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BRCore: an R package implementing flexible selection of core taxa using contribution to Bray-Curtis dissimilarity and neutral model fitting

Identifying core taxa in microbial ecology highlights groups likely to participate in a broad range of potential ecological interactions. Here, we present BRCore, an R package to identify core taxa using abundance-occupancy distributions and beta-diversity contributions across ecological niches, and predict stochastic and deterministic taxa.

59 BASIC BIOLOGICAL SCIENCES

Geographic source attribution of honey by strontium isotope analyses: Latvia and India measurements compared to model predictions in a feasibility study

Strontium isotope ratios ( 87 Sr/ 86 Sr) can be used to determine the geographic origin of agricultural products. Here, in this study, we measured the 87 Sr/ 86 Sr of honey samples from Richland, WA, USA, Latvia, and India, and compared the results to published 87 Sr/ 86 Sr from surrounding areas and values predicted based upon a random forest isoscape model (Bataille et al., 2020). While the 87 Sr/ 86 Sr of the honey samples compared well with previously published data, the model did not accurately predict the 87 Sr/ 86 Sr of the honey samples, demonstrating that further refinement of the model would be beneficial. Because Sr cycling in terrestrial ecosystems is complex, the 87 Sr/ 86 Sr of honey is likely to reflect several sources (e.g., nectar, surface water, dust) and may change over time. In order to accurately predict the 87 Sr/ 86 Sr of honey, models must consider local geology, ecology, and bee behavior. Additional research examining how Sr is incorporated into honey is needed to inform models.

60 APPLIED LIFE SCIENCES

Human–Earth system interactions under climate change

This special issue, titled ‘Focus on human–Earth system interactions under climate change,’ compiles cutting-edge research that deepens our understanding of the complex feedback mechanisms between anthropogenic activities and Earth system processes in the context of a changing climate (figure 1). The featured articles employ a diverse array of methodologies—including field studies, remote sensing, modeling, and socio-ecological analyses—to explore these interconnections. A unifying theme across these contributions is the imperative to bridge disciplinary divides, integrating physical Earth sciences with social sciences to fully capture the spectrum of human-Earth system interactions. Key topics addressed the impacts of human activities on natural systems, encompassing land-use change and water resource management on biogeochemistry, climate dynamics, and feedback on the climate system and socioeconomics from local to global scales under a changing climate.

Li, Huidong [Vanderbilt Univ., Nashville, TN (Unit

Electromagnetic Induction (EMI) Data, 2024, Trail Creek, Colorado

This dataset contains Electromagnetic Induction (EMI) data collected at Trail Creek, Colorado, in 2024. EMI surveys were conducted to investigate the spatial distribution of electrical conductivity in the subsurface, providing insights into soil moisture and subsurface geological features. The surveys were performed along multiple transects to capture variations in conductivity influenced by changes in soil composition, moisture content, and underlying geological structures. This dataset complements other geophysical data collected in the region, including Electrical Resistivity Tomography (ERT) and Terrestrial LiDAR Scanning (TLS), providing a detailed understanding of the subsurface and its impact on surface vegetation and hydrological processes. The data are valuable for environmental geophysics, ecological research, and hydrological modeling in mountainous ecosystems. The files include: - data.zip: the raw EMI data (.csv) - inversion.zip: the inverted resistivity model (.csv and .kml) - kriging.zip: the kriging resistivity model (.csv, .tif, .kmz) - flmd.csv: file level metadata file describing all files within this dataset - dd.csv: data dictionary file describing the column headers within CSV files This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

CMD Mini-Explorer

Weak-form inference for hybrid dynamical systems in ecology

Species subject to predation and environmental threats commonly exhibit variable periods of population boom and bust over long timescales. Understanding and predicting such behaviour, especially given the inherent heterogeneity and stochasticity of exogenous driving factors over short timescales, is an ongoing challenge. A modelling paradigm gaining popularity in the ecological sciences for such multi-scale effects is to couple short-term continuous dynamics to long-term discrete updates. We develop a data-driven method utilizing weak-form equation learning to extract such hybrid governing equations for population dynamics and to estimate the requisite parameters using sparse intermittent measurements of the discrete and continuous variables. The method produces a set of short-term continuous dynamical system equations parametrized by long-term variables, and long-term discrete equations parametrized by short-term variables, allowing direct assessment of interdependencies between the two timescales. We demonstrate the utility of the method on a variety of ecological scenarios and provide extensive tests using models previously derived for epizootics experienced by the North American spongy moth ( Lymantria dispar dispar ).

54 ENVIRONMENTAL SCIENCES

A novel open-source cultivation system helps establish the first full cycle chemosynthetic symbiosis model system involving the giant ciliate Zoothamnium niveum

Symbiotic interactions drive species evolution, with nutritional symbioses playing vital roles across ecosystems. Chemosynthetic symbioses are globally distributed and ecologically significant, yet the lack of model systems has hindered research progress. The giant ciliate Zoothamnium niveum and its sulfur-oxidizing symbionts represent the only known chemosynthetic symbiosis with a short life span that has been transiently cultivated in the laboratory. While it is experimentally tractable and presents a promising model system, it currently lacks an open-source, simple, and standardized cultivation setup. Following the FABricated Ecosystems (EcoFABs) model, we leveraged 3D printing and polydimethylsiloxane (PDMS) casting to develop simple flow-through cultivation chambers that can be produced and adopted by any laboratory. The streamlined manufacturing process reduces production time by 86% and cuts cost by tenfold compared to the previous system. Benchmarking using previously established optimal growth conditions, the new open-source cultivation system proves stable, efficient, more autonomous, and promotes a more prolific growth of the symbiosis. For the first time, starting from single cells, we successfully cultivated the symbiosis in flow-through chambers for 20 days, spanning multiple generations of colonies that remained symbiotic. They were transferred from chamber to chamber enabling long-term cultivation and eliminating the need for continuous field sampling. The chambers, optimized for live imaging, allowed detailed observation of the synchronized growth between the host and symbiont. Highlighting the benefit of this new system, we here describe a new step in the first hours of development where the host pauses growth, expels a coat, before resuming growth, hinting at a putative symbiont selection mechanism early in the colony life cycle. With this simple, open-source, cultivation setup, Z. niveum holds promises for comparative studies, standardization of research and wide adoption by the symbiosis research community.

59 BASIC BIOLOGICAL SCIENCES

Organic molecules are deterministically assembled in variably inundated river sediments, but drivers remain unclear

Dissolved organic matter (DOM) is central to ecosystem function. A fundamental challenge is understanding the processes leading to variation in the chemistry of organic molecules that comprise DOM. Here we study these processes in variably inundated riverbed sediments, as an understudied, yet ubiquitous component of rivers. Using null-model approaches adopted from community ecology, we found that within-site variation in environmental conditions caused non-random (i.e., deterministic) shifts in DOM chemistry. Deterministic shifts were observed across diverse biomes, though the strength of determinism varied substantially. We found that the strength of determinism decreased with increasing sediment moisture, but in the form of a constraint space. Many systems fell below the upper constraint boundary, however. We propose a conceptual model based on our results and other publications in which DOM assemblages are hypothesized to be increasingly deterministic across the continuum from the river water column to saturated sediment pore spaces to unsaturated and dry soils/sediments.

59 BASIC BIOLOGICAL SCIENCES

Linking Community‐Climate Disequilibrium to Ecosystem Function

Turnover in species composition often lags behind the pace of climate change, resulting in mismatches between climate and communities. However, the impact of these community‐climate disequilibria on ecosystem functions is rarely considered, and current methods for measuring disequilibria assume that species ranges were, until recently, in equilibrium with climate. Here, in this work, we develop a simple theoretical model to address both of these problems by linking community‐climate disequilibrium with ecosystem functioning. We show how disequilibrium can impair functioning in the near‐term even when climate change is expected to enhance functioning in the long‐term. Responses are most likely to change over time in communities where turnover is slow, the impact of disequilibrium counteracts the direct effects of climate on ecosystem function, and pre‐existing disequilibrium is large. These findings emphasise the importance of precise and unbiased estimates of community‐climate disequilibria for improving ecological forecasts. By fitting our model to time series of both climate and ecosystem function from a metacommunity simulation, we show the potential for community‐climate disequilibrium to be inferred without direct knowledge about species' distributions or climatic tolerances. We end by outlining a research agenda to apply dynamic disequilibrium concepts and test novel hypotheses across diverse ecosystems.

climate change

Fine-scale landscape characteristics, vegetation composition, and snowmelt timing control phenological heterogeneity across low-Arctic tundra landscapes in Western Alaska

The Arctic is warming at over twice the rate of the rest of the Earth, resulting in significant changes in vegetation seasonality that regulates annual carbon, water, and energy fluxes. However, a crucial knowledge gap exists regarding the intricate interplay among climate, permafrost, and vegetation that generates high phenology variability across extensive tundra landscapes. This oversight has led to significant discrepancies in phenological patterns observed across warming experiments, long-term ecological observations, and satellite and modeling studies, undermining our ability to understand and forecast plant responses to climate change in the Arctic. To address this problem, we assessed plant phenology across three low-Arctic tundra landscapes on the Seward Peninsula, Alaska, using a combination of in-situ phenocam observations and high-resolution PlanetScope CubeSat data. We examined the patterns and drivers of phenological diversity across the landscape by (1) quantifying phenological diversity among dominant plant function types (PFTs) and (2) modeling the interrelations between plant phenology and fine-scale landscape features, such as topography, snowmelt, and vegetation. Our findings reveal that both spring and fall phenology varied significantly across Arctic PFTs, accounting for about 25%–44% and 34%–59% of the landscape-scale variation in the start of spring [SOS] and start of fall [SOF], respectively. Deciduous tall shrubs (e.g. alder and willow) had a later SOS (~7 d behind the mean of other PFTs), but completed leaf expansion (within 2 weeks) considerably faster compared to other PFTs. We modeled the landscape-scale variation in SOS and SOF using Random Forest, which showed that plant phenology can be accurately captured by a suite of variables related to vegetation composition, topographic characteristics, and snowmelt timing (variance explained: 53%–68% for SOS and 59%–82% for SOF). Notably, snowmelt timing was a crucial determinant of SOS, a factor often neglected in most spring phenology models. Our study highlights the impact of fine-scale vegetation composition, snow seasonality, and landscape features on tundra phenological heterogeneity. Improved understanding of such considerable intra-site phenological variability and associated proximate controls across extensive Arctic landscapes offers critical insights for representation of tundra phenology in process models and associated impact assessments with climate change.

54 ENVIRONMENTAL SCIENCES

Flash flourishing of Northern Hemisphere vegetation and its drivers

Rapid surges in vegetation growth—defined by thresholds in growth rate and duration—are critical yet understudied indicators of ecosystem responses to environmental change. Here, we investigate spatiotemporal patterns of such abrupt, short-lived flash flourishing events across the northern extratropical latitudes (NEL) from 2003 to 2022. We find more frequent occurrence of flash flourishing events at high latitudes (≥45° N), where their incidence is 1.6 times higher than at mid-latitudes. Moreover, there is an increasing tendency in frequency, duration, and intensity of flash flourishing events over the past two decades, alongside consistent rises in vegetation indices across onset, post-onset, and entire phases. Model simulations attribute these multiyear increases primarily to elevated atmospheric CO 2 , while temperature and radiation predominantly control phase-specific variability, with onset traits strongly predicting subsequent phenological responses. Together, these findings identify the patterns and drivers of NEL flash flourishing and highlight their large-scale impacts on ecosystem dynamics, offering critical insights for model improvement and the assessment of ecological shifts.

Kong, Xiangxu [Nanjing University of Information S

Using an Isotope Enabled Mass Balance to Evaluate Existing Land Surface Models

Abstract Land surface models (LSMs) play a crucial role in elucidating water and carbon cycles by simulating processes such as plant transpiration and evaporation from bare soil, yet calibration often relies on comparing LSM outputs of landscape total evapotranspiration ( ET ) and discharge with measured bulk fluxes. Discrepancies in partitioning into component fluxes predicted by various LSMs have been noted, prompting the need for improved evaluation methods. Stable water isotopes serve as effective tracers of component hydrologic fluxes, but data and model integration challenges have hindered their widespread application. Leveraging National Ecological Observation Network measurements of water isotope ratios at 16 US sites over 3 years combined with LSM‐modeled fluxes, we employed an isotope‐enabled mass balance framework to simulate ET isotope values ( δET ) within three operational LSMs (Mosaic, Noah, and VIC) to evaluate their partitioning. Models simulating δET values consistent with observations were deemed more reflective of water cycling in these ecosystems. Mosaic exhibited the best overall performance (Kling‐Gupta Efficiency of 0.28). For both Mosaic and Noah there were robust correlations between bare soil evaporation fraction and error (negative) as well as transpiration fraction and error (positive). We found the point at which errors are smallest ( x ‐intercept of the multi‐site regression) is at a higher transpiration fraction than is currently specified in the models. Which means that transpiration fraction is underestimated on average. Stable isotope tracers offer an additional tool for model evaluation and identifying areas for improvement, potentially enhancing LSM simulations and our understanding of land‐surface hydrologic processes.

58 GEOSCIENCES

A Computational Workflow of Elucidating Viral Impact on Mediating Microbial Response to In-situ Experimental Warming: Bridging microbial modeling to carbon and mineral modeling

Viruses are abundant in soils and shape microbial communities in ways that can potentially influence ecosystem processes, yet their contributions to carbon cycling and mineral transformations remain poorly understood. Here we present a multi-phase framework that links virus-host interactions to soil biogeochemistry by combining ecological simulations, genome- and community-scale metabolic modeling, and statistical and machine-learning analyses. We first calibrated microbial abundance profiles under explicit infection scenarios to capture how viral pressure alters community structure, then explored alternative interaction strategies, including kill-the-winner, piggyback-the-winner, and mixed lytic-lysogenic modes, through forward simulations. These ecological shifts were translated into metabolic consequences using exchange fluxes summarized into biologically meaningful categories, while integrated statistical and machine-learning screens elevated subtle but consistent signals. Application of this framework revealed that viral infections shift the balance between organic and inorganic fluxes, redirecting metabolism from diffuse organic transformations toward inorganic pools such as protons and CO 2 , directly linking viral regulation to respiration and soil carbon balance. The roll-up analysis also isolated perturbations in critical mineral ions, including magnesium, manganese, zinc, and copper, which serve as essential enzymatic cofactors. In piggyback-the-winner scenarios, uptake of these ions was strongly suppressed. Contrasting viral strategies produced distinct community structures and metabolic outcomes, from broad suppression under kill-the-winner dynamics to dramatic redistributions under high-lytic and high-gain lysogenic regimes that collapsed vulnerable microbial populations while promoting opportunists. Together, these results provide a tractable path to trace viral perturbations from host abundance shifts to metabolic flux adjustments and ecosystem-scale processes, offering a practical way to include viruses in earth system models.

54 ENVIRONMENTAL SCIENCES

A Numerical Modeling Framework for Flocculation and Cohesive Sediment Transport in the Wave Bottom Boundary Layer

Flocculation, a critical process in coastal and estuarine systems, plays a significant role in sediment transport, nutrient cycling, and ecological health. This study develops a cohesive sediment transport modeling framework tailored to the wave bottom boundary layer under dilute and equilibrium conditions, explicitly incorporating flocculation effects via a Population Balance Equation (PBE). Using Direct Numerical Simulation, six baseline cases, each with a distinct sediment concentration profile resulting from a constant settling velocity and critical erosion shear stress, are generated to drive the PBE flocculation model for given floc yield strength and stickiness. Results reveal that flocculation significantly influences sediment concentration profiles promoting three distinct stages, well‐mixed, transition to lutocline, and well‐developed lutocline. At low concentrations with well‐mixed profiles, cohesive floc properties are less significant, and turbulence is a main flocculation driver. In contrast, as concentration increases, cohesive floc properties become crucial, facilitating lutocline formation. Here, the analysis also highlights limitations of depth‐averaged settling velocity as a parameterization. It is suitable for well‐mixed and transitional profiles but fails in well‐developed lutoclines, where empirical formulations that explicitly incorporate turbulent shear rate and sediment concentration better capture variability. This study underscores the necessity of incorporating flocculation effects into sediment transport models to enhance predictions of sediment dynamics in wave bottom boundary layers.

Penaloza‐Giraldo, Jorge A. [Oak Ridge National Lab

The Global Spectra-Trait Initiative: A database of paired leaf spectroscopy and functional traits associated with leaf photosynthetic capacity

Accurate assessment of leaf functional traits is crucial for a diverse range of applications from crop phenotyping to parameterizing global climate models. Leaf reflectance spectroscopy offers a promising avenue to advance ecological and agricultural research by complementing traditional, time-consuming gas exchange measurements. However, the development of robust hyperspectral models for predicting leaf photosynthetic capacity and associated traits from reflectance data has been hindered by limited data availability across species and environments. Here we introduce the Global Spectra-Trait Initiative (GSTI), a collaborative repository of paired leaf hyperspectral and gas exchange measurements from diverse ecosystems. The GSTI repository currently encompasses over 7500 observations from 397 species and 41 sites gathered from 36 published and unpublished studies, thereby offering a key resource for developing and validating hyperspectral models of leaf photosynthetic capacity. The GSTI database is developed on GitHub (https://github.com/plantphys/gsti, last access: 4 January 2026) and published to ESS-DIVE https://doi.org/10.15485/2530733, Lamour et al., 2025). It includes gas exchange data, derived photosynthetic parameters, and key leaf traits often associated with traditional gas exchange measurements such as leaf mass per area and leaf elemental composition. By providing a standardized repository for data sharing and analysis, we present a critical step towards creating hyperspectral models for predicting photosynthetic traits and associated leaf traits for terrestrial plants.

Lamour, Julien [Université of Toulouse (France); U

Evaluation of daily gridded climate products using in situ FLUXNET data and tree growth modeling

Gridded climate data products have facilitated research in climate and ecology by providing meteorological data continuously across large spatial scales. However, the sensitivity of scientific outcomes to dataset choice remains poorly understood, and evaluation using station-based records can favor datasets built heavily on weather stations. Here, we evaluate seven high-resolution daily gridded datasets covering the contiguous United States using independent meteorology from the FLUXNET2015 dataset, with a focus on the implications of dataset choice for process-based tree growth modeling. We find that gridded products tend to capture temperature accurately while consistently overestimating the magnitude and frequency of precipitation and its extremes. Moreover, datasets vary in how they define a ‘day,’ which significantly affects temporal alignment with FLUXNET2015 observations. Despite differences among the datasets, the interannual variability in tree ring simulations is insensitive to dataset choice, likely because daily-scale biases are averaged out through accumulated growth across several months. However, inaccuracies in temperature and precipitation can significantly bias modeled xylem cell production, with systematically higher annual precipitation in the gridded datasets leading to greater xylem production compared to simulations using in situ data. Our results suggest that model applications, especially those that integrate to time scales longer than one day, are likely insensitive to climate dataset choice, but applications that are sensitive to daily climate variations or to absolute climate values need to carefully consider biases in gridded climate products.

54 ENVIRONMENTAL SCIENCES

Intraspecific Reaction Norm Variation Controls the Eco-Evolutionary Consequences of Environmental Change

As environmental change accelerates globally, understanding concurrent organismal, species, and community responses is increasingly vital. Here, we examine these collective responses by incorporating genotype-specific thermal reaction norms into an eco-evolutionary predator-prey model, allowing us to track simultaneous phenotypic, ecological, and evolutionary responses to environmental change within ecological communities. We show that the reaction norms expressed by genotypes within a population determine how a community switches between different eco-evolutionary outcomes with changes in temperature. We identify how different components of phenotypic variation in thermal reaction norms—environmental (E), additive environmental and genetic (E + G), and gene-by-environment interactions (G × E)—influence eco-evolutionary dynamics and outcomes as temperature changes. Furthermore, our findings underscore how complex eco-evolutionary responses to environmental change ultimately emerge from variation in reaction norms among genotypes, offering new mechanistic insights into environmental impacts on adaptation, the maintenance of phenotypic and genetic variation, and ecological stability, which is crucial for understanding and predicting eco-evolutionary effects of rapid environmental change in the future.

Eco-evolutionary

The architecture of resilience: a genome assembly of Myrothamnus flabellifolia sheds light on desiccation tolerance and sex determination

Myrothamnus flabellifolia is a dioecious resurrection plant endemic to southern Africa that has become an important model for understanding desiccation tolerance. Despite its ecological and medicinal significance, genomic and transcriptomic resources for the species are limited. We generated a chromosome-level, haplotype-resolved reference genome assembly and annotation for M. flabellifolia and conducted transcriptomic profiling across a natural dehydration–rehydration time course in the field. Genome architecture and sex determination were characterized, and co-expression network and cis-regulatory element (CRE) enrichment analyses were used to investigate dynamic responses to desiccation. The 1.28-Gb genome exhibits unusually consistent chromatin architecture with unique chromosome organization across highly divergent haplotypes. We identified an XY sexual system with a small sex-determining region on Chromosome 8. Transcriptomic responses varied with dehydration severity, pointing to early suppression of growth, progressive activation of protective mechanisms, and subsequent return to homeostasis upon rehydration. Late embryogenesis abundant and early light-induced protein transcripts were dynamically regulated and showed enrichment of abscisic acid and stress-responsive CREs pointing toward conserved responses. Together, this study provides foundational resources for understanding the genomic architecture and reproductive biology of M. flabellifolia and offers new insights into the mechanisms of desiccation tolerance.

chromosome structure

Infection and Genomic Properties of Single- and Double-Stranded DNA Cellulophaga Phages

Bacterial viruses (phages) are abundant and ecologically impactful, but laboratory-based experimental model systems vastly under-represent known phage diversity, particularly for ssDNA phages. Here, we characterize the genomes and infection properties of two unrelated marine flavophages—ssDNA generalist phage phi18:4 (6.5 Kbp) and dsDNA specialist phage phi18:1 (39.2 Kbp)—when infecting the same Cellulophaga baltica strain #18 (Cba18), of the class Flavobacteriia. Phage phi18:4 belongs to a new family of ssDNA phages, has an internal lipid membrane, and its genome encodes primarily structural proteins, as well as a DNA replication protein common to ssDNA phages and a unique lysis protein. Phage phi18:1 is a siphovirus that encodes several virulence genes, despite not having a known temperate lifestyle, a CAZy enzyme likely for regulatory purposes, and four DNA methyltransferases dispersed throughout the genome that suggest both host modulation and phage DNA protection against host restriction. Physiologically, ssDNA phage phi18:4 has a shorter latent period and smaller burst size than dsDNA phage phi18:1, and both phages efficiently infect this host. These results help augment the diversity of characterized environmental phage–host model systems by studying infections of genomically diverse phages (ssDNA vs. dsDNA) on the same host.

Howard-Varona, Cristina (ORCID:0000000241495818)