Exploring Fungal Biodiversity in Crop Rotation Systems: Impact of Soil Fertility and Winter Wheat Cropping DOI Creative Commons
Srđan Šeremešić, Sonja Tančić, Miloš Rajković

et al.

Plants, Journal Year: 2024, Volume and Issue: 14(1), P. 65 - 65

Published: Dec. 28, 2024

This study investigated soil fungal biodiversity in wheat-based crop rotation systems on Chernozem within the Pannonian Basin, focusing effects of tillage, rotation, and properties. Over three years, samples from ten plots were analyzed, revealing significant diversity with Shannon–Wiener indices ranging 1.90 monoculture to 2.38 a fertilized two-year rotation. Dominant fungi, including Fusarium oxysporum, Penicillium sp., Aspergillus showed distinct preferences for conditions such as pH organic matter (OM). Conservation tillage significantly enhanced richness, highest observed three-year system incorporating cover crops, which achieved an average winter wheat yield 7.0 t ha−1—47% higher than unfertilized systems. Increased OM nitrogen levels these correlated greater abundance diversity. Canonical correspondence analysis revealed strong relationships between communities properties, particularly calcium carbonate content. These findings highlight importance tailored strategies improve health, enhance microbial biodiversity, boost agricultural sustainability temperate climates, providing valuable insights mitigating impacts intensive farming climate change.

Language: Английский

Integrating Artificial Intelligence Agents with the Internet of Things for Enhanced Environmental Monitoring: Applications in Water Quality and Climate Data DOI Open Access
Tymoteusz Miller, Irmina Durlik, Ewelina Kostecka

et al.

Electronics, Journal Year: 2025, Volume and Issue: 14(4), P. 696 - 696

Published: Feb. 11, 2025

The integration of artificial intelligence (AI) agents with the Internet Things (IoT) has marked a transformative shift in environmental monitoring and management, enabling advanced data gathering, in-depth analysis, more effective decision making. This comprehensive literature review explores AI IoT technologies within sciences, particular focus on applications related to water quality climate data. methodology involves systematic search selection relevant studies, followed by thematic, meta-, comparative analyses synthesize current research trends, benefits, challenges, gaps. highlights how enhances IoT’s collection capabilities through predictive modeling, real-time analytics, automated making, thereby improving accuracy, timeliness, efficiency systems. Key benefits identified include enhanced precision, cost efficiency, scalability, facilitation proactive management. Nevertheless, this encounters substantial obstacles, including issues quality, interoperability, security, technical constraints, ethical concerns. Future developments point toward enhancements technologies, incorporation innovations like blockchain edge computing, potential formation global systems, greater public involvement citizen science initiatives. Overcoming these challenges embracing new technological trends could enable play pivotal role strengthening sustainability resilience.

Language: Английский

Citations

6

From underwater to drone: A novel multi-scale knowledge distillation approach for coral reef monitoring DOI Creative Commons
Matteo Contini,

Victor Illien,

Julien Barde

et al.

Ecological Informatics, Journal Year: 2025, Volume and Issue: unknown, P. 103149 - 103149

Published: April 1, 2025

Language: Английский

Citations

1

Elevation gradient effects on grassland species diversity and phylogenetic in the two-river source forest region of the Altai Mountains, Xinjiang, China DOI Creative Commons

Jing Che,

Mao Ye, Qingzhi He

et al.

Frontiers in Plant Science, Journal Year: 2025, Volume and Issue: 16

Published: Feb. 4, 2025

Altitude, as a key environmental factor, shapes the spatial patterns of species diversity, phylogenetic and community structure. Studying grassland diversity structure along altitudinal gradients helps clarify how altitude-driven changes influence assembly, reveal vertical in formation. This study examines grasslands at 1300–2500 m elevation Two-River Source Forest Area, Altai Mountains, Xinjiang. Six (200 intervals) were surveyed with 90 quadrats, documenting characteristics data. The analyzes composition, phylogeny across different explores their relationships factors. results indicate that composition is dominated by from Poaceae, Rosaceae, Asteraceae families, Poa annua (annual bluegrass) being dominant within Poaceae. gradient exhibits bimodal trend, an initial increase, followed decrease, another finally decline rises. In contrast, shows unimodal pattern, characterized increase increasing elevation. Although did not exhibit significant trend transitioning divergence to clustering gradient, overall pattern communities tended toward clustering. Further analysis reveals correlations between factors such temperature, precipitation, forest cover, soil moisture. However, no found have correlation indices.

Language: Английский

Citations

0

Reviewing the Impact of Seed-Borne Mycoflora on Mycotoxin Accumulation: A Threat to Lentil Genetic Resources DOI

Sanam Asif,

Momina Nisar,

Shakir Ullah

et al.

Toxicon, Journal Year: 2025, Volume and Issue: unknown, P. 108290 - 108290

Published: Feb. 1, 2025

Language: Английский

Citations

0

Turning Systemic Vulnerabilities into Strategic Opportunities: A Research Proposal for Societal Grand Challenges DOI

Steph Sharma,

Joachim Layes,

Yusaf H. Akbar

et al.

Published: Jan. 1, 2025

Language: Английский

Citations

0

Safeguarding China’s irreplaceable natural legacy: combating the illicit trade of old trees DOI Creative Commons
Chunping Xie, C.Y. Jim

Environmental Conservation, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 3

Published: March 25, 2025

Summary The illegal theft of old trees threatens China’s ecological and cultural heritage. Despite legal protections, their high-value timber has persistently fuelled illicit trade driven by economic incentives weak enforcement in remote areas, endangering biodiversity traditions. This Comment article proposes comprehensive alternative approaches to combat the advocating for a strengthened framework, enhanced monitoring systems increased support local authorities. It highlights importance public awareness community engagement conservation efforts address ingrained drivers this trade.

Language: Английский

Citations

0

No need for niches in new ecology DOI Creative Commons
C.J.M. Musters, G.R. de Snoo

Acta Oecologica, Journal Year: 2025, Volume and Issue: 127, P. 104075 - 104075

Published: April 4, 2025

Language: Английский

Citations

0

Swarm Intelligence and Multi-Drone Coordination With Edge AI DOI
Siva Raja Sindiramutty

Advances in computational intelligence and robotics book series, Journal Year: 2025, Volume and Issue: unknown, P. 271 - 304

Published: March 28, 2025

Swarm intelligence is transforming drone tech to enable autonomous air systems collaborate and adapt readily real-world conditions. By flying in coordination, drones can perform sophisticated tasks that would be difficult or impossible for a single unit accomplish. Whether search rescue large-scale agricultural surveillance, coordinated improve speed, coverage, decision-making. Edge AI significant it allows process information real time, cutting down on reliance remote cloud servers. This enables swarms react quickly changing environments, such as navigating through disaster scenes tracking moving objects. Unlike using central controller all commands, communicate with each other collectively decide, birds flock ants colony. coordination supplemented advanced technologies like 5G connectivity sensor fusion the smooth sharing of data among drones.

Language: Английский

Citations

0

Application of Artificial Intelligence in Agri-Tech, Environmental and Biodiversity Conservation DOI Creative Commons

Chatrabhuj,

Kundan Meshram, Umank Mishra

et al.

Array, Journal Year: 2025, Volume and Issue: unknown, P. 100412 - 100412

Published: May 1, 2025

Language: Английский

Citations

0

BirdRecon: A free open source tool for image based bird species recognition DOI Creative Commons
Hari Kishan Kondaveeti,

Nabin Kumar Upadhaya,

Dheeraj Sai Tukkugudam

et al.

Ecological Informatics, Journal Year: 2025, Volume and Issue: unknown, P. 103193 - 103193

Published: May 1, 2025

Language: Английский

Citations

0