413 papers
This study demonstrates that commercial eDNA metabarcoding services exhibit highly variable performance and significant inaccuracies in detecting stream fish communities, challenging their current reliability for large-scale ecological assessments without standardized protocols and comprehensive reference databases.
This study demonstrates that long-term scale cortisol levels in the Mexican tetra (*Astyanax mexicanus*) vary significantly between surface and cave ecotypes and are influenced by habitat stability, indicating that evolutionary adaptations to diverse environments shape the species' chronic stress physiology.
This study reveals that Japan's coral bleaching events are widespread despite failing to trigger Degree Heating Week (DHW) alerts because the metric's reliance on Maximum Monthly Mean anomalies creates a structural insensitivity across latitudes, rendering absolute temperature thresholds a significantly more effective predictor of bleaching severity.
This paper proposes that the universal scaling of metabolic rate with body size (Kleiber's law) emerges from an information-theoretic optimum in stochastic cellular dynamics, where organism-level fluctuations become maximally dependent on size and minimally sensitive to microscopic noise.
This study demonstrates that in Nares Strait, functional diversity of benthic macrofauna is a superior predictor of organic matter remineralization rates than taxonomic diversity, suggesting that ongoing sea ice decline could shift community composition toward deposit feeders, thereby accelerating remineralization and potentially reducing the Arctic's capacity as a carbon sink.
A laboratory column study on Metehara Sugar Estate's saline-sodic Cambisols determined that applying phosphogypsum at 100% or higher of the gypsum requirement combined with 3–4 pore volumes of leaching water is the most effective strategy for reducing soil salinity and sodicity to levels suitable for crop production, though field validation is recommended before finalizing implementation guidelines.
BatSpot is a retrainable convolutional neural network with a user-friendly interface that outperforms existing tools in automatically detecting and classifying bat echolocation search calls, buzzes, and social calls, while enabling researchers to easily adapt the model to specific geographic regions for improved conservation monitoring.
This study demonstrates that windthrow-generated tip-up mounds create drier, well-aerated soil conditions that selectively favor black cherry seedling survival over red oak, offering critical regeneration niches for specific tree species in Carolinian forests increasingly constrained by white-tailed deer browsing on the forest floor.
This study demonstrates that internal climate variability can produce qualitatively different and even reversed species distribution outcomes across marine and terrestrial ecosystems, necessitating flexible, stress-tested decision-making strategies that account for multiple plausible climate futures rather than relying on single best-estimate projections.
While wing biopsies from common vampire bats show a lower probability of detecting blood-borne pathogens compared to blood samples, they remain a viable, less invasive method for initial pathogen discovery and characterizing infections, though they are less ideal for accurately estimating infection prevalence.
This study demonstrates that herbarium specimens are reliable resources for tracking plant phenological responses to climate change in montane systems, showing consistent flowering time estimates and sensitivity to snow density with field observations, though they may slightly underestimate temperature sensitivity and benefit from focusing on early-flowering individuals to capture community-level trends.
By analyzing 14,835 PRRSV-2 sequences from 2015 to 2024, this study quantifies the regional spread dynamics of 156 viral variants across the United States, revealing that the Upper Midwest serves as a central hub for both emergence and introduction while interior regions experience faster dispersal than coastal pathways, thereby providing critical data to enhance epidemiological models and disease preparedness.
This study analyzes over 42,000 forest plots across North America to quantify the risk of trait misalignment between current forest communities and projected late-century climates, revealing that high-latitude and montane conifer forests face the greatest functional incompatibility while high species richness serves as a critical buffer against these adverse outcomes.
Although stage-dependent biotic interactions can theoretically alter stochastic competitive dynamics, the study finds that simpler models ignoring these interactions remain highly accurate for forecasting because their practical importance is contingent on low temporal fluctuations in population stage structure rather than species life-history strategies.
This systematic review of 20 studies reveals that research on soil microbial communities in military-impacted environments relies heavily on 16S rRNA sequencing for explosive and heavy metal contamination, while suffering from significant methodological gaps including inconsistent physicochemical characterization and a lack of fungal, fauna, and soil compaction data.
This paper presents a transparent, manual-matching protocol that derives regional elevation correction factors from reference weather stations to standardize temperature data across heterogeneous study sites, thereby enabling robust cross-site ecological meta-analyses for taxa with documented altitudes.
This paper presents an automated, open-source deep learning framework using the Segment Anything Model (SAM) to predict the weight of juvenile Chinook Salmon from 2D images with high accuracy (R²=0.99), thereby minimizing the need for physical handling of threatened fish populations.
By integrating phylogenetic information with community assembly models, this study reveals that local species coexistence in plant communities relies on a surprisingly high number of independent traits—often exceeding species richness—thereby challenging the traditional view that communities are structured by only a few key characteristics.
This study demonstrates that multi-generational exposure to environmental polyaromatic hydrocarbons drives the evolution of metabolic insecticide resistance in *Anopheles coluzzii* by upregulating detoxification genes, particularly CYP6M4, which metabolizes both pollutants and insecticides.
This paper introduces a novel LLM-based pipeline that rapidly extracts morphological trait data from fungal species descriptions to accelerate ecological research, demonstrating promising results despite observed variations in accuracy and systematic biases.