshimensis, A. inaequivalvis, and Tegillarca granosa), and ecologically relevant non-MAF species (Buccinum undatum, Hexaplex trunculus, and Rapana venosa). Age estimation methods included direct techniques, such as shell growth ring and opercular annulus analysis, alongside indirect approaches, such as length-frequency analysis, stable isotope profiling, and mark–recapture studies. Growth trajectories were modelled using von Bertalanffy growth function (VBGF) parameters to estimate the shell size from ages 1 to 4. Based on these estimates, species were categorised into slow, moderate, fast, and exceptional growth groups. These classifications were further explored through hierarchical clustering that grouped species according to their VBGF-derived growth values, revealing consistent and contrasting life history strategies. This comparative analysis should enhance the understanding of molluscan growth dynamics and support the conservation and management of MAF-associated ecosystems by informing restoration planning, guiding species selection, and contributing to evidence-based policy development. Full article

Urban forests provide many ecosystem services in urbanized landscapes, including biodiversity conservation. The sustainable management of urban forests requires a thorough understanding of biodiversity changes in the context of rapid urbanization. As biodiversity in rapidly changing urban areas is very dynamic, we need a better understanding of long-term biodiversity changes in urban forests. Birds are very good bioindicators of urban forest biodiversity because they are strongly habitat-sensitive. However, a major knowledge gap exists in long-term trends in bird diversity in temperate urban forests. This study analyzed a comparison of bird-species richness in a temperate Central European urban forest over a time span of 37 years. Bird-counts using the standard line-transect method conducted in 2023–2024 were compared with older field data from 1987 gained using the same method in a lowland hardwood floodplain forest in the Czech Republic. The results revealed significant faunistic similarities in the bird-species diversity of an urban forest during the 1987–2024 period. The high local alpha diversity of the bird community (42 nesting bird species) as well as the relatively high long-term stability in bird richness indicated the importance of the studied urban forest as a stable biodiversity refugium in a dynamic urbanized landscape. Therefore, urban forests can be considered very stable biodiversity refugia in dynamically changing urban areas. Full article

Artificial reefs serve as a crucial measure for preventing habitat degradation, enhancing primary productivity in marine areas, and restoring and increasing fishery resources, making them an essential component of marine ranching development. Accurate identification and detection of artificial reefs are vital for ecological conservation and fishery resource management. To achieve precise segmentation of artificial reefs in multibeam sonar images, this study proposes an improved YOLOv11-based model, YOLO-AR. Specifically, the DCCA (Dynamic Convolution Coordinate Attention) module is introduced into the backbone network to reduce the model’s sensitivity to complex seafloor environments. Additionally, a small-object detection layer is added to the neck network, along with the ultra-lightweight dynamic upsampling operator DySample (Dynamic Sampling), which enhances the model’s ability to segment small artificial reefs. Furthermore, some standard convolution layers in the backbone are replaced with ADown (Advanced Downsampling) to reduce the model’s complexity. Experimental results demonstrate that YOLO-AR achieves an mAP@0.5 of 0.912, an intersection-over-union (IOU) of 0.832, and an F1 score of 0.908. Meanwhile, the parameters and model size of YOLO-AR are 2.67 million and 5.58 MB. Compared to other advanced segmentation models, YOLO-AR maintains a more lightweight structure while delivering a superior segmentation performance. In real-world multibeam sonar images, YOLO-AR can accurately segment artificial reefs, making it highly effective for practical applications. Full article

The rapid expansion of transportation infrastructure on Hainan Island has intensified ecological pressures such as landscape fragmentation and decreased connectivity, threatening the environmental integrity of Hainan Tropical Rainforest National Park. As China’s only tropical island national park, it is important to maintain biodiversity and ecological resilience. Therefore, this study attempts to examine the park and its 5 km buffer zone to assess how transport expansion from 2003 to 2023 has altered land use patterns and landscape connectivity. Through the analysis of multi-period land use data, the land use changes are tracked by using ArcGIS and Fragstats 4.3 software, and the landscape dynamics are quantified. We linked these patterns to ecological processes via a resistance-surface model, which is further refined by spatial structural indices to better reflect ecological realism. Ecological sources were subsequently identified through morphological analysis and ecosystem service evaluation, and circuit theory was applied to delineate potential corridors and construct an ecological security network. The results indicate that (1) transportation development has significantly increased landscape fragmentation and ecological resistance, particularly along major highways; (2) while core forest areas inside the park remain relatively intact, the buffer zones show accelerating degradation; and (3) Although there are many ecological conflict points between the transportation network and the ecological corridor, the construction of animal channels in combination with bridges, tunnels and culverts can effectively improve ecological connectivity and protect the integrity of animal habitat. These findings highlight the vulnerability of ecological integrity as the network expands. The proposed modeling framework provides a more realistic assessment of infrastructure impact and offers a scientific basis for coordinating ecological protection and transport planning in tropical island national parks. Full article

The process of social globalization and urbanization has developed rapidly in China, and the tension between economic development and the eco-environment is becoming increasingly tense, posing a major challenge to the sustainable development strategy of the Shandong Peninsula Urban Agglomeration (SPUA). Coordination development between economic development and habitat quality has become essential for preserving ecological stability and advancing long-term regional sustainability. This study constructed the optimal regression model to measure GDP density using night-time lighting data and economic statistical data and calculated habitat quality at the grid scale with the InVEST model. The spatiotemporal dynamics and driving factors of the coupling coordination between economy and habitat quality (EHCCD) were revealed using the coupling coordination degree model and the Geo-detector model. The results show that (1) between 2000 and 2020, the spatial pattern of GDP density has evolved from a single-core to a multi-core networked development. (2) The habitat quality of the SPUA exhibited a spatial pattern high in the east and low in the west, showing a downward trend. (3) The synergistic effect between GDP density and habitat quality was strengthened continuously, showing an overall strengthening tendency. (4) Driving factors’ influence on the EHCCD showed evident differences; socio-economic factors such as built-up area especially had greater explanatory power for the EHCCD; the interaction factors had shifted from socio-economic dominance to synergistic dominance of natural and human factors. This study not only overcomes the limitations imposed by administrative boundaries on assessing inter-regional coupling coordination but also provides fundamental data support for cross-regional cooperation, thereby advancing the sustainable development goal of the SPUA. Full article

This study employs a systems theory approach to investigate the coupling coordination and driving mechanisms within the economic–social–environmental (ESE) system in China’s ethnic regions. It analyzes 67 ethnic counties in Sichuan Province, using an integrated framework that combines dynamic Shannon entropy, coupling coordination modeling, and GeoDetector. Based on data from 2005 to 2024, the study reveals the spatiotemporal patterns of ESE coupling coordination. The key findings are as follows: (1) The coupling coordination degree has gone through four stages: moderate imbalance → mild imbalance → primary coordination → moderate coordination. By 2024, 81.8% of counties had achieved coordinated development, and “highly coordinated” counties emerged for the first time. (2) The Western Sichuan Plateau has formed a high–high agglomeration zone by monetizing ecological assets and utilizing ethnic cultural resources. In contrast, the hilly and parallel ridge–valley regions in central and eastern Sichuan remain in low–low agglomerations due to their dependency on traditional industrialization paths. The decrease in high–low and low–high outliers indicates the recent policy polarization effects. (3) The interaction between habitat quality and per capita GDP has the strongest explanatory power. The rising marginal contributions of energy and carbon emission intensity suggest that green industrialization is crucial to breaking the “poverty–pollution” trap. Full article

Forest fires pose severe ecological, climatic, and socio-economic threats, destroying habitats and emitting greenhouse gases. Early and timely warning is particularly challenging because fires often originate from small-scale, low-temperature ignition sources. Traditional monitoring approaches primarily rely on single-source satellite imagery and empirical threshold algorithms, and most forest fire monitoring tasks remain human-driven. Existing frameworks have yet to effectively integrate multiple data sources and detection algorithms, lacking the capability to provide continuous, automated, and generalizable fire monitoring across diverse fire scenarios. To address these challenges, this study first improves multiple monitoring algorithms for forest fire detection, including a statistically enhanced automatic thresholding method; data augmentation to expand the U-Net deep learning dataset; and the application of a freeze–unfreeze transfer learning strategy to the U-Net transfer model. Multiple algorithms are systematically evaluated across varying fire scales, showing that the improved automatic threshold method achieves the best performance on GF-4 imagery with an F-score of 0.915 (95% CI: 0.8725–0.9524), while the U-Net deep learning algorithm yields the highest F-score of 0.921 (95% CI: 0.8537–0.9739) on Landsat 8 imagery. All methods demonstrate robust performance and generalizability across diverse scenarios. Second, data-driven scheduling technology is developed to automatically initiate preprocessing and fire detection tasks, significantly reducing fire discovery time. Finally, an integrated framework of multi-source remote sensing data, advanced detection algorithms, and a user-friendly visualization interface is proposed. This framework enables all-weather, fully automated forest fire monitoring and early warning, facilitating dynamic tracking of fire evolution and precise fire line localization through the cross-application of heterogeneous data sources. The framework’s effectiveness and practicality are validated through wildfire cases in two regions of Yunnan Province, offering scalable technical support for improving early detection of and rapid response to forest fires. Full article

The gut microbiota of red deer is a topic of growing interest, particularly with regard to its ecological and physiological importance. The diversity and composition of these microbial communities is influenced by environmental variables, diet and interactions with other organisms in their habitat. Fecal samples were collected in 10 hunting reserves in the Friuli-Venezia Giulia region, Italy. In each hunting reserve, five individual samples were taken from the ground for a total of 50 samples. After DNA extraction, the V3–V4 16s rRNA regions were sequenced. The raw data were uploaded to QIIME2 and taxonomic annotation was performed. Significant differences between the deer sampled in the hunting reserves (p < 0.05) were calculated for the phyla Firmicutes and Cyanobacteriota and for the ratio of Firmicutes to Bacteroidota, especially for the mountain reserves in the north and northeast compared to the reserves in the hills in the west. Shannon and Chao1 alpha diversity indices varied between reserves (p < 0.01) and the Bray–Curtis beta diversity index also indicated differences in microbiota between hunting reserves. The different habitats and vegetation of the reserves could explain the differences observed. Understanding the dynamics of the microbiota of red deer provides important information about their health and feeding behavior and also has far-reaching implications for species conservation. Full article

Insect pests impose major economic, agricultural, and public health burdens, damaging crops and transmitting pathogens such as dengue, malaria, and Zika. Conventional chemical control is increasingly ineffective due to insecticide resistance and environmental concerns, prompting a search for innovative strategies. The insect microbiome—comprising both obligate symbionts and environmentally acquired microbes—emerges as a key driver of host physiology and behavior. Microbes influence nutrient acquisition, immunity, reproduction, and chemosensory processing, often to promote their own transmission. By modulating olfactory and gustatory pathways, microbiota can alter host-seeking, mate choice, foraging, and oviposition patterns, reshaping ecological interactions and vector dynamics. These effects are shaped by microbial acquisition routes, habitat conditions, and anthropogenic pressures such as pesticide use, pollution, and climate change. Understanding these multi-directional interactions offers opportunities to design highly specific, microbe-based insect control strategies, from deploying microbial metabolites that disrupt host sensory systems to restoring beneficial symbionts in threatened pollinators. Integrating microbiome ecology with insect physiology and behavior not only deepens our understanding of host–microbe coevolution but also enables the development of sustainable, targeted alternatives to chemical insecticides. This review synthesizes current evidence linking microbiomes to insect biology and explores their potential as tools for pest and vector management. Full article

Assessing habitat quality and quantifying human disturbance are fundamental prerequisites for ecological conservation. However, existing studies predominantly focus on single dimensions. There is an urgent need to integrate habitat quality and human disturbance, and quantify their spatially coupled coordination relationships to address the disconnect between them in current research. As a critical ecological reserve in southeastern China, Fujian Province faces threats of ecological degradation. This study employed the InVEST model to evaluate habitat quality in Fujian from 1980 to 2020, utilized a human disturbance index to quantify spatiotemporal patterns of anthropogenic activities, analyzed their changes using landscape indices, and applied coupling coordination analysis to examine their interrelationships. Machine learning and geographically weighted regression were further integrated to identify driving factors of coupling coordination patterns. The results showed that: (1) Habitat quality remained relatively high while human disturbance levels stayed low throughout 1980–2020, though both showed gradual deterioration over time, particularly during 2010–2020, with riverine and coastal eastern regions exhibiting the lowest habitat quality and highest disturbance levels. (2) Coupling coordination relationships predominantly exhibited synergy, with moderate imbalance zones concentrated in the eastern coastal areas. Temporally, regions with lower imbalance expanded significantly during 2010–2020. (3) Landscape metric analysis revealed declining dominance of high-quality habitat/low-disturbance/synergistic zones, contrasted by increased fragmentation of low-quality habitat/high-disturbance/imbalanced zones. (4) Socioeconomic factors exerted stronger influence on coupling coordination patterns than natural environmental variables, proximity to urban areas, road density, and nighttime light indices. Each driver displayed spatially variable positive/negative effects. The results enhance our understanding of human–nature sustainable development dynamics, urban expansion–ecological conservation trade-offs, and provide methodological insights for regional ecological management and achieving sustainable development goals. Full article

This review considers fundamental issues related to the genomics of birds (Aves), including the special organization and evolution of their chromosomes. In particular, we address the capabilities of molecular genetic/genomic approaches to clarify aspects of their evolutionary history, including how they have adapted to multiple habitats. We contemplate general genomic organization, including the small size and typical number of micro/macrochromosomes. We discuss recent genome sequencing efforts and how this relates to cytogenomic studies. We consider the emergence of this unique organization ~245 million years ago, examining examples where the “norm” is not followed. We address the functional role of synteny disruptions, centromere repositioning, repetitive elements, evolutionary breakpoints, synteny blocks and the role of the unique ZW sex chromosome system. By analyzing the cytogenetic maps and chromosomal rearrangements of eight species, the possibility of successfully applying modern genomic methods/technologies to identify general and specific features of genomic organization and an in-depth understanding of the fundamental patterns of the evolution of avian genomes are demonstrated. An interpretation of the observed genomic “variadicity” and specific chromosomal rearrangements is subsequently proposed. We also present a mathematical assessment of cross-species bacterial artificial chromosome (BAC) hybridization during genomic mapping in the white-throated sparrow, a species considered a key model of avian behavior. Building on model species (e.g., chicken), avian cytogenomics now encompasses hundreds of genomes across nearly all families, revealing remarkable genomic conservation with many dynamic aspects. Combining classical cytogenetics, high-throughput sequencing and emerging technologies provides increasingly detailed insights into the structure, function and evolutionary organization of these remarkable genomes. Full article

Spilled hydrocarbons released from oil pipeline accidents can result in long-term environmental contamination and significant damage to habitats. In this regard, evaluating actions in response to vulnerability scenarios is fundamental to emergency management and groundwater integrity. To this end, understanding the trajectories and their influence on the various parameters and characteristics of the contaminant’s fate through accurate numerical simulations can aid in developing a rapid remediation strategy. This paper develops a numerical model using the CactusHydro code, which is based on a high-resolution shock-capturing (HRSC) conservative method that accurately follows sharp discontinuities and temporal dynamics for a three-phase fluid flow. We analyze nine different emergency scenarios that represent the breaking of a diesel oil onshore pipeline in a porous medium. These scenarios encompass conditions such as dry season rupture, rainfall-induced saturation, and varying pipeline failure pressures. The influence of the spilled oil pressure and water saturation in the unsaturated zone is analyzed by following the saturation contour profiles of the three-phase fluid flow. We follow with the high-accuracy formation of shock fronts of the advective part of the migration. Additionally, the mass distribution of the expelled contaminant along the porous medium during the emergency is analyzed and quantified for the various scenarios. The results obtained indicate that the aquifer contamination strongly depends on the pressure outflow in the vertical flow. For a fixed pressure value, as water saturation increases, the mass of contaminant decreases, while the contamination speed increases, allowing the contaminant to reach extended areas. This study suggests that, even for LNAPLs, the distribution of leaked oil depends strongly on the spill pressure. If the pressure reaches 20 atm at the time of pipeline failure, then contamination may extend as deep as two meters below the water table. Additionally, different seasonal conditions can influence the spread of contaminants. This insight could directly inform guidelines and remediation measures for spill accidents. The CactusHydro code is a valuable tool for such applications. Full article

Although significant progress has been made in the conservation of Père David’s deer (Elaphurus davidianus) populations, rapid population growth in coastal wetlands has caused severe habitat degradation. This highlights the urgent challenge of balancing ungulate population dynamics with wetland restoration efforts, particularly considering the limited data available on post-disturbance ecosystem recovery in these environments. In this study, we evaluated soil quality and bacterial community dynamics at an abandoned feeding site and a nearby control site within the Dafeng Milu National Nature Reserve during 2020–2021. The goal was to provide a theoretical basis for the ecological restoration of Père David’s deer habitat in coastal wetlands. The main findings are as follows: among the measured indicators, bulk density (BD), soil water content (SWC), sodium (Na⁺), total carbon (TC), total nitrogen (TN), total phosphorus (TP), available potassium (AK), microbial biomass nitrogen (MBN), and the Chao index were selected to form the minimum data set (MDS) for calculating the soil quality index (SQI), effectively reflecting the actual condition of soil quality. Overall, the SQI at the feeding site was lower than that of the control site. Based on the composition of bacterial communities and the functional prediction analysis of bacterial communities in the FAPROTAX database, it is shown that feeding sites are experiencing sustained soil carbon loss, which is clearly caused by the gathering of Père David’s deer. Co-occurring network analyses demonstrated the structure of the bacterial community at the feeding site was decomplexed, and with a lower intensity than the control. In RDA, Na⁺ is the main soil property that affects bacterial communities. These findings suggest that the control of soil salinity is a primary consideration in the development of Père David’s deer habitat restoration programmes, followed by addressing nitrogen supplementation and carbon sequestration. Full article

Arbuscular mycorrhizal (AM) fungi can have complicated interactions with plants and soils, which play a critical role in mediating the soil carbon cycle. However, the mechanism by which AM fungi regulate soil respiration is not well documented. This study conducted a completely randomized block-design mesocosm experiment using the inoculation of AM fungi (RI: Rhizophagus intraradices; FM: Funneliformis mosseae) with Fraxinus malacophylla to identify the pathways of AM fungi controlling soil respiration in a rocky desertification habitat. We observed that the average soil respiration rates (3.78 μmol·m⁻²·s⁻¹) were significantly higher in two AM fungi inoculation treatments than in the control (2.87 μmol·m⁻²·s⁻¹). Soil respiration rates were 1.59-fold higher in RI fungi inoculation and 1.05-fold higher in FM inoculation than in the control. Explanation rates of microbial biomass carbon, biomass nitrogen, and root biomass in RI (57.46–76.49%) and FM (44.81–62.62%) inoculation for soil respiration variation were higher than those in the control (24.51–34.32%). The direct positive pathway of soil respiration was mainly regulated by microbial biomass (59.5%) and root biomass (34.90%), while the indirect positive contributions of soil physicochemical properties (30.00%), colonization level (3.50%), soil microclimate (19.30%), and enzyme activity (3.38%) to respiration dynamics ranked second. Thus, we conclude that soil respiration dynamics can be mainly controlled by AM fungi-mediated changes in microbial and root biomass in rocky desertification areas. Full article

Forest disturbance is a major driver shaping the structure and function of plantation ecosystems. Current research predominantly focuses on single forest types or landscape scales. However, species-level fine-scale assessments of disturbance dynamics are still scarce. In this study, we investigated Chinese fir (Cunninghamia lanceolata), Armand pine (Pinus armandii), and Yunnan pine (Pinus yunnanensis) plantations in the mountainous eastern Yunnan Plateau. We developed a Spatial Coupling Framework of Disturbance Legacy (SC-DL) to systematically elucidate the spatial associations between contemporary species distribution patterns and historical disturbance regimes. Using the Google Earth Engine (GEE) platform, we reconstructed pixel-level disturbance trajectories by integrating long-term Landsat time series (1993–2024) and applying the LandTrendr algorithm. By fusing multi-source remote sensing features (Sentinel-1/2) with terrain factors, employing RFE, and performing a multi-model comparison, we generated 10 m-resolution species distribution maps for 2024. Spatial overlay analysis quantified the cumulative proportion of the historically disturbed area and the spatial aggregation patterns of historical disturbances within current species ranges. Key results include the following: (1) The model predicting disturbance year achieved high accuracy (R² = 0.95, RMSE = 2.02 years, MAE = 1.15 years). The total disturbed area from 1993 to 2024 was 872.7 km², exhibiting three distinct phases. (2) The random forest (RF) model outperformed other classifiers, achieving an overall accuracy (OA) of 95.17% and a Kappa coefficient (K) of 0.93. Elevation was identified as the most discriminative feature. (3) Significant spatial differentiation in disturbance types emerged: anthropogenic disturbances (e.g., logging and reforestation/afforestation) dominated (63.1% of total disturbed area), primarily concentrated within Chinese fir zones (constituting 70.2% of disturbances within this species’ range). Natural disturbances accounted for 36.9% of the total, with fire dominating within the Yunnan pine range (79.3% of natural disturbances in this zone) and drought prevailing in the Armand pine range (71.3% of natural disturbances in this zone). (4) Cumulative disturbance characteristics differed markedly among species zones: Chinese fir zones exhibited the highest cumulative proportion of disturbed area (42.6%), with strong spatial aggregation. Yunnan pine zones followed (36.5%), exhibiting disturbances linearly distributed along dry–hot valleys. Armand pine zones showed the lowest proportion (20.9%), characterized by sparse disturbances within fragmented, high-altitude habitats. These spatial patterns reflect the combined controls of topographic adaptation, management intensity, and environmental stress. Our findings establish a scientific basis for identifying disturbance-prone areas and inform the development of differentiated precision management strategies for plantations. Full article