Abstract Pancreatic ductal adenocarcinoma (PDAC) remains among the most aggressive cancers, due to its limited therapeutic options and poor prognosis. Even with the adoption of total neoadjuvant therapy (TNT) and potentially curative surgical resection, PDAC relapse rates remain unacceptably high. Current systems for evaluating tumor response are valuable but limited, as they fail to capture the ecological complexity and broader architecture of the tumor microenvironment (TME). This results in uncertainty regarding the prognosis and recurrence risk of patients. To address this and to capture the complexity of the PDAC TME, we developed the Tumor Landscape Analysis (TLA). Using digitized H&E slides from 203 PDAC patients who received TNT and surgical resection at our institution, we applied a machine-learning pipeline to segment tumor and stromal compartments. We then quantified the TME architecture using ecological frameworks to assess the disease in multiple scales: individual patches, whole-slide landscapes, and aggregated patient-level summaries. Our analysis revealed that higher-order spatial features are independently prognostic of disease-free survival (DFS). Two statistical models showed different but complementary spatial characteristics that predict disease risk. In the first model, patients with more irregular cancer patch shapes and lower variability in stromal shape had significantly better DFS, with high-risk patients relapsing in a median of 7.2 months compared to 11.6 months in the low-risk group (HR=1.82, p=0.0003). In the second model, smaller stromal patch areas combined with greater tumor-stroma edge density identified patients at elevated risk, with high-risk individuals showing a median DFS of 8.0 months versus 15.7 months in low-risk patients (HR=1.73, p=0.0007). Importantly, these associations persisted even after adjustment for the T and N stage, showing that spatial features provide unique information beyond traditional pathology measures. These models help visualize PDAC as a comprehensive ecosystem that carries clinical significance. By quantifying tumor conformation and configuration, our models reveal prognostic information not available through CAP grading, percent tumor burden, or routine cell counts. This study suggests that tumor-stroma interactions and their spatial organizations are potentially biologically important for recurrence. We present a new, ecologically inspired approach to digital pathology for PDAC that not only improves our ability to predict recurrence and survival in PDAC but also sheds light on cancer as a complex, evolving ecosystem. Citation Format: Merih D. Toruner, Luis H. Cisneros, Miranda Lin, Andrea Maraone, Carlo Maley, Paul Dizona, Qian Shi, Martin E. Fernandez-Zapico, Ryan M. Carr. Ecological landscape analysis of the tumor microenvironment predicts recurrence risk in pancreatic ductal adenocarcinoma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Cancer Evolution: The Dynamics of Progression and Persistence; 2025 Dec 4-6; Albuquerque, NM. Philadelphia (PA): AACR; Cancer Res 2025;85(23_Suppl):Abstract nr B027.

The control of ticks is challenging owing to their ubiquity, complex ecologies, and difficulties relating to costs and non-target impacts of chemical control programs. Nature-based solutions centre around co-opting natural processes and biodiversity to address socio-environmental problems; and in some cases, rewilded species can provide nature-based solutions. In northern Japan, the winter ecology of ticks is poorly studied, though some species are believed to overwinter under the snow. Winter grazing activity of rewilded horses may disturb overwintering ticks, exposing them to sub-zero temperatures and killing them, thereby providing a nature-based solution to tick control. In this study we sought to ascertain: (i) whether ticks in Japan overwinter in leaflitter under the snow, (ii) whether the winter grazing activity of semi-rewilded horses is associated with reduced springtime tick abundance, (iii) whether semi-rewilded horses serve as key hosts for ticks during springtime. Paired leaflitter sampling undertaken at 10 sites during autumn and winter, respectively, showed that Haemaphysalis ticks overwinter in leaflitter under the snow. Using six paired 25 m2 exclusion-grazing plots we tested whether winter horse grazing was associated with reduced springtime tick abundances but found no significant relationships. Springtime surveys revealed extremely low tick loads (0.2 ticks per horse) and prevalences (12%) on semi-rewilded horses. This suggests that while the winter grazing activities of horses may not appreciably reduce tick abundances, that horses likely do not serve as important amplifying hosts of ticks in northern Japan and that rewilded horses are neither a help nor hinderance to local tick control efforts in this region.

Forest cover influences the fecal virome of Oligoryzomys nigripes in Atlantic Forest remnants, Brazil.

Seasonal variations and functional insights into the urban air microbiome across public transit environments at railway stations in Delhi, India.

Fungi associated with coffee rust Hemileia vastatrix and the description of two new species.

Coastal embayments are ecologically significant ecosystems increasingly affected by human activities and climate change pressures. This study investigated the spatial and temporal dynamics of the zooplankton community in Cam Ranh Bay under varying environmental conditions by chronically sampling in consecutive days, weeks and seasons. The bay exhibited high zooplankton diversity, with 188 species recorded across seven phyla. Arthropoda, particularly Copepoda, contributed over 65% of the total species richness. Notable changes were observed in the zooplankton community, particularly within Copepoda families, even over short periods (e.g., day or week). At a seasonal scale, the zooplankton community shifted with increased densities of larval groups during the rainy season, coinciding with a relative decrease in arthropods. Biodiversity indices indicated greater stability during the rainy season, while canonical correspondence analysis (CCA) revealed distinct seasonal relationships between species and environmental variables, such as nutrient fluxes and salinity. These findings underscore the ecological complexity of Cam Ranh Bay, providing a critical baseline for monitoring environmental changes and managing human impacts on this biodiverse ecosystem.

Regulation, responsibility, and resource complexity: A qualitative evaluation of stakeholder perspectives on Ireland's Nitrates Action Programme for dairy farms.

Monoculture plantations of Eucalyptus in China have raised ecological concerns due to water depletion, soil degradation, and fire risk. Integrating Eucalyptus with Cupressus offers a sustainable approach to improving forest ecosystem health. In this study, we established five forest treatments, pure Eucalyptus (1:0), mixed Eucalyptus–Cupressus at three ratios (2:1, 1:1, and 1:2), and pure Cupressus (0:1), to assess their effects on soil properties, microbial diversity, and metabolomic profiles. Laboratory analyses revealed significant differences in physicochemical soil properties (such as water content (p < 0.05), pH (p < 0.001), organic carbon (p < 0.001), and nitrogen (p < 0.001)) among various groups within the mixed forests. Microbial community investigations highlighted a unique microbial signature in Eucalyptus–Cupressus mixed forests, especially when the tree ratio was 1:2, characterized by a rich (Chao1, p < 0.05) and diverse (Shannon, p < 0.05) array of bacterial taxa. The mixed Eucalyptus–Cupressus forest also exhibited an uplift in microbial communities, bacterial genera such as RB41, and fungal genera including Penicillium, Talaromyces, and Mortierella, which are associated with enhanced organic matter decomposition and nutrient cycling. Interactive networks within microbial communities were revealed through co-occurrence and Spearman correlation analyses, highlighting potential symbiotic relationships and ecological complexities. Metabolomic analysis, coupled with pathway analysis, further illuminated metabolic shifts in the mixed forests, emphasizing alterations in key metabolic pathways such as phenylpropanoid biosynthesis, tyrosine metabolism, arachidonic acid metabolism, and isoquinoline alkaloid biosynthesis. Collectively, these results show that moderately mixed Eucalyptus–Cupressus forests improve soil fertility and microbial multifunctionality, providing a practical model for sustainable and resilient forest management in subtropical regions.

ABSTRACTTrophic niche differentiation alleviates interspecific competition among soil fauna by modulating resource utilization and allocation, offering a novel perspective for understanding biodiversity maintenance and species coexistence in subterranean ecosystems. As a typical example of an oligotrophic and extremely dark environment, karst cave soils support arthropod communities that are functionally distinct from those in surface habitats. However, systematic understanding of the multidimensional diversity patterns and ecological network complexity of multitrophic groups of cave‐dwelling soil mites remains limited. In this study, soil mite samples were collected from distinct photic zones of the cave including the dark, twilight, light, and entrance zones. We aimed to uncover the variation in α, β, and functional diversity among multitrophic groups (including predators and decomposers), and constructed ecological networks to examine patterns of biotic interactions and species coexistence. The results showed that along the cave environmental gradient, the α‐diversity of different trophic groups increased, while functional diversity exhibited a contrasting trend. In addition, except for predator groups, the β‐diversity of soil mites did not differ significantly among cave microhabitats and was primarily driven by species replacement processes. Moreover, the complexity of ecological networks progressively increased along the cave gradient, indicating that interactions among multitrophic groups intensified, with predatory mites playing a central role in maintaining network stability. Notably, no indicator species were found in the dark zone, which represents the core oligotrophic habitat within caves. Our study demonstrates that, compared to surface habitats such as cave entrances and adjacent agricultural lands, cave soil environments support simpler community composition, diversity, and ecological network complexity across different trophic groups of mites. Furthermore, predatory mites not only serve as keystone taxa within cave habitats, but also play a pivotal role in mediating interactions among trophic groups. These findings provide important theoretical insights for understanding community assembly processes under extreme environmental conditions, maintaining ecosystem stability, and supporting the conservation of subterranean biodiversity.

Global technological competition and the sustainable development agenda urgently demand a systemic reshaping of science education.This paper diagnoses a profound ecological crisis in primary and secondary science education in China: the fragmentation of knowledge structures leads to a rupture in the Knowledge Ecological Chain, the singularization of cognitive pathways causes the atrophy of the Cognitive Ecological Web, and the lack of value concern results in the desertification of the Meaning Ecological Field. Based on holistic ecological views and complexity theory, and integrating the concepts of the US NGSS standards and China’s new curriculum standards, this study constructs an AI-empowered Triple Helix model for the ecologicalization of the science curriculum. This model focuses on the core framework of Knowledge Ecological Chain-Cognitive Ecological Web-Meaning Ecological Field, driven by an AI-enhanced learning ecological cycle of Perception-Interaction-Reflection-Creation. Through the practical pathways of Ecological Content Restructuring, Immersive Teaching Practice, and Intelligent Evaluation Guidance, it aims to propel science education from mechanical indoctrination towards organic generation, and from instrumental rationality back to value rationality. This paper provides a systematic theoretical framework and practical plan for addressing the ecological imbalance in science education, aiming to cultivate an innovative generation with scientific literacy, humanistic spirit, and ecological wisdom.

With the development of information technology and the transformation of consumer culture, the live streaming economy has been integrated into China's digital economic system, driving urban economic growth. However, it has also brought about regulatory issues such as information asymmetry, false advertising, difficulty in ensuring quality, and high costs of rights protection. This new economic form of virtualization, real-time, and cross-domain is facing enormous challenges. Traditional methods, such as manual sampling, reporting, and post-event tracing, are unable to meet the complex and ever-changing live streaming economic ecology. The powerful perception, recognition, and understanding capabilities of artificial intelligence provide new possibilities for building a scientific regulatory system in real-time, accurately, and efficiently. This article uses the theory of technological empowerment to explore the operational mechanism of artificial intelligence in regulating the live streaming economy, with a focus on the role of artificial intelligence in empowering live streaming economy regulation in four aspects: data intelligence, behavior recognition, risk warning, and intelligent decision-making. In addition, this article proposes a feasible path for building a smart regulatory system from three aspects: technology integration, institutional collaboration, and talent cultivation, providing relevant inspiration and reference for exploring the construction of a government platform collaborative governance mechanism and achieving modernization of platform economic governance in practice.

This research presents a comprehensive analysis of the spatial extent and temporal change in benthic habitats within the Puck Lagoon in the southern Baltic Sea, utilizing integrated machine learning classification and multi-sourced remote sensing. Object-based image analysis was integrated with Random Forest, Support Vector Machine, and K-Nearest Neighbors algorithms for benthic habitat classification based on airborne bathymetric LiDAR (ALB), multibeam echosounder (MBES), satellite bathymetry, and high-resolution aerial photography. Ground-truth data collected by 2023 field surveys were supplemented with long temporal datasets (2010–2023) for seagrass meadow analysis. Boruta feature selection showed that geomorphometric variables (aspect, slope, and terrain ruggedness index) and optical features (ALB intensity and spectral bands) were the most significant discriminators in each classification case. Binary classification models were more effective (93.3% accuracy in the presence/absence of Zostera marina) compared to advanced multi-class models (43.3% for EUNIS Level 4/5), which identified the inherent equilibrium between ecological complexity and map validity. Change detection between contemporary and 1957 habitat data revealed extensive Zostera marina loss, with 84.1–99.0% cover reduction across modeling frameworks. Seagrass coverage declined from 61.15% of the study area to just 9.70% or 0.63%, depending on the model. Seasonal mismatch may inflate loss estimates by 5–15%, but even adjusted values (70–94%) indicate severe ecosystem degradation. Spatial exchange components exhibited patterns of habitat change, whereas net losses in total were many orders of magnitude larger than any redistribution in space. These findings recorded the most severe seagrass habitat destruction ever described within Baltic Sea ecosystems and emphasize the imperative for conservation action at the landscape level. The methodology framework provides a reproducible model for analogous change detection analysis in shallow nearshore habitats, creating critical baselines to inform restoration planning and biodiversity conservation activities. It also demonstrated both the capabilities and limitations of automatic techniques for habitat monitoring.

ABSTRACTAcoustic communication plays a critical role in mediating social interactions, coordinating behaviours and maintaining group cohesion in many animals. While fish are known to produce a diverse range of sounds, most studies have been conducted in laboratory settings, limiting our understanding of how vocalisations function in natural social and ecological contexts. In this study, we provide a comprehensive examination of vocal behaviour in social groups of orange anemonefish (Amphiprion percula), an anemonefish species with strict size‐based hierarchies. Using underwater video and acoustic recordings from nine wild groups in Kimbe Bay, Papua New Guinea, we quantified acoustic features of individual vocalisations and linked them to behavioural contexts. We also examined the effect of body size and social status on vocalisation's acoustic features. Our findings demonstrate that A. percula's vocalisations differ between behavioural contexts, highlighting the role of acoustic signals in signalling submission, regulating conflict, and maintaining group hierarchy. Behavioural context emerged as the strongest predictor of vocal variation, with body size and social rank providing additional variation. This study underscores the importance of field‐based investigations to capture the ecological and social complexity of acoustic communication. These findings establish a baseline for future functional studies, including playback experiments, and provide critical insight into the adaptive significance of sound in social fish communities.

Background/Objectives: Due to the numerical dominance of environmental and commensal strains, understanding antimicrobial resistance (AMR) transmission in Escherichia coli requires consideration of non-clinical as well as pathogenic isolates. In this cross-sectional study, associations between the genetic context of non-clinical E. coli and AMR carriage are examined in isolates sampled from different niches within a One Health continuum. Methods: Two hundred eighty-eight E. coli isolates collected in Alberta, Canada (2018–2019) from wastewater, well water, feces of broiler chickens and feedlot cattle, and retail beef and chicken meat were selected from existing surveillance collections using a stratified random sampling structure. Using short-read whole genome assemblies, phylogenetic relationships were inferred from pan-genome multiple sequence alignments. Principal coordinate analysis and permutational analysis of variance (PERMANOVA) of a Jaccard dissimilarity matrix derived from gene presence/absence data were used to investigate contributions of source and AMR strata to observe genetic dissimilarity. Population clustering and gene under- or over-representation by source and cluster were also explored. Results: Minimal phylogenetic segregation of isolates was noted based on source or AMR strata, and both contributed significant but small proportions of observed genetic dissimilarity, with the largest proportion attributed to phylogroup. There was notable diversity of E. coli within and between sources; however, in some larger clusters, differential gene presence/absence was potentially linked to ecological niche rather than source of isolation. Conclusions: This study highlights the ecological complexity of AMR in E. coli in non-clinical contexts, offering a novel lens on how niche-specific factors can influence population structure and AMR carriage. It also provides insight into apparent discrepancies in the literature regarding clustering of E. coli by source. These findings support a more integrative One Health approach to AMR surveillance, emphasizing the need to account for microbial diversity and niche-specific adaptation across interconnected systems.

ABSTRACT This study proposes an Ecological Functional Sub‐regional Integrated Natural Resource Management framework specifically adapted to Vietnam's complex ecological and socio‐economic conditions. Originating from the CGIAR's 2000 INRM model, the framework is critically revised to address its limitations—particularly the absence of a preliminary assessment stage and lack of ecological functional sub‐region division. Using a theoretical and analytical approach, the study integrates insights from INRM literature and Vietnam‐specific environmental planning to develop a seven‐stage model emphasizing localized assessment, stakeholder participation, and the integration of production, social welfare, and ecosystem functions. Findings highlight that dividing districts into ecological functional sub‐regions and engaging communities in planning processes significantly improves the effectiveness and sustainability of resource management strategies. The proposed framework enables more context‐sensitive interventions that balance environmental protection, economic development, and social equity. The research concludes that flexible, participatory, and place‐based approaches are essential for natural resource governance in ecologically diverse regions. Practically, this framework provides a scalable tool for planners, policymakers, and development organizations seeking to implement sustainable, community‐responsive natural resource management aligned with national and global development goals.

Abstract Cooperative breeding, a rare trait in <1% of mammals, is explored within African wild dog packs ( Lycaon pictus ), where alpha females typically produce the first litters, but subordinate females may also breed, resulting in second litters within the same pack. We investigated the reproductive dynamics of wild dog packs in Zimbabwe's Savé Valley Conservancy (SVC) using 14 years of data from 49 packs and 131 den sites, obtained through spoor tracking, radio telemetry, sighting reports and camera traps during denning periods. Among packs capable of multiple litters, 41.15% of breeding events produced multiple litters annually, with 24.86% of all litters from subordinate females, primarily litter sisters of the alpha. Generalized linear mixed models revealed that younger packs and those with more subordinate females were significantly more likely to produce multiple litters, indicating weaker dominance hierarchies. Within multiple litter packs, pup survival to 1 year was significantly higher for second‐born than first‐born litters. However, 2‐year survival significantly increased with higher pre‐emergence rainfall, older alpha females and higher maximum temperatures. Across both litter types, 1‐year and 2‐year pup survival significantly improved with larger packs, while 2‐year survival also significantly increased with pre‐emergence rainfall. Pups from single litters had significantly lower survival to 2 years compared to multiple litters. Despite the potential for reproductive conflict, we found low infanticide (2%) and moderate pup stealing or adoption (14%), suggesting that kin selection promotes reproductive tolerance. These findings highlight the social and ecological complexity of cooperative breeding and its conservation relevance.

Microorganisms, especially prokaryotes, are fundamental in sustaining marine ecosystems through nutrient cycling and organic matter decomposition. However, understanding what shapes their diversity and distribution remains challenging. Our study highlights the significant role ocean currents and environmental conditions play in influencing prokaryotic communities in the South China Sea-a critical marine environment due to its dynamic currents and ecological complexity. We found that currents facilitate microbial dispersal, shaping community composition over vast areas, while temperature gradients act as key selective pressures, determining which species thrive. Additionally, we reveal that both predictable environmental selection and random ecological drift significantly contribute to community structuring. By identifying keystone microbes and biomarkers sensitive to environmental change, our work offers essential insights into marine microbial ecology. These findings are crucial for predicting how microbial communities, and thus ocean health and productivity, respond to ongoing environmental changes.

Transfer of 14C from naturally depleted peat to freshwater benthic invertebrates in a controlled laboratory system.

ABSTRACTEcosystem restoration is a global priority for biodiversity recovery. However, many restoration efforts to date focus only on planting target species, without evaluating the resulting ecosystem‐level impacts on community development and trophic networks. For example, most of the world's efforts to restore tropical coral reefs have evaluated only the recovery of coral organisms. Here, we investigate the re‐establishment of different trophic groups of reef fishes in response to rapid coral recovery at one of the world's largest coral restoration projects. Within 4–6 years of coral restoration starting, coral cover returned to levels found at nearby healthy reference sites. Many groups of fishes recovered similarly quickly; herbivores, planktivores and omnivores recovered abundances equivalent to reference sites within the same time frame. However, although corallivorous fish abundance on 4–6‐year‐old restored reefs was significantly higher than on degraded reefs, it remained at just half the abundance of nearby healthy reference sites. Feeding observations demonstrated that across both healthy and restored habitat, the system's most abundant obligate corallivore (the butterflyfish Chaetodon octofasciatus) consistently targeted a small subset of corals—82% of all recorded bites were on just seven coral morphotaxa. Several of these targeted coral morphotaxa were significantly less abundant on restored reefs than on healthy reference sites. Despite reduced availability of these comparatively rare corals on restored reefs, butterflyfish maintained their dietary preferences, meaning that they exhibited a higher dietary selectivity and foraged over areas twice as large compared to healthy reefs. This demonstrates that despite a rapid recovery of coral cover and some fish groups, the reduced recovery rates of slower‐growing coral morphotaxa limit the speed at which specialist corallivores can re‐establish. Restored coral reefs may regain their coral cover within 5 years, but they will require longer time frames to achieve full trophic networks and ecological complexity.

Hydrothermal coordination dominated vegetation restoration in open-pit mine reclamation across multiple climatic zones in arid and semi-arid China.