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At least 1,099 records · Page 61

Behavioral responses of fish to a current-based hydrokinetic turbine under mutliple operational conditions

There is significant international interest in developing current-based marine and hydrokinetic (MHK) technologies to capture the power of tidal energy. However, concerns have been raised regarding the ecological effects of these projects on fish, including the risk of blade collision and behavioral impacts such as the disruption of migratory behavior and food acquisition and displacement from preferred habitats. In this study, we conducted mobile hydroacoustic surveys to track fish as they approached a tidal turbine deployed in Cobscook Bay, Maine. There was a significant decline in fish numbers with decreasing distance to the turbine, beginning approximately 140 m from the turbine. Similar declines were not observed at control transects or when the turbine was not spinning. The decline in fish numbers appeared to be the result of horizontal displacement, not vertical, movements to avoid the turbine. Noise rather than visual cues or flow field disturbance seemed to be a likely explanation for the reduced number of fish near the turbine. This finding, combined with near-field blade collision studies indicating a low probability of encounter, suggests that a single turbine poses a low collision risk to pelagic fish and that a single turbine is likely to result in minimal behavioral responses by fish. However, the risk may be different with additional devices, which will become more relevant as commercial-scale MHK arrays come under consideration. Therefore, the risks associated with commercial-scale operations will ultimately have to be evaluated to fully understand the ecological impacts of MHK devices.

42 ENGINEERING↗

Evaluating ecosystem water use efficiency under drought stress: a case study of the Helan Mountain region, northwest China

Context Water use efficiency (WUE) is a fundamental ecological indicator links carbon assimilation and water loss in terrestrial ecosystems. Understanding its responses to drought stress is essential for adaptive ecosystem management, particularly in climate-sensitive mountain landscapes. Objectives This study aimed to investigate drought-driven variations in WUE across major vegetation types in the Helan Mountain region of Northwest China. Specifically, we sought to identify dominant ecological drivers of WUE variability and to disentangle their relative importance and causal pathways. Methods We quantified WUE using the Moderate Resolution Imaging Spectroradiometer (MODIS) products and the Drought Severity Index (DSI) data from 2001 to 2020. To examine WUE – drought relationships across contrasting vegetation types, we employed a spatially explicit analytical framework integrating Random Forest (RF) modeling, partial correlation analysis, and structural equation modeling (SEM). Results Regional WUE exhibited relatively stable interannual dynamics, yet pronounced spatial heterogeneity that was strongly modulated by drought conditions. Vegetation properties, particularly Leaf Area Index (LAI) and Normalized Difference Vegetation Index (NDVI), emerged as the dominant determinants of WUE, with NDVI alone explaining over 20% of its spatial variance in forest and grassland during non-drought periods. SEM analyses revealed that climate forcing influenced WUE mainly through indirect pathways mediated by soil moisture availability and vegetation structural dynamics, rather than through direct climatic controls. Among all regulating factors, LAI acted as the central control node governing ecosystem carbon–water coupling. In contrast, short-term climatic stress, especially atmospheric demand and drought duration, exerted weak or negative direct effects on WUE. Ecosystem-specific responses were observed, with croplands mainly regulated by soil water availability, whereas forests and grasslands showed more sensitive to atmospheric drought stress. Together, these results reveal a hierarchical control framework where soil–vegetation interactions mediate climate impacts on WUE, driving strong spatial heterogeneity in drought responses across mountain landscapes. Conclusions Our findings highlight the pivotal role of indirect drought effects mediated by vegetation and soil processes in shaping ecosystem WUE. The identified soil–vegetation–climate regulatory hierarchy provides mechanistic insight into landscape–scale drought sensitivity and supports integrated modeling approaches for evaluating ecosystem resilience and sustainable management in arid mountain regions.

China↗

Scale-dependent enhancement of productivity and stability in xenic Nannochloropsis cultures

Although bacterial amendments can enhance algal productivity and stability, the development of algal-bacteria consortia for commercial-scale utilization is limited. Here, for this work, we used an established high-throughput approach to generate algal-bacteria consortia, and tested consortia performance at spatial scales from microplates to 320 L raceway ponds. We used both lab and field-reared strains of Nannochloropsis oceanica to build consortia. In some experiments, we imposed environmental perturbations to test the ability of bacteria to enhance algal culture stability. In repeated assays at the scale of well plates, flasks, and bioreactors, strong effects of bacterial amendments on N. oceanica were observed. These effects were most dramatic when cultures experienced stressors such as temperature perturbations or removal of CO 2 augmentation. Isolates that were advanced for field testing included species in the genera Algoriphagus, Oceanicaulis, and Marinobacter. When consortia were generated in the field, positive effects of bacterial amendments were not observed. The amended bacteria were outcompeted, and bacterial community composition across treatments converged after the first grow out. These results highlight the complexity of using consortia in open systems, where interactions between the existing bacterial community, inoculated bacteria, and changing environmental conditions are layered upon other differences in scale and cultivation regimes. Moreover, functionally redundant bacteria are likely present in the field. Following this work, we hypothesize that tight interactions (e.g., obligate relationships between partners) will scale more predictably to outdoor systems. We suggest relying on true synthetic ecological approaches in which the relationships between bacteria and algae partners are well understood, or synthetic ecological approaches coupled with high throughput approaches to design and test consortia. We also recommend future work to examine the effect of algae-bacteria inoculation ratios on productivity and stability, track dynamics of partners through time, and manage ponds to retain beneficial symbioses.

59 BASIC BIOLOGICAL SCIENCES↗

Visualization of in-situ chemical flow through sand using neutron radiography

Chemical movement through soil is an important process in agriculture and ecology. Observing the spatial and temporal dynamics of these processes using conventional chemical ecology methods requires techniques that are destructive and/or lack resolution. Neutron radiography has the capability to allow chemical motion through sand/soil to be tracked with high spatial and temporal resolution, and we show that it allows for the motion of hydrophobic and hydrophilic chemicals to be distinguished. This technique can have an important impact on introducing neutron radiography to a wider community and into our understanding of chemical communication dynamics between plants and movement of applied chemicals in agricultural soils.

MORRIS, KATHRYN [Xavier University]↗

Contrasting effects of land-use and local disturbance on plant and pollinator communities in wetlands

While pollinators and wetlands both provide important ecosystem services (e.g., the pollination of flowering plants and improving water quality), the relationship between the two is not well understood. Both biotic and abiotic effects can mediate the local wetland flower and pollinator community. In this study, we investigated how land use, including a land use gradient at five different radii, from 250 m to 2 km, along with anthropogenic disturbance affected pollinators in wetland ecosystems. We surveyed the abundance and diversity of plant-pollinator communities in fifteen different wetlands across two years. We also tested the relationship between water quality and temperature, and the abundance and diversity of flowering plants and pollinating insects. Our results suggest that increasing temperature, which was strongly associated with developed land use, had a negative effect on the floral display of wetland plants, as well as the abundance of all flower visitors and hover flies. Hover fly abundance was also positively associated with agricultural land use and total nitrogen in the water. Meanwhile, the abundance of female bees was affected by an interaction between temperature and disturbance: female bees were most abundant when temperatures were lower in areas of low disturbance. In contrast, pollinator species richness increased with temperature when developed land use was low, and floral diversity was strongly affected by several interactions between disturbance, land use, and water quality. Finally, the community composition of both plants and insects varied significantly among low, medium, and high disturbance categories, with weedier, non-native species being significantly associated with areas of higher disturbance and in sites with greater anthropogenic land use. We demonstrate that ecological communities shift significantly in response to anthropogenic change. Our work also illustrates the importance of quantifying interactions between land use and local disturbance with abiotic factors such as temperature and water quality on ecological systems.

Disturbance↗

Ten questions concerning housing sufficiency

Housing sufficiency is an emerging concept in the provision of environmentally sustainable housing. It aims for demand-side strategies that reduce excessive, aggregate consumption levels to promote efficient resource utilization and sustainability in the construction sector while providing everyone with a decent standard of housing. However, it is challenging to implement as it interferes with housing-related social and cultural norms. This paper poses and answers ten questions that highlight the challenges, opportunities, and examples of sufficiency strategies in the context of housing provision and the environmental crisis. Question 1 discusses the need for sufficiency as a tool to complement supply-side strategies including efficiency and renewable energy strategies in providing housing. Question 2 examines the concept of housing sufficiency from different perspectives, such as ecological economics and social ecology. Question 3 summarizes the methods used to measure housing sufficiency, with specific focus on the upper and lower limits that respect planetary boundaries and basic human needs. Questions 4 and 5 describe the benefits, potential drawbacks, and rebound effects of housing sufficiency. Questions 6 and 7 examine housing sufficiency in developed and developing countries, respectively. Questions 8 and 9 discuss design strategies, housing occupancy, and tenure models that are needed for housing sufficiency. Finally, Question 10 provides a of policies and regulations that are needed to systematically support the implementation of sufficiency strategies. The questions and answers provide insights for wider application of housing sufficiency in research and practice.

Arceo, Aldrick↗

Leveraging SETS resilience capabilities for safe-to-fail infrastructure under climate change

As the rehabilitation of infrastructure is outpaced by changes in the profile, frequency, and intensity of extreme weather events, infrastructure’s service disruptions and failures become increasingly likely. Safe-to-fail approaches for infrastructure planning and design improve the capacity of cities to adapt for uncertain climate futures by identifying social, ecological, and technological systems (SETS) capabilities to prepare for potential failure scenarios. In this work, we argue for transforming infrastructure planning and design to effectively utilize safe-to-fail approaches by navigating the opportunities and trade-offs of SETS resilience capabilities. From a technological vantage point, traditional infrastructure planning approaches account for social and ecological domains as external design conditions rather than embedded system characteristics. Safe-to-fail approaches directly challenge the isolation of the technological domain by necessitating a recognition that SETS domains are interconnected and interdependent in infrastructure systems, as such risks and system capabilities for resilience must be managed cohesively.

54 ENVIRONMENTAL SCIENCES↗

The protist Aurantiochytrium has universal subtelomeric rDNAs and is a host for mirusviruses

Viruses are the most abundant biological entities in the world's oceans, where they play important ecological and biogeochemical roles. Metagenomics is revealing new groups of eukaryotic viruses, although disconnected from known hosts. Among these are the recently described mirusviruses, which share some similarities with herpesviruses.50 years ago, "herpes-type" viral particles were found in a thraustochytrid member of the labyrinthulomycetes, a diverse group of abundant and ecologically important marine eukaryotes, but could not be further characterized by methods then available. Long-read sequencing has allowed us to connect the biology of mirusviruses and thraustochytrids. We sequenced the genome of the genetically tractable model thraustochytrid Aurantiochytrium limacinum ATCC MYA-1381 and found that its 26 linear chromosomes have an extraordinary configuration. Subtelomeric ribosomal DNAs (rDNAs) found at all chromosome ends are interspersed with long repeated sequence elements denoted as long repeated-telomere and rDNA spacers (LORE-TEARS). We identified two genomic elements that are related to mirusvirus genomes. The first is a ~300-kbp episome (circular element 1 [CE1]) present at a high copy number. Strikingly, the second, distinct, mirusvirus-like element is integrated between two sets of rDNAs and LORE-TEARS at the left end of chromosome 15 (LE-Chr15). Similar to metagenomically derived mirusviruses, these putative A. limacinum mirusviruses have a virion module related to that of herpesviruses along with an informational module related to nucleocytoplasmic large DNA viruses (NCLDVs). CE1 and LE-Chr15 bear striking similarities to episomal and endogenous latent forms of herpesviruses, respectively, and open new avenues of research into marine virus-host interactions.

59 BASIC BIOLOGICAL SCIENCES↗

Fungal endophytes

Organisms are commonly grouped into ecological guilds that reflect their shared resource use and similar ecological roles. The guild concept has been used to categorize the vast diversity of the fungal kingdom (estimated at 2.2–5 million species) into groups of fungi with common lifestyles, such as mycorrhizal symbionts, pathogens of animals and plants, and the group that is the focus of this primer — fungal endophytes of plants. Fungal endophytes have resisted scientists’ attempts to silo organisms into neat assemblages. In conclusion, scattered across the fungal tree of life and lacking few diagnostic characteristics, they are defined less by what they are than by what they are not.

Cosner, Julian [Oak Ridge National Laboratory (ORN↗

A dataset of eco-evidence tools to inform early-stage environmental impact assessments of hydropower development

The datasets described herein provide the foundation for a decision support prototype (DSP) toolkit aimed at assisting stakeholders in determining evidence of which aspects of river ecosystems have been impacted by hydropower. The DSP toolkit and its application are presented and described in the article “Evidence-based indicator approach to guide preliminary environmental impact assessments of hydropower development” [1]. Development of the DSP and the output for decision support centralize around 42 river function indicators describing the dimensionality of river ecosystems through six main categories: biota and biodiversity, water quality, hydrology, geomorphology, land cover, and river connectivity. Three main tools are represented in the DSP: A science-based questionnaire (SBQ), an environmental envelope model (EEM), and a river function linkage assessment tool (RFLAT). The SBQ is a structured survey-style questionnaire whose objective is to provide evidence of which indicators have been impacted by hydropower. Based on a global literature review, 140 questions were developed from general hypotheses regarding the impacts of dams on rivers. The EEM is a model to predict the likelihood of hydropower impacting indicators based on a several variables. The intended use of the EEM is for situations of new hydropower development where results of the SBQ are incomplete or highly uncertain. The EEM was developed through the compilation of a dataset containing attributes of dams, reservoirs, and geospatial information on environmental concerns, which was combined with data on ecological indicators documented at those sites through literature review. The model operates through 247 “envelopes” and weighting factors, representing the individual effect of each variable on each indicator, all available through spreadsheets. Finally, the RFLAT is a tool to examine causal relationships amongst indicators. Inter-indicator relationships were hypothesized based on literature review and summarized into node and edge datasets to represent the structure of a graphical network. Bayes theorem was used estimate conditional probabilities of inter-indicator relationships based on the output of the SBQ. Nodes and edges were imported into R programming environment to visualize ecological indicator networks. The datasets can be expanded upon and enriched with more detailed questions for the SBQ, building upon the EEM with to develop more sophisticated models, and identifying new relationships for the RFALT. Additionally, once the tools are applied to numerous hydropower developments, the output of the tools (e.g. evidence of impacted indicators) becomes a very useful dataset for meta-analyses of hydropower impacts.

13 HYDRO ENERGY↗

From observation to replication: machine-learning-driven quantification and replication of fine-scale fish kinematics and behavior

Long-term quantification of fish behavior is essential for aquatic ecology, wildlife telemetry, and biomechanical device development. However, the observation duration required to obtain reliable behavioral and kinematic metrics remains unclear, and few tools exist to physically reproduce natural swimming motion for controlled experimentation. We address these challenges by developing a generalizable framework that models behavioral reliability (Spearman–Brown reliability index) as a function of observation duration and derives metric-specific monitoring thresholds. Using juvenile white sturgeon (Acipenser transmontanus) as a case study, we demonstrate that the minimum duration needed for reliable estimates varies substantially across kinematic features: to exceed a reliability of 0.8, total distance traveled requires 12 days, average curvature (mm?¹) 15 days, tail-beat frequency (Hz) 8 days, and average speed (body length/s) 17 days. We further bridge digital analysis and physical testing by developing a hardware-in-the-loop simulator that reconstructs machine-learning-derived swimming kinematics with high fidelity (correlation coefficient 0.98–0.99, RMSE 1.22–1.27 mm over a 5-minute segment). This platform enables realistic, repeatable motion stimuli for evaluating aquatic sensing technologies and bio-integrated devices under controlled conditions. Together, these contributions provide a scalable approach for designing long-term behavioral studies and a data-driven connection between ecological observation and robotic experimentation.

Hwang, SungJoo↗

A spatiotemporally explicit and scalable indicator of intact lands across the conterminous United States, 1986–2023

Globally, ecologically intact areas are increasingly scarce. Agricultural expansion into previously uncultivated areas drives the loss of intact lands that might otherwise exhibit high levels of ecological integrity. Thus, the absence of cultivation can be an indicator of intact lands as measured from remote sensing data and thematic maps. Our objective for this study was to develop and compare tractable approaches based on remotely sensed satellite data to map spatial patterns of potentially intact lands across the conterminous U.S. (CONUS). Using annual cultivation probabilities derived from satellite observations, we classified and mapped potentially intact lands across CONUS from 1986 to 2023 at 30 m resolution. We created three maps, first by applying a constant cultivation probability threshold across CONUS, second by varying the threshold state-by-state to maximize state-level overall accuracies, and third by equalizing the state-level user's and producer's accuracies to minimize classification bias. Validation against 800,000+ independent ground samples resulted in CONUS-level overall accuracies ≥85% for the roughly 660 million ha of potentially intact land. Map accuracy varied with the proportion of potentially intact lands across regions, with the Pacific-Mountain and Great Plains regions exhibiting the highest accuracies, while Eastern CONUS exhibited a greater mix of potentially intact and non-intact lands and more moderate map accuracies. These novel maps and approaches can be adapted to different spatiotemporal extents to support conservation and production decisions ranging from species and ecosystems protection to reducing land conversion and climate mitigation.

agriculture↗

Land-use history, fire regime, and large-mammal herbivory affect deer-preferred plant diversity in longleaf pine woodlands

Since ecological systems often experience multiple disturbances, understanding changes in important ecological interactions, such as plant-herbivore interactions, may require studies capable of disentangling the unique and interactive effects of multiple forms of disturbance. For example, understanding how mammalian herbivores affect plant communities may require understanding how widespread past disturbances, such as agricultural land use, interact with contemporary disturbances, such as prescribed fire. Here, we tested if past agricultural land use and contemporary fire regime modified the effects of mammalian herbivory on focal plant communities by measuring the richness of plant species preferred by deer at 26 longleaf pine woodlands containing paired open and large-mammal exclusion plots. Land-use history significantly affected the community composition of deer-preferred species, and focal species were 8.19 times more likely to be present in post-agricultural sites than non-agricultural sites. Large-mammal herbivory only affected plant species richness in woodlands with low fire frequencies wherein focal species were on average 2.23 times more likely to be present in exclusion plots than open plots. These results suggest that past and present disturbances can mediate contemporary plant-animal interactions and may explain spatial patterns in the intensity of large-mammal herbivory. Our findings also suggest that common management practices, such as use of prescribed burns, may indirectly promote plant species richness by reducing deer herbivory.

60 APPLIED LIFE SCIENCES↗

Belowground cross-trophic networks impact CH4 and CO2 emissions in degraded alpine peatlands

Belowground organisms forming complex cross-trophic ecological networks are essential for maintaining peatland carbon stability and energy flow. However, how peatland degradation affects the biodiversity and cross-trophic ecological networks of soil communities remains poorly understood. Here, we examined the degradation effects on soil prokaryotes (i.e., bacteria, archaea), fungi and nematodes in alpine peatlands on the eastern Tibetan Plateau, characterized by varying water table depths (indicating degradation levels). We found that peatland degradation, accompanied by significant shifts in soil moisture and pH (P < 0.05), reduced the taxonomic richness and phylogenetic diversity of prokaryotes, fungi, and nematodes, particularly in deeper soil layers (20–50 cm). Crucially, peatland degradation weakened potential cross-trophic interactions within bipartite networks of prokaryotes-nematodes and fungi-nematodes, resulting in less than 6.5 %–28.8 % of unchanged modules. Degradation-induced changes in soil moisture and pH were identified as primary drivers of biodiversity loss and network restructuring. Furthermore, such changes of belowground cross-trophic networks (particularly prokaryote-nematode) were significantly correlated with greenhouse gas emissions, such as decreased CO2 emissions, maintained CH4 emissions (leading to a higher CH4/CO2 ratio in deep layers), and reduced temperature sensitivity (Q10) of soil respiration. These findings underscore the critical need to protect soil biodiversity and cross-trophic networks in peatlands, particularly under the threat of climate change, to preserve peatland carbon stocks and maintain ecosystem stability. Our findings highlight that belowground cross-trophic networks are pivotal to decipher soil carbon dynamics of degraded peatlands and project the fate of peatland carbon stocks under future climate change scenarios.

Cross-trophic networks↗

The influence of submarine canyons-related processes on recent benthic foraminiferal distribution, Espírito Santo Basin, Southeastern Brazil

The complex topography of submarine canyons may result in different composition of benthic foraminifera assemblages. To understand how trophic, hydrological and sedimentological conditions in submarine canyons can influence the distribution of benthic foraminifera, and to use this information to corroborate paleoenvironmental interpretations for the Holocene, we investigated recent benthic foraminiferal assemblages (total fauna >63 μm) and sedimentological data in two canyons (CANWN and CAND) in the Espírito Santo Basin (ESB) between 18°20' and 21°20' S. Surface sediment samples (0–2 cm) were collected inside the canyons (150 to 1300 m water depth) and in shelf-slope adjacent transects (50 to 1300 m water depth). The density, taxonomic diversity, and assemblage composition of benthic foraminifera change with depth and location. The distinct ecological preferences of the most abundant taxa allowed us to recognize five benthic foraminiferal groups. Three groups (V, III, and I) are present in different bathymetric sectors; Group V: outer shelf (50 m), Group III: upper, and middle – lower slope (150 to 400 m), and Group I: middle – lower slope (1000 to 1300 m). Groups II and IV show no characteristic bathymetric distribution and are present only in CAND and in CANWN, respectively. Group V consists of Hanzawaia boueana, Peneroplis planatus, and Quinqueloculina lamarckiana; Group III is dominated by Globocassidulina rossensis and Trifarina spp.; Group I consists of Globocassidulina crassa, Bolivina lowmani, Gavelinopsis versiformis, Alabaminella weddellensis, and Epistominella exigua. The main species in Group II (CAND, 150, 1000 to 1300 m) are Trifarina angulosa, Globocassidulina subglobosa, and Discorbis vilardeboanus. Group IV (middle – lower CANWN, 1000 to 1300 m), consists mainly of agglutinated species Glomospira charoides, Rhabdammina abyssorum, and Psammosphaera fusca. Further, our data suggest that the quantity (and quality) of food supply, hydrodynamic conditions and sediment properties are the main drivers controlling the bathymetric distribution of benthic foraminiferal assemblages in both canyons. The middle – lower CANNW revealed unstable trophic conditions, related to terrigenous sediment input due to turbidity currents. In CAND, the foraminiferal assemblages ecology indicated sufficient organic matter supply that favors species establishment and diversity, indicating a more productive and less unstable environment than in CANWN.

58 GEOSCIENCES↗

Is a Prescribed Fire Sufficient to Slow the Spread of Woody Plants in an Infrequently Burned Grassland? A Case Study in Tallgrass Prairie

In many mesic grasslands, such as the central Great Plains in North America, frequent fire is a key regulator of ecological processes. Long periods of infrequent fire facilitate the conversion of herbaceous-dominated grassland to woody-dominated shrubland or woodland. At the Konza Prairie Biological Station in northeast Kansas, one infrequently burned portion of the landscape has undergone transformation from grassland to woodland after nearly 30 yr without fire. In Spring 2017, a prescribed burn was implemented to assess fire effectiveness on woody plant mortality. A postfire census of 3 000+ individual woody plants identified the distribution of species by size (height), topographic position, and slope on the landscape. Mortality and canopy fire damage were calculated for each individual. In lowland locations with near-continuous shrub cover (30.7% of the landscape), woody plants were unaffected by fire. However, in upland and slope locations, where shrubs and trees were sparser, survival probability varied by topographic position and species. In these locations 68% of all woody individuals experienced 90% or greater fire damage to the canopy, with 56% of these individuals exhibiting new canopy regrowth within 2 mo after the fire. Here, the two most abundant woody shrubs, Cornus drummondii and Rhus aromatica, showed high survival at all height classes and landscape positions. The two abundant tree species, Gleditsia triacanthos and Juniperus virginiana, showed increased survival probability with tree height that varied by landscape position. Survival of J. virginiana also varied according to proximity and size of neighboring clonal shrubs, providing a mechanism for persistence of this fire-sensitive tree species even at small height classes. The probability survival curves developed here are useful for managers assessing when to prescribe fire to maximize mortality for J. virginiana and provide insight relevant for broader ecological understanding of woody encroachment within grasslands throughout the world.

54 ENVIRONMENTAL SCIENCES↗

Tracking seasonal variability in plant traits from spaceborne PRISMA and NEON AOP across forest types and ecoregions

Plant traits serve as critical indicators of how plants adapt to environmental changes and influence ecosystem functions. While airborne hyperspectral remote sensing effectively maps plant traits through detailed reflectance properties, it is limited by cost and scale, making large-scale and temporal studies challenging. The recently launched spaceborne hyperspectral imager, PRecursore IperSpettrale della Missione Applicativa (PRISMA), offers frequent, large scale and high-fidelity observations on a spatial resolution of 30 m and a revisit time of around 29 days, making it suitable for large-scale seasonal trait mapping. However, their potential remains largely unexplored. This study developed a multi-stage framework by leveraging the PRISMA spaceborne hyperspectral data and National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP) hyperspectral data to investigate the seasonal dynamics of four key plant traits — chlorophyll content, carotenoid content, equivalent water thickness, and nitrogen content — across eleven NEON sites representing diverse forest types and ecoregions in the contiguous U.S. Our results demonstrated that PRISMA hyperspectral data can reliably track seasonal variability in plant traits, achieving overall R 2 values ranging from 0.78 to 0.88 and normalized root mean square error (NRMSE) values ranging from 5.4% to 8.4% for the four traits. Seasonal patterns revealed bell-shaped trajectories for chlorophyll and carotenoids, while equivalent water thickness decreased steadily across most sites, driven by structural changes during leaf maturation and senescence. Nitrogen content exhibited less pronounced seasonal variation but followed expected nutrient resorption patterns. Analysis of environmental drivers showed that seasonal variability is primarily controlled by solar radiation and day length in northern sites, vapor pressure in semi-arid regions, and temperature in mid-southeastern sites. Spatial variability, meanwhile, was primarily driven by soil properties, particularly during the peak growing season. However, the influence of soil variables slightly declines toward the end of the season at several sites, as climatic factors become more prominent. This study highlights the capability of PRISMA, and potentially other similar spaceborne hyperspectral data for large-scale, time-series plant trait mapping and provides valuable insights into the interactions between plant traits and environmental factors. In conclusion, these findings contribute to advancing our understanding of plant functional ecology and improving predictions of ecosystem responses to environmental changes.

Environmental drivers↗

Predicting measures of soil health using the microbiome and supervised machine learning

Soil health encompasses a range of biological, chemical, and physical soil properties that sustain the commercial and ecological value of agroecosystems. Monitoring soil health requires a comprehensive set of diagnostics that can be cost-prohibitive for routine analyses. The soil microbiome provides a rich source of information about soil properties, which can be assayed in a high-throughput, cost-effective way. We evaluated the accuracy of random forest (RF) and support vector machine (SVM) regression and classification models in predicting 12 measures of soil health, tillage status, and soil texture from 16S rRNA gene amplicon data with an operationally relevant sample set. We validated the efficacy of the best performing models against independent datasets and also tested best practices for processing microbiome data for use in machine learning. Soil health metrics could be predicted from microbiome data with the best models achieving a Kappa value of ~0.65, for categorical assessments, and a R2 value of ~0.8, for numerical scores. Biological health ratings were better predicted than chemical or physical ratings. Validation with independent datasets revealed that models had general predictive value for soil properties, including yield. The ecological profiles of several taxa important for model accuracy matched the observed relationships with soil health, including Pyrinomonadaceae, Nitrososphaeraceae, and Candidatus Udeaobacter. Models trained at the highest taxonomic resolution proved most accurate, with losses in accuracy resulting from rarefying, sparsity filtering, and aggregating at higher taxonomic ranks. Furthermore, our study provides the groundwork for developing scalable technology to use microbiome-based diagnostics for the assessment of soil health.

16S rRNA gene↗