Search Results (6,559)

Understanding the spatial morphology and geographic adaptability of traditional settlements is crucial for their preservation and management. Accordingly, this study employs Hehuang region, China, as a case study, adopting an integrated approach that combines morphological type analysis and boundary shape index. This comprehensive methodology systematically investigates the spatial morphological features and reveals the geographic adaptability of the two types of traditional villages, which are river valley and mountain types. Specifically, the results demonstrate that: (1) The boundary morphology of river valley-type traditional villages is primarily composite, with a regular and compact overall tendency, creating a spatial pattern consisting of mountains and water bodies surrounding farmland and villages, which conveniently supports agricultural production. Their streets and alleys are mainly fishbone-shaped, dendritic, and grid-shaped. (2) Mountain-type traditional villages also exhibit composite boundary morphology but with lower compactness, higher fragmentation, and more pronounced belt-shape characteristics. Their spatial pattern facilitates agriculture and animal husbandry, with streets and alleys being predominantly grid-shaped, S-shaped, and Z-shaped. (3) The spatial morphology of both types of villages is well-adapted to local terrain and climate conditions, as well as to the resident’s requirements for water use and disaster prevention, which reflects the wisdom of the Hehuang region’s ancestors regarding settlement construction. This study contributes to comprehending the spatial characteristics and geographic adaptability of traditional villages in a multicultural area and provides a significant reference for advancing analogous traditional settlement protections and rural revitalization initiatives. Full article

Repeated expeditions across various regions of Georgia in the early 2000s led to the identification of 434 wild grapevine individuals (Vitis vinifera L. subsp. sylvestris (C.C. Gmel.) Hegi) across 127 different sites, with 45% of these sites containing only a single vine and only 7% more than 9 vines. A total of 70 accessions were propagated in a germplasm collection, 41 of them were descripted from the ampelographic point of view and 32 from the phenological one. The geographical and ecological analysis confirmed that wild grapevines primarily grow in humid environments with warm and fully humid climates, often near rivers. They favor deep, fertile, and evolved soils, mainly alluvial and cinnamonic types (80%), with a marginal presence on strongly eroded soils. Their main natural vegetations are forests and open woodlands, with some individuals in the Southeast found in steppes. The altitudinal range spans from 0 to 1200 m, with 80% of vines distributed between 400 and 900 m. The phenological analysis revealed significant differences among the accessions but no difference among populations, with only a slight variation in bud-break timing, indicating a high level of synchronicity overall. Flowering timing proved to be the most uniform stage, suggesting minimal environmental pressure on genetic adaptation. The mature leaf morphology exhibited significant polymorphism, though leaves were generally three- or five-lobed, weak-wrinkling, and -blistering, with a low density of hairs. Bunch and berry morphology were more uniform. Bunches were consistently very small, cylindrical, and never dense or winged. Berries were also very small, mostly globular, always blue-black in color, and non-aromatic. A striking feature was the frequency of red flesh coloration, which ranged from weak to strong, with uncolored flesh being rare. The Georgian population of wild grapevines was found to be fragmented, often consisting of scattered single individuals or small groups. Therefore, we believe it is urgent for Georgia to implement specific protection measures to preserve this vital genetic resource. Full article

West Africa faces a complex range of challenges arising from climatic, social, economic, and ecological factors, which pose significant risks. The rapidly growing population, coupled with persistently low agricultural yield, further exacerbates these risks. A state-of-the-art monitoring and data derivation of agricultural systems are crucial for improving livelihoods and enhancing food security. Despite smallholder farming systems accounting for 80% of cultivated cropland area and providing about 42% of the total employment in West Africa, there exists a lack of a comprehensive overview of Remote Sensing (RS) products and studies specifically tailored to smallholder farming systems, which this review aims to address. Through a systematic literature review comprising 163 SCI papers sourced from the Web of Science database (Filter I), followed by a full-text review (Filter II), we analyze the RS sensors, spatiotemporal distribution, temporal scales, the crop types examined, and thematic foci employed in existing research. Our findings highlight the predominance of high to very high-resolution, multispectral sensors as the primary data source and we observe that a wide array of available sensors and datasets, along with increasing computing capacities, have shaped the field over the last years. By highlighting existing knowledge, this study identifies the potential of RS and pinpoints the key research gaps. This sets the stage for future investigations aimed at addressing critical challenges in West African smallholder agricultural systems. Full article

This review explores the applications of Convolutional Neural Networks (CNNs) in smart agriculture, highlighting recent advancements across various applications including weed detection, disease detection, crop classification, water management, and yield prediction. Based on a comprehensive analysis of more than 115 recent studies, coupled with a bibliometric study of the broader literature, this paper contextualizes the use of CNNs within Agriculture 5.0, where technological integration optimizes agricultural efficiency. Key approaches analyzed involve image classification, image segmentation, regression, and object detection methods that use diverse data types ranging from RGB and multispectral images to radar and thermal data. By processing UAV and satellite data with CNNs, real-time and large-scale crop monitoring can be achieved, supporting advanced farm management. A comparative analysis shows how CNNs perform with respect to other techniques that involve traditional machine learning and recent deep learning models in image processing, particularly when applied to high-dimensional or temporal data. Future directions point toward integrating IoT and cloud platforms for real-time data processing and leveraging large language models for regulatory insights. Potential research advancements emphasize improving increased data accessibility and hybrid modeling to meet the agricultural demands of climate variability and food security, positioning CNNs as pivotal tools in sustainable agricultural practices. A related repository that contains the reviewed articles along with their publication links is made available. Full article

Environmental factors control the accumulation of aboveground biomass (AB) in tropical forests, along with the role of AB in climate change mitigation. As such, the objective of this study was to evaluate the influence of factors such as forest type, succession, abundance of individuals, species richness, height, diameter, texture, and soil nutrient levels on the AB in mature and postmining forests in Chocó, Colombia. Five plots each were set up in primary and postmining forests with 15 and 30 years of regeneration, in which the amount of AB was measured and related to the environmental factors. The AB was 178.32 t ha⁻¹ in the mature forests and 35.17 and 56.3 t ha⁻¹ after 15 and 30 years of postmining regeneration, respectively. Furthermore, the general AB level was determined by the ecosystem type, diameter, richness, abundance, Shannon evenness, and Margalef diversity. In mature forests, the AB amount was positively influenced by height and richness, and negatively influenced by dominance and evenness; in areas degraded by mining, the AB level was positively related to richness and equity, and negatively related to species diversity and soil silt. In summary, environmental factors determine the carbon storage in the forests in Chocó. Mining reduces the function of these ecosystems in mitigating climate change. Full article

Forests have a key role in mitigating both non-biological and biological ecological disturbances. However, major disturbances (soil pollution, shift from native forest species to exoticones, forested watersheds and climate changes) can have different impacts on a forest’s soil microbiome. Because the soil microbial community of forests has a key role in a variety of ecosystem services that promote the forest’s health, this review tries to answer the following questions: (i) Which are the main ecological disturbances that drive the responses of the forest soil microbiome? (ii) How can we measure these changes? For this aim, the review summarizes details on the tree vegetation type, the microbial communities in forest ecosystems, and the mutual influence between plants, soil, and microbiomes. Microbial communities are shaped by factors such as soil type and composition, plant and vegetation types, nutrient levels and soil fertility, disturbance patterns, symbiotic associations, biotic interactions, and the progression of forest succession. Anthropogenic activities produce a rapid response in the microbial communities, leading to both short- and long-term alterations. Harvesting processes reduce drastically the microbiome diversity, forcing a shift from specialized to more generalist microorganisms. Restoration scenarios indicate a re-establishment of microbial communities to a level similar to the native forest, but with a high percentage of replaced native microorganisms. This review emphasizes that the forest soil microbiome is shaped by a range of environmental, ecological, and biotic factors. The primary drivers of the soil microbiome in forest ecosystems discussed in this review include soil composition and nutrient availability, plant community structure, microbial interactions within the soil, disturbances, succession, and temporal dynamics. When considered together, these factors interact in complex ways, influencing the diversity, function, and resilience of the soil microbiome in forest ecosystems. Full article

The fungus Puccinia triticina Eriks (Pt) is the cause of leaf rust, one of the most damaging diseases, which significantly reduces common wheat yields. In Pt-resistant adult plants, an APR-type resistance is observed, which protects the plant against multiple pathogen races and is distinguished by its persistence under production conditions. With a more complete understanding of the molecular mechanisms underlying the function of APR genes, it will be possible to develop new strategies for resistance breeding in wheat. Currently, mainly APR genes, such as Lr34, Lr46, and Lr67, are principally involved in resistance breeding as they confer durable resistance to multiple fungal races occurring under different climatic and environmental conditions. However, the mechanisms underlying the defence against pathogens mediated by APR genes remain largely unknown. Our research aimed to shed light on the molecular mechanisms related to resistance genes and miRNAs expression, underlying APR resistance to leaf rust caused by Pt. Furthermore, the present study aimed to identify and functionally characterize the investigated miRNAs and their target genes in wheat in response to leaf rust inoculation. The plant material included hybrid forms of wheat from the F₂ and BC₁F₁ generations, obtained by crossing the resistance cultivar Glenlea (CItr 17272) with agriculturally important Polish wheat cultivars. Biotic stress was induced in adult plants via inoculation with Pt fungal spores under controlled conditions. The RT-qPCR method was used to analyze the expression profiles of selected APR genes at five time points (0, 6, 12, 24, and 48 hpi). The results presented here demonstrate the differential expression of APR genes and miRNAs at stages of leaf rust development at selected timepoints after inoculation. We analyzed the expression of three leaf rust resistance genes, using different genetic backgrounds in F₂ and BC₁F₁ segregation materials, in leaf tissues after Pt infection. Our goal was to investigate potential differences resulting from the genetic background found in different generations of hybrid forms of the same parental forms. Gene ontology analysis predicted 190 target genes for tae-miR5384-3p and 167 target genes for tae-miR9653b. Our findings revealed distinct expression profiles for genes, with the highest expression levels observed mainly at 6, 24, and 48 hpi. The candidate gene Lr46-Glu2 displayed an upregulation, suggesting its potential involvement in the immune response against Pt infection. Full article

Arctic sea ice has a significant effect on global climate change, ship navigation, Arctic ecosystems, and human activities. Therefore, it is essential to produce high-resolution sea ice maps that accurately represent the geographical distribution of various sea ice types. Based on deep learning technology, many automatic sea ice classification algorithms have been developed using synthetic aperture radar (SAR) imagery over the last decade. However, sea ice classification faces two vital challenges: (1) it is difficult to distinguish sea ice types with close developmental stages solely from SAR images and (2) an imbalanced sea ice dataset has a significantly negative effect on ice classification model performance. In this article, a spatio-temporal deep learning model—the Dynamic Multi-Layer Perceptron (MLP)—is utilized to classify 10 sea ice types automatically. It consists of a SAR image branch and a spatio-temporal branch, which extracts SAR image features and spatio-temporal distribution characteristics of sea ice, respectively. By projecting similar image features to different positions in the spatio-temporal feature space dynamically, the Dynamic MLP model effectively distinguishes between similar sea ice types. Furthermore, to reduce the impact of data imbalance on model performance, the dynamic curriculum learning (DCL) method is used to train the Dynamic MLP model. Experimental results demonstrate that our proposed method outperforms the long short-term memory (LSTM) network approach in distinguishing between sea ice types with similar developmental stages. Moreover, the DCL training method can also effectively improve model performance in identifying minority ice types. Full article

Haian Depression is one of the key areas for oil and gas resource replacement in Jiangsu Oilfield. Since the 13th cycle of the Five Year Plan, with the continuous improvement in the exploration level of the Taizhou Formation (K₂t), the difficulty of tapping potential has gradually increased. It is urgent to change our thinking and expand new exploration layers. From the perspective of oil and gas display frequency in different layers of the Haian Depression, except for K₂t, the oil and gas systems with the Fusan Member (E₁f₃) as the main reservoir have good oil and gas display frequency, demonstrating great exploration potential. This study of sedimentary characteristics is the basis of analyzing the sedimentary environment and lithofacies paleogeographic conditions and is of great significance for determining the distribution range of subtle oil and gas reservoirs. Based on this understanding, this study was specially established to systematically analyze the logging curves of forty-three wells in the research area, combined with core observations of eighteen coring wells and the analysis of eight seismic profiles. The results show that the low slope, warm and humid climate, sufficient provenance, and frequent lake level rise and fall cycles during the deposition period of the E₁f₃ member of the Haian Sag provide a favorable depositional background for the development of shallow water delta in the study area. There are many gullies in the research area, mainly consisting of U-shaped gullies and W-shaped gullies. Slope breaks are mainly affected by structural factors leading to fractures, and the types are mostly fault terrbreakslope breaks. In the study area, the shallow water delta deposits during the deposition period of the four key sand groups in the Fu3 Formation are dominated by the shallow water delta front and shallow water prodelta. The shallow water delta plain subfacies are not significantly developed because of erosion. The sand bodies are mainly distributed in the Sunjiawa Subdepression, and the Fuan Subdepression in the north of the depression, and the sand bodies in the plane show the filling characteristics of the strip. Based on the above research, a sedimentary model of shallow water delta during the E₁f₃ section of the Haian Depression was established, providing a geological basis for the design of exploration and development plans for hidden oil and gas reservoirs in the next step. Full article

Understanding the distribution patterns and driving mechanisms of bamboo species diversity on islands is essential for advancing knowledge of island ecosystem processes and informing strategies for bamboo resource conservation and management. This study utilized standardized major axis regression (SMA) to assess the effects of island area and isolation on bamboo species across 30 islands in Fujian, China. Furthermore, a partial least squares structural equation model (PLS-SEM) was constructed to explore the driving mechanisms underlying bamboo species richness. This analysis incorporated six key environmental factors—island size, isolation, shape, climate, development intensity, and habitat heterogeneity—spanning a total of 12 variables. The primary findings were as follows: (1) Eight genera and twenty-nine bamboo species were identified on Fujian islands. Species richness increased significantly with island area, consistent with the theory of area effects, while isolation had no significant impact on richness. (2) Different reproductive types exhibited distinct responses to environmental conditions. This was evident in the species–area relationship slopes (z-values): SR = 2.07; monopodial = 0.94; sympodial = 0.82; and polycyclic = 0.44. These variations highlight the ecological adaptability and functional traits of different reproductive strategies within island ecosystems. (3) Among the six environmental factors, island area exerted the greatest influence on species richness, underscoring its role as the primary driver of bamboo diversity and reproductive strategies. (4) Island area and isolation also impacted species richness indirectly through their effects on development intensity. In conclusion, the bamboo species richness and reproductive types on Fujian islands are primarily shaped by island area, followed by development intensity and habitat heterogeneity. In contrast, climate, island shape, and isolation play relatively minor roles. This study provides critical insights into the interplay of island area, isolation, shape, climate, development intensity, and habitat heterogeneity in shaping bamboo diversity. The findings offer a valuable foundation for bamboo resource conservation, island ecosystem management, and sustainable development. Full article

The wetland ecosystem is one of the most important carbon sinks on Earth, the most biodiverse ecological landscape in nature, and one of the most important living environments for human beings. The Weihe River wetland is located in the Guanzhong Plain urban agglomeration, with extreme climate and urban expansion having a great impact on its dynamic changes. Revealing the characteristics of and trends in wetland dynamics in the Weihe River Basin is the key to protecting and maintaining the healthy development of the Weihe River wetlands. This paper analyzed the changing characteristics of land use types and landscape patterns in the wetlands of the Weihe River Basin using wetland land use data from six periods in the Weihe River wetland from 1980 to 2020 and explored the spatial and temporal distribution characteristics and dynamic changes in wetlands in the Weihe River Basin. The results showed the following: (1) Wetlands in the Weihe River Basin, dominated by rivers, saw area fluctuations with an initial decline followed by an increase. Land use changes followed a slow–fast–slow trend. (2) From 1980 to 2020, frequent conversions among wetland types were observed. The primary transformation was the conversion of marshes into lakes (18.05 km²) and reservoirs/ponds (17.98 km²). Approximately 0.06 km² of lakes were transformed into canals/channels. (3) River patches have the largest area, while canals/channels have the smallest. The patch density (PD) and landscape shape index (LSI) of wetlands fluctuate significantly, and the reduction in area leads to a 3.46% decrease in aggregation index (AI). Shannon’s diversity index (SHDI) has decreased by 5.41%. (4) The centroid of marshes experiences significant changes, while river changes are complex. The centroid changes in reservoirs/ponds are located along the southeast–northwest line. Canals/watercourses remain stable. Lakes exhibit the longest migration. This study provides robust scientific support for wetland ecological protection, policy formulation, and social sustainable development by conducting an in-depth analysis of the dynamic change characteristics of wetlands in the Weihe River Basin. Full article

Temperature and host fruit availability are key factors influencing the life history traits of the Mediterranean fruit fly (medfly) (Ceratitis capitata). This study examines how developmental temperature and host fruit type affect adult longevity and fecundity in medflies from six populations spanning Southern to Central Europe. Larvae were reared on apples and bitter oranges at three constant temperatures (15, 20, and 25 °C), with pupae maintained under the same thermal conditions until adult emergence. Adults were then kept at 25 °C, with longevity and fecundity recorded daily. The results showed that higher developmental temperatures increased adult lifespan across all populations, regardless of host fruit. Similarly, fecundity rates in ovipositing females were higher at higher temperatures. Reproductive periods (pre-oviposition, oviposition, and post-oviposition) varied among populations, indicating population-specific responses. These findings underscore how temperature and host fruit availability shape medfly invasion dynamics, highlighting the species’ biological plasticity and adaptation to different environments. This research provides valuable insights for pest management, particularly in the context of climate change, offering strategies to mitigate the spread of medflies into new regions. Full article

Biochar, an important by-product of the waste biomass pyrolysis process, shows great potential to reduce the environmental impact of and address the serious problems related to climate change as well as to define an efficient circular economy model. Its use as a soil conditioner has increased the interest in biochar in agriculture over time. This review investigates how critical aspects such as starting material, temperature, and the presence or absence of oxygen during the pyrolysis process influence the yield and quality of this valuable soil conditioner. Considering the horticultural sector, this review also provides a comprehensive and detailed overview of how biochar positively influences growth, development, and yield by explaining the mechanisms and modes of action under both optimal growth conditions and unfavorable contexts (salt and water stress and the presence of heavy metals). The main mechanisms highlighted by this literature review are improvement in soil aeration and water-holding capacity, microbial activity, and nutritional status of soil and plants, as well as alterations in some important soil chemical properties. This in-depth review of the literature highlights how the interaction between biochar types, dose, crop species, and growing conditions (optimal or nonoptimal) result in nonunique responses. The heterogeneity of the results reported in the literature confirms how many of the topics discussed deserve further investigation, with particular attention to identifying the right dose of biochar in relation to the different preharvest factors considered. Full article

Epiphytic bryophytes are an important component in terms of the diversity and functioning of montane forests known as biodiversity hotspots. Bryophytes are highly dependent on their external environments because they are sensitive to environmental changes related to disturbance, fragmentation, air pollution, and climate change. The richness and composition of bryophytes in remnants of primary and secondary forests were analyzed, where the richness and cover were recorded on trunk bases of 120 trees. Changes in species richness and diversity were analyzed using generalized linear models (GLMs), and changes in species composition, using multivariate analysis. A total of 57 bryophyte species (36 liverworts and 21 mosses) were recorded in trunk bases. For the first time, 19 new liverworts for the province of El Oro are reported. The richness and diversity of bryophyte species decrease in disturbed forests when compared to primary forests, with a marked decrease in species less adapted to conditions of high light (shade epiphytes). In the same line, species composition is different in each type of forest, where bryophytes with high humidity requirements were abundant in primary forests. This study confirms that forest disturbance is a key factor in determining not only the number of species but also the composition of bryophyte species. The maximum tree diameter and primary forest remnants are important factors in the conservation of sensitive bryophyte species at the base of trees in one of the last remnants of mountain forests in El Oro Province, Ecuador. Full article

As climate change intensifies, extreme drought events have become more frequent, and investigating the mechanisms of watershed drought has become highly significant for basin water resource management. This study utilizes the WRF-Hydro model in conjunction with standardized drought indices, including the standardized precipitation index (SPI), standardized soil moisture index (SSMI), and Standardized Streamflow Index (SSFI), to comprehensively investigate the spatiotemporal characteristics of drought in the Huai River Basin, China, from 2012 to 2018. The simulation performance of the WRF-Hydro model was evaluated by comparing model outputs with reanalysis data at the regional scale and site observational data at the site scale, respectively. Our results demonstrate that the model showed a correlation coefficient of 0.74, a bias of −0.29, and a root mean square error of 2.66% when compared with reanalysis data in the 0–10 cm soil layer. Against the six observational sites, the model achieved a maximum correlation coefficient of 0.81, a minimum bias of −0.54, and a minimum root mean square error of 3.12%. The simulation results at both regional and site scales demonstrate that the model achieves high accuracy in simulating soil moisture in this basin. The analysis of SPI, SSMI, and SSFI from 2012 to 2018 shows that the summer months rarely experience drought, and droughts predominantly occurred in December, January, and February in the Huai River Basin. Moreover, we found that the drought characteristics in this basin have significant seasonal and interannual variability and spatial heterogeneity. On the one hand, the middle and southern parts of the basin experience more frequent and severe agricultural droughts compared to the northern regions. On the other hand, we identified a time–lag relationship among meteorological, agricultural, and hydrological droughts, uncovering interactions and propagation mechanisms across different drought types in this basin. Finally, we concluded that the WRF-Hydro model can provide highly accurate soil moisture simulation results and can be used to assess the spatiotemporal variations in regional drought events and the propagation mechanisms between different types of droughts. Full article