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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Optimizing invader suppression to restore native species: Leveraging species traits to overcome collateral damage

Strategies to control ongoing biological invasions are often developed by modelling the invasive species' population and aiming to reduce its abundance. However, if the ultimate objective is to protect and restore native species, focussing solely on the invader may not be optimal because it does not account for (i) species interactions that can cause the invader's impacts to depend nonlinearly on its abundance, (ii) collateral damages to native species incurred due to nonspecific removal methods or (iii) native-invader trait differences. Here, to identify an invader suppression strategy that maximizes average native population size, we applied optimal control theory to a two-species model of a native species threatened by an invasive competitor. We examined trade-offs between iterative physical removals that selectively target invaders and intensifiable chemical control that is nonselective but has higher efficacy. We found that while iterative removals were capable of supporting large native populations when applied continuously, cost could be prohibitively high. In contrast, when favourable native-invader trait differences enabled native species to re-establish more quickly than invaders, intensifiable methods could achieve substantial restoration benefits at lower cost by focussing removal effort into periodic, high-efficacy events. In a metapopulation, removals that rotated among spatial patches were optimal when the native species had higher dispersal, whereas synchronous removals were preferred when native recovery was initiated locally and the invader could disperse. For a case study in Hawaiian streams, we compared how effective two alternative methods of removing invasive live-bearing fishes (poeciliids) might be at restoring the endemic freshwater goby Sicyopterus stimpsoni. We found that rotenone (a piscicidal chemical) offered superior benefits when the control budget was small and efficacy was high, but that electrofishing (use of electricity to manually collect target fish) was better with larger budgets and in many lower-efficacy scenarios. Synthesis and applications. Our findings demonstrate that, by accounting for species interactions and collateral damage, invasive species control strategies can be optimized in light of species traits. Choices about the timing, locations and types of removal events present opportunities to increase the efficiency with which invasive species suppression benefits native species.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Comparative Study on the Machine Learning-Based Prediction of Adsorption Energies for Ring and Chain Species on Metal Catalyst Surfaces

Computation of adsorption and transition state energies for a large number of surface intermediates for numerous active site models pose significant computational overhead in computational screening of catalysts. Machine learning (ML) techniques can be used to predict part of these energies. To predict the energies, ML models need to be fed appropriate metal and species descriptors. For complex surface chemistries, the structures of the intermediate species can vary greatly. In this paper, working with the hydrodeoxygenation of succinic acid on six different metal surfaces, we have studied the effect of linear and non-linear ML models used along with pen-and-paper based species descriptors and two categories of metal descriptors on two different categories of intermediate species: chain and ring. More specifically, our computations include the prediction of chain species when trained on only chain species and also when trained on both chain and ring species. Similar computations were performed for predictions of ring species. In each case, results of linear ML models were compared with kernel based non-linear models. Our results indicate that ring species data does not improve the prediction of chain species. Similarly, chain species data does not improve the prediction of ring species. The use of non-linear ML models, however, did help to minimize the prediction errors compared to the linear models. Furthermore, the study also shows that electronic or adsorption energy based metal descriptors along with bond count based species fingerprints can achieve a mean absolute error (MAE) of less than 0.2 eV for complex chain molecules when used with an appropriate machine learning model.

Adsorption↗
DOE OSTI2021

Hydraulic architecture explains species moisture dependency but not mortality rates across a tropical rainfall gradient

Aim Intensified droughts are affecting tropical forests across the globe. However, the underlying mechanisms of tree drought response and mortality are poorly understood. Hydraulic traits and especially hydraulic safety margins (HSMs), i.e. the extent to which plants buffer themselves from thresholds of water stress, provide insights into species-specific drought vulnerability. Methods We investigated hydraulic traits during an intense drought triggered by the 2015-2016 El Niño on 27 canopy trees across three tropical forest sites with differing precipitation. We capitalized on the drought event as a time when plant water status might approach or exceed thresholds of water stress. We investigated the degree to which these traits varied across the rainfall gradient, as well as relationships amongst hydraulic traits and species-specific optimal moisture and mortality rates. Results There were no differences among sites for any measured trait. There was strong coordination among traits, with a network analysis revealing two major groups of coordinated traits. In one group there were water potentials, turgor loss point, sapwood capacitance and density, HSMs, and mortality rate. In the second group there was leaf mass per area, leaf dry matter content, hydraulic architecture (leaf area to sapwood area ratio), and species-specific optimal moisture. Conclusion These results demonstrated that while species with greater safety from turgor loss had lower mortality rates, hydraulic architecture was the only trait that explained species’ moisture dependency. Species with a greater leaf area to sapwood area ratio were associated with drier sites and reduced their transpirational demand during the dry season via deciduousness.

Hydraulic Saftey Margins, drought, tropical forest↗
DOE OSTI2021

Investigation of species-mass diffusion in binary-species boundary layers at high pressure using direct numerical simulations

Here, direct numerical simulations of single-species and binary-species temporal boundary layers at high pressure are performed with special attention to species-mass diffusion. The working fluids are nitrogen or a mixture of nitrogen and methane. Mean profiles and turbulent fluctuations of mass fraction show that their qualitative characteristics are different from those of streamwise velocity and temperature, due to the different boundary conditions. In a wall-parallel plane near the wall, the streamwise velocity and temperature have streaky patterns and the fields are similar. However, the mass fraction field at the same location is different from the streamwise velocity and temperature fields indicating that species-mass diffusion is not similar to the momentum and thermal diffusion. In contrast, at the centre and near the edge of the boundary layer, the mass fraction and temperature fields have almost the same pattern, indicating that the similarity between thermal and species-mass diffusion holds away from the wall. The lack of similarity near the wall is traced to the Soret effect that induces a temperature-gradient-dependent species-mass flux. As a result, a new phenomenon has been identified for a non-isothermal binary-species system – uphill diffusion, which in its classical isothermal definition can only occur for three or more species. A quadrant analysis for the turbulent mass flux reveals that near the wall the Soret effect enhances the negative contributions of the quadrants. Due to the enhancement of the negative contributions, small species-concentration fluid tends to be trapped near the wall.

42 ENGINEERING↗
DOE OSTI2021

Constraints and variation in food web link-species space

Predicting food web structure in future climates is a pressing goal of ecology. These predictions may be impossible without a solid understanding of the factors that structure current food webs. Here, the most fundamental aspect of food web structure—the relationship between the number of links and species—is still poorly understood. Some species interactions may be physically or physiologically ‘forbidden'—like consumption by non-consumer species—with possible consequences for food web structure. We show that accounting for these ‘forbidden interactions' constrains the feasible link-species space, in tight agreement with empirical data. Rather than following one particular scaling relationship, food webs are distributed throughout this space according to shared biotic and abiotic features. Our study provides new insights into the long-standing question of which factors determine this fundamental aspect of food web structure.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

DNABERT-S: pioneering species differentiation with species-aware DNA embeddings

SUMMARY: We introduce DNABERT-S, a tailored genome model that develops species-aware embeddings to naturally cluster and segregate DNA sequences of different species in the embedding space. Differentiating species from genomic sequences (i.e. DNA and RNA) is vital yet challenging, since many real-world species remain uncharacterized, lacking known genomes for reference. Embedding-based methods are therefore used to differentiate species in an unsupervised manner. DNABERT-S builds upon a pre-trained genome foundation model named DNABERT-2. To encourage effective embeddings to error-prone long-read DNA sequences, we introduce Manifold Instance Mixup (MI-Mix), a contrastive objective that mixes the hidden representations of DNA sequences at randomly selected layers and trains the model to recognize and differentiate these mixed proportions at the output layer. We further enhance it with the proposed Curriculum Contrastive Learning (C2LR) strategy. Empirical results on 28 diverse datasets show DNABERT-S's effectiveness, especially in realistic label-scarce scenarios. For example, it identifies twice more species from a mixture of unlabeled genomic sequences, doubles the Adjusted Rand Index (ARI) in species clustering, and outperforms the top baseline's performance in 10-shot species classification with just a 2-shot training. AVAILABILITY AND IMPLEMENTATION: Model, codes, and data are publically available at https://github.com/MAGICS-LAB/DNABERT_S.

Zhou, Zhihan↗
NASA NTRS2007

Evaluation of Integrating the Invasive Species Forecasting System to Support National Park Service Decisions on Fire Management Activities and Invasive Plant Species Control

The USGS and NASA, in conjunction with Colorado State University, George Mason University and other partners, have developed the Invasive Species Forecasting System (ISFS), a flexible tool that capitalizes on NASA's remote sensing resource to produce dynamic habitat maps of invasive terrestrial plant species across the United States. In 2006 ISFS was adopted to generate predictive invasive habitat maps to benefit noxious plant and fire management teams in three major National Park systems: The Greater Yellowstone Area (Yellowstone / Grand Tetons National Parks), Sequoia and Kings Canyon National Park, and interior Alaskan (between Denali, Gates of The Arctic and Yukon-Charley). One of the objectives of this study is to explore how the ISFS enhances decision support apparatus in use by National Park management teams. The first step with each park system was to work closely with park managers to select top-priority invasive species. Specific species were chosen for each study area based on management priorities, availability of observational data, and their potential for invasion after fire disturbances. Once focal species were selected, sources of presence/absence data were collected from previous surveys for each species in and around the Parks. Using logistic regression to couple presence/absence points with environmental data layers, the first round of ISFS habitat suitability maps were generated for each National Park system and presented during park visits over the summer of 2006. This first engagement provided a demonstration of what the park service can expect from ISFS and initiated the ongoing dialog on how the parks can best utilized the system to enhance their decisions related to invasive species control. During the park visits it was discovered that separate "expert opinion" maps would provide a valuable baseline to compare against the ISFS model output. Opinion maps are a means of spatially representing qualitative knowledge into a quantitative two-dimensional map. Furthermore, our approach combines the qualitative expert opinion habitat maps -- with the quantitative ISFS habitat maps in a difference map that shows where the two maps agree and disagree. The objective of the difference map is to help focus future field sampling and improve model results. This paper presents a demonstration of the habitat, expert opinion, and difference map for Yellowstone National Park.

Ma, Peter↗
DOE OSTI2025

Species‐Specific Epigenetic Signature Associates With Heat Stress Tolerance in the Perennial Tree Species Populus

Epigenetic regulation in annual plants is recognized as a key component of recurring stress acclimation and adaptation, but reports on perennial tree species are limited. In this study, two contrasting tree species, Populus trichocarpa and Populus deltoides, and an F1 hybrid cross between them showed species-specific epigenetic and physiological responses to heat stress (42°C) following priming (35°C). By analyzing whole-genome methylation, transcriptomics, proteomics, metabolomics, and photosynthesis parameters, we found that P. deltoides expresses specific epigenetic signatures in response to heat, resulting in improved photosynthetic efficiency compared to P. trichocarpa. Conversely, P. trichocarpa displayed stress signaling and defense mechanisms that could not sustain a net assimilation rate despite maintaining higher gas exchange. Heat stress following priming in hybrid plants increased transcript levels of thermotolerance-related transcription factors, such as SPL12. Selected regions in the promoter of SPL12 showed differential methylation between direct heat stress and priming followed by heat stress. As a result, upregulation of downstream genes and associated increases in protein and metabolite abundance for stress adaptation were exhibited. Consequently, hybrid plants showed enhanced photosynthesis and gas exchange rates, a trait lacking in P. trichocarpa. These results imply that priming may not be universally effective in enhancing plant performance under stress, particularly in perennial tree species. However, priming can acclimate the perennial tree species P. deltoides to withstand elevated temperature stress better. Our study has demonstrated that priming-based stress adaptation is species-specific but can be attained through crossbreeding, indicating its potential use in breeding programs.

DNA methylation↗
DOE OSTI2021

Analysis of digitized herbarium records and community science observations provides a glimpse of downy mildew species diversity of North America, reveals potentially undescribed species, and documents the need for continued digitization and collecting

Downy mildew diseases caused by Peronosporaceae cause significant crop losses globally, with several emerging and resurgent threats in recent decades. Biodiversity data from digitized herbarium specimens provide an opportunity to develop a baseline census of species diversity, however, these resources may represent aggregations of nonrandom and opportunistic collecting efforts, which could lead to spurious results. Here, the MyCoPortal census of digitized herbarium records for downy mildew species collected from North America 1800 to present were analyzed. From 9838 unique records, 196 species were identified, reflecting ~28% of known species diversity. Temporal and geographic collecting biases were observed, with 90% of the collections made prior to 1960 and the efforts of six “super-collectors” accounting for 25% of the collections. The presence of 50–100 undescribed species in North America was inferred from the records. Together, these results highlight the need for continued downy mildew collections, taxonomic research and digitization efforts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Leafweb: Leaf Gas Exchange and Pulse-Amplitude Modulated Fluorometry for C4 Species, June 2026 Release

This dataset contains leaf gas exchange and Pulse-Amplitude Modulated (PAM) fluorometry for 98 C4 species. The C4 photosynthetic pathway employs specialized CO2 concentration mechanisms and Kranz anatomy to enrich CO2 concentration around Rubisco, the enzyme that catalyzes carbon fixation in the Calvin-Benson cycle to suppress photorespiration and increase the use efficiencies of light, nitrogen, and water as compared to the C3 photosynthetic pathways. Large-scale C4 photosynthetic datasets are relatively scarce, which has affected C4 photosynthesis research. To improve C4 photosynthetic data availability, Leafweb organized an effort to systematically collect, compile, standardize, and organize measurements of leaf gas exchange and/or Pulse-Amplitude Modulated (PAM) fluorometry of C4 species. This derived a C4 photosynthetic dataset containing measurements made by independent researchers in multiple countries in various environments (field, garden, or greenhouse). It covers three biochemical subtypes – the nicotinamide adenine dinucleotide phosphate-malic enzyme (NADP-ME), nicotinamide adenine dinucleotide-malic enzyme (NAD-ME), and phosphoenolpyruvate carboxykinase (PEP-CK) subtypes. This dataset is useful for using Artificial Intelligence / Machine Learning and mechanistic models to study C4 photosynthesis and compare across different biochemical subtypes. This dataset contains 3 compressed (*.zip) folders containing 1,892 data files in comma-separate values (*.csv) format. Additional metadata are provided: one data dictionary and a file-level metadata file in comma-separate values (*.csv) format and a user guide in PDF (*.pdf) format.

Zhou, Haoran [Tianjin University, China]↗
DOE OSTI2026

The Energy Costs of Dewatering Feedstock Microalgae Species Using Conventional Implementations of Ultrasonic and Crossflow Filtration Technologies

The use of microalgae as a feedstock for biofuels and other products continues to be explored, but large-scale biomass production faces persistent high costs. One major cost contributor is the energy required for harvesting and dewatering, a challenge resulting from the dilute nature of microalgae cultures as well as the properties of microalgae cells. This study investigated the energy demands of concentrating three diverse microalgae species (Nannochloropsis salina, Scenedesmus obliquus, and Chlorella luteoviridis) exhibiting different settling velocities, a key harvesting property, using conventional ultrasonic and crossflow membrane filtration. Membrane-free ultrasonic filtration removed 60-80% of the microalgae largely in steady-state operations, increasing concentrations 20-100 times, while consuming 1-6 kWh/m3 - similar to centrifugation. In contrast, crossflow membrane filtration retained nearly 100% of the microalgae, increasing concentrations over 20-fold, but consumed 158 kWh/m3 - over 10 times the energy of centrifugation. Both approaches exceeded the 10% energy target suggested in the 2010 National Algal Biofuel Technology Roadmap. This study also highlights potential sources of energy savings. For ultrasonic filtration, attention to an innovative, dynamic property of the ultrasonic chamber called the Energy Efficiency Factor, could lead to energy reductions by no more than 10-fold and improve the favorability of two of the microalgae species studied. For membrane filtration, a dead-end configuration could reduce energy consumption by no more than 1000-fold, making it favorable for all three species. This study not only highlights the need to further increase the energy content of microalgae cultures, but also the critical importance of continued development of ultrasonic filtration and other harvesting technologies to achieve low-cost, energy-sustainable algal biofuels.

09 BIOMASS FUELS↗
NASA NTRS2003

The Distribution and Abundance of Bird Species: Towards a Satellite, Data Driven Avian Energetics and Species Richness Model

This paper addresses the fundamental question of why birds occur where and when they do, i.e., what are the causative factors that determine the spatio-temporal distributions, abundance, or richness of bird species? In this paper we outline the first steps toward building a satellite, data-driven model of avian energetics and species richness based on individual bird physiology, morphology, and interaction with the spatio-temporal habitat. To evaluate our model, we will use the North American Breeding Bird Survey and Christmas Bird Count data for species richness, wintering and breeding range. Long term and current satellite data series include AVHRR, Landsat, and MODIS.

Smith, James A.↗
NASA NTRS2012

The Invasive Species Forecasting System (ISFS): An iRODS-Based, Cloud-Enabled Decision Support System for Invasive Species Habitat Suitability Modeling

The Invasive Species Forecasting System (ISFS) is an online decision support system that allows users to load point occurrence field sample data for a plant species of interest and quickly generate habitat suitability maps for geographic regions of interest, such as a national park, monument, forest, or refuge. Target customers for ISFS are natural resource managers and decision makers who have a need for scientifically valid, model- based predictions of the habitat suitability of plant species of management concern. In a joint project involving NASA and the Maryland Department of Natural Resources, ISFS has been used to model the potential distribution of Wavyleaf Basketgrass in Maryland's Chesapeake Bay Watershed. Maximum entropy techniques are used to generate predictive maps using predictor datasets derived from remotely sensed data and climate simulation outputs. The workflow to run a model is implemented in an iRODS microservice using a custom ISFS file driver that clips and re-projects data to geographic regions of interest, then shells out to perform MaxEnt processing on the input data. When the model completes, all output files and maps from the model run are registered in iRODS and made accessible to the user. The ISFS user interface is a web browser that uses the iRODS PHP client to interact with the ISFS/iRODS- server. ISFS is designed to reside in a VMware virtual machine running SLES 11 and iRODS 3.0. The ISFS virtual machine is hosted in a VMware vSphere private cloud infrastructure to deliver the online service.

Gill, Roger↗
DOE OSTI2021

Root anatomy helps to reconcile observed root trait syndromes in tropical tree species

Premise Studying the organization of functional traits in plant leaves and stems has revealed notable patterns linking function and form; however, evidence of similarly robust organization in root tissues remains controversial. We posit that anatomical traits in roots can provide insight on the overall organization of the root system. We hypothesized that size variation in the tissue outside the stele is related in a nonlinear fashion with functional traits associated with direct resource uptake, including a negative relationship with root architectural traits, and that similar relationships detected in tropical areas also hold true in other biomes. Methods We addressed our hypotheses using empirical data from 24 tropical tree species in French Guiana, including anatomical measurements in first order roots and functional trait description for the entire fine root system. In addition, we compiled a global meta‐analysis of root traits for 500+ forest species across tropical, subtropical, and temperate forests. Results Our results supported the expected nonlinear relationships between cortical size and morphological traits and a negative linear trend with architectural traits. We confirmed a global negative relationship among specific root length (SRL), diameter, and tissue density, suggesting similar anatomical constraints in root systems across woody plants. However, the importance of factors varies across biomes, possibly related to the unequal phylogenetic representation across latitudes. Conclusions Our findings imply that the rhizocentric hypothesis can be a valuable approach to understand fine root trait syndromes and the evolution of absorptive roots in vascular plants.

Valverde‐Barrantes, Oscar J.↗
DOE OSTI2023

Synthesis and Surface Attachment of Molecular Re(I) Hydride Species with Silatrane Functionalized Bipyridyl Ligands

Three molecular Re hydrides of the form ( R bpy)Re(CO) 3 H with 2,2′-bipyridine (bpy) ligands containing silatrane functional groups for surface attachment on metal oxide surfaces were synthesized. IR spectroscopy and cyclic voltammetry (CV) demonstrated that the complexes containing the silatrane functional groups have electronic properties similar to those of a control compound, which did not contain functional groups for attachment. Additionally, in a similar fashion to the control compound, the silatrane containing Re hydrides are electrocatalysts for the reduction of CO 2 to CO in solution. The silatrane containing complexes were immobilized on a thin layer of TiO 2 on Si, and the resulting composites were characterized using X-ray photoelectron and IR spectroscopy as well as cyclic voltammetry in the dark and under illumination. Control experiments indicated that the hydride complexes are not stable on the surface and degrade to species which contain a bpy ligand, three CO ligands, and an unknown ligand in the sixth site. Similarly, when one of the silatrane containing Re hydride complexes was immobilized on Si nanoparticles with a thin layer of SiO 2 or silica nanoparticles, the hydride ligand was lost. Density functional theory calculations were used to corroborate the observed behavior of hydride species on a surface. Altogether, this work demonstrates the difficulties associated with attaching well-defined molecular hydride complexes to metal oxide surfaces.

Anions↗
DOE OSTI2021

The controlling role of atmosphere in dawsonite versus gibbsite precipitation from tetrahedral aluminate species

In highly alkaline solution, aluminum speciates as the tetrahedrally coordinated aluminate monomer, Al(OH)4- and/or dimer Al2O(OH)62-, yet precipitates as octahedrally coordinated gibbsite (Al(OH)3). This tetrahedral to octahedral transformation governs Al precipitation, which is crucial to worldwide Al production, and to the processing of caustic high-level radioactive wastes. Despite its significance, the transformation pathway remains unknown. Here we explore the roles of atmospheric water and carbon dioxide in mediating the transformation of the tetrahedrally coordinated potassium aluminate dimer salt (K2Al2O(OH)6) to gibbsite versus potassium dawsonite (KAl(CO3)(OH)2). A combination of in-situ attenuated total reflection infrared spectroscopy, ex-situ micro X-ray diffraction, and multivariate curve resolution-alternating least squares chemometrics analysis reveals that humidity plays a key role in the transformation by limiting the amount of alkalinity neutralization by dissolved CO2. Lower humidity favors higher alkalinity and incorporation of carbonate species in the final Al product to form KAl(CO3)(OH)2. Higher humidity enables more acid generation that destabilizes dawsonite and favors gibbsite as the solubility limiting phase. Because the transformation was restricted to occur in thin water films, the results suggest that transition from tetra- to octahedrally coordinated Al does not have to occur in bulk solution, as has often been hypothesized, but may instead appear on the source mineral surface.

Dembowski, Mateusz↗