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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1996

Paleobiology, community ecology, and scales of ecological pattern

The fossil record provides a wealth of data on the role of regional processes and historical events in shaping biological communities over a variety of time scales. The Quaternary record with its evidence of repeated climatic change shows that both terrestrial and marine species shifted independently rather than as cohesive assemblages over scales of thousands of years. Larger scale patterns also show a strong individualistic component to taxon dynamics; assemblage stability, when it occurs, is difficult to separate from shared responses to low rates of environmental change. Nevertheless, the fossil record does suggest that some biotic interactions influence large-scale ecological and evolutionary patterns, albeit in more diffuse and protracted fashions than those generally studied by community ecologists. These include: (1) the resistance by incumbents to the establishment of new or invading taxa, with episodes of explosive diversification often appearing contingent on the removal of incumbents at extinction events; (2) steady states of within-habitat and global diversity at longer time scales (10(7)-l0(8) yr), despite enormous turnover of taxa; and (3) morphological and biogeographic responses to increased intensities of predation and substratum disturbance over similarly long time scales. The behavior of species and communities over the array of temporal and spatial scales in the fossil record takes on additional significance for framing conservation strategies, and for understanding recovery of species, lineages, and communities from environmental changes.

NASA Discipline Exobiology↗
NASA NTRS1998

A natural view of microbial biodiversity within hot spring cyanobacterial mat communities

This review summarizes a decade of research in which we have used molecular methods, in conjunction with more traditional approaches, to study hot spring cyanobacterial mats as models for understanding principles of microbial community ecology. Molecular methods reveal that the composition of these communities is grossly oversimplified by microscopic and cultivation methods. For example, none of 31 unique 16S rRNA sequences detected in the Octopus Spring mat, Yellowstone National Park, matches that of any prokaryote previously cultivated from geothermal systems; 11 are contributed by genetically diverse cyanobacteria, even though a single cyanobacterial species was suspected based on morphologic and culture analysis. By studying the basis for the incongruity between culture and molecular samplings of community composition, we are beginning to cultivate isolates whose 16S rRNA sequences are readily detected. By placing the genetic diversity detected in context with the well-defined natural environmental gradients typical of hot spring mat systems, the relationship between gene and species diversity is clarified and ecological patterns of species occurrence emerge. By combining these ecological patterns with the evolutionary patterns inherently revealed by phylogenetic analysis of gene sequence data, we find that it may be possible to understand microbial biodiversity within these systems by using principles similar to those developed by evolutionary ecologists to understand biodiversity of larger species. We hope that such an approach guides microbial ecologists to a more realistic and predictive understanding of microbial species occurrence and responsiveness in both natural and disturbed habitats.

Review↗
NASA NTRS2023

A Community Convention for Ecological Forecasting: Output Files and Metadata Version 1.0

This paper summarizes the open community conventions developed by the Ecological Forecasting Initiative (EFI) for the common formatting and archiving of ecological forecasts and the metadata associated with these forecasts. Such open standards are intended to promote interoperability and facilitate forecast communication, distribution, validation, and synthesis. For output files, we first describe the convention conceptually in terms of global attributes, forecast dimensions, forecasted variables, and ancillary indicator variables. We then illustrate the application of this convention to the two file formats that are currently preferred by the EFI, netCDF (network common data form), and comma-separated values (CSV), but note that the convention is extensible to future formats. For metadata, EFI's convention identifies a subset of conventional metadata variables that are required (e.g., temporal resolution and output variables) but focuses on developing a framework for storing information about forecast uncertainty propagation, data assimilation, and model complexity, which aims to facilitate cross-forecast synthesis. The initial application of this convention expands upon the Ecological Metadata Language (EML), a commonly used metadata standard in ecology. To facilitate community adoption, we also provide a Github repository containing a metadata validator tool and several vignettes in R and Python on how to both write and read in the EFI standard. Lastly, we provide guidance on forecast archiving, making an important distinction between short-term dissemination and long-term forecast archiving, while also touching on the archiving of code and workflows. Overall, the EFI convention is a living document that can continue to evolve over time through an open community process.

Michael C. Dietze↗
NASA NTRS1998

Thermal Infrared Remote Sensing for Analysis of Landscape Ecological Processes: Methods and Applications

Thermal Infrared (TIR) remote sensing data can provide important measurements of surface energy fluxes and temperatures, which are integral to understanding landscape processes and responses. One example of this is the successful application of TIR remote sensing data to estimate evapotranspiration and soil moisture, where results from a number of studies suggest that satellite-based measurements from TIR remote sensing data can lead to more accurate regional-scale estimates of daily evapotranspiration. With further refinement in analytical techniques and models, the use of TIR data from airborne and satellite sensors could be very useful for parameterizing surface moisture conditions and developing better simulations of landscape energy exchange over a variety of conditions and space and time scales. Thus, TIR remote sensing data can significantly contribute to the observation, measurement, and analysis of energy balance characteristics (i.e., the fluxes and redistribution of thermal energy within and across the land surface) as an implicit and important aspect of landscape dynamics and landscape functioning. The application of TIR remote sensing data in landscape ecological studies has been limited, however, for several fundamental reasons that relate primarily to the perceived difficulty in use and availability of these data by the landscape ecology community, and from the fragmentation of references on TIR remote sensing throughout the scientific literature. It is our purpose here to provide evidence from work that has employed TIR remote sensing for analysis of landscape characteristics to illustrate how these data can provide important data for the improved measurement of landscape energy response and energy flux relationships. We examine the direct or indirect use of TIR remote sensing data to analyze landscape biophysical characteristics, thereby offering some insight on how these data can be used more robustly to further the understanding and modeling of landscape ecological processes.

Quattrochi, Dale A.↗
NASA NTRS2021

TLSLEAF: Automatic Leaf Angle Estimates From Single-Scan Terrestrial Laser Scanning

Leaf angle distribution (LAD) in forest canopies affects estimates of leaf area, light interception, and global-scale photosynthesis, but is often simplified to a single theoretical value. Here, we present TLSLeAF (Terrestrial Laser Scanning Leaf Angle Function), an automated open-source method of deriving LADs from terrestrial laser scanning. TLSLeAF produces canopy-scale leaf angle and LADs by relying on gridded laser scanning data. The approach increases processing speed, improves angle estimates, and requires minimal user input. Key features are automation, leaf–wood classification, beta parameter output, and implementation in R to increase accessibility for the ecology community. TLSLeAF precisely estimates leaf angle with minimal distance effects on angular estimates while rapidly producing LADs on a consumer-grade machine. We challenge the popular spherical LAD assumption, showing sensitivity to ecosystem type in plant area index and foliage profile estimates that translate to c. 25% and c. 11% increases in canopy net photosynthesis (c. 25%) and solar-induced chlorophyll fluorescence (c. 11%). TLSLeAF can now be applied to the vast catalog of laser scanning data already available from ecosystems around the globe. The ease of use will enable widespread adoption of the method outside of remote-sensing experts, allowing greater accessibility for addressing ecological hypotheses and large-scale ecosystem modeling efforts.

3D↗
NASA NTRS2020

The Global Ecosystem Dynamics Investigation: High-Resolution Laser Ranging of the Earth’s Forests and Topography

Obtaining accurate and widespread measurements of the vertical structure of the Earth’s forests has been a longsought goal for the ecological community. Such observations are critical for accurately assessing the existing biomass of forests, and how changes in this biomass caused by human activities or variations in climate may impact atmospheric CO2 concentrations. Additionally, the three-dimensional structure of forests is a key component of habitat quality and biodiversity at local to regional scales. The Global Ecosystem Dynamics Investigation (GEDI) was launched to the International Space Station in late 2018 to provide high-quality measurements of forest vertical structure in temperate and tropical forests between 51.6 N & S latitude. The GEDI instrument is a geodetic-class laser altimeter/waveform lidar comprised of 3 lasers that produce 8 transects of structural information. Over its two-year nominal lifetime GEDI is anticipated to provide over 10 billion waveforms at a footprint resolution of 25 m. These data will be used to derive a variety of footprint and gridded products, including canopy height, canopy foliar profiles, Leaf Area Index (LAI), sub-canopy topography and biomass. Additionally, data from GEDI are used to demonstrate the efficacy of its measurements for prognostic ecosystem modeling, habit and biodiversity studies, and for fusion using radar and other remote sensing instruments. GEDI science and technology are unique: no other space-based mission has been created that is specifically optimized for retrieving vegetation vertical structure. As such, GEDI promises to advance our understanding of the importance of canopy vertical variations within an ecological paradigm based on structure, composition and function.

Dubayah, Ralph↗
NASA NTRS1973

Mapping coastal vegetation, land use and environmental impact from ERTS-1

The author has identified the following significant results. Digital analysis of ERTS-1 imagery was used in an attempt to map and inventory the significant ecological communities of Delaware's coastal zone. Eight vegetation and land use discrimination classes were selected: (1) Phragmites communis (giant reed grass); (2) Spartina alterniflora (salt marsh cord grass); (3) Spartina patens (salt marsh hay); (4) shallow water and exposed mud; (5) deep water (greater than 2 m); (6) forest; (7) agriculture; and (8) exposed sand and concrete. Canonical analysis showed the following classification accuracies: Spartina alterniflora, exposed sand, concrete, and forested land - 94% to 100%; shallow water - mud and deep water - 88% and 93% respectively; Phragmites communis 83%; Spartina patens - 52%. Classification accuracy for agriculture was very poor (51%). Limitations of time and available class-memory space resulted in limiting the analysis of agriculture to very gross identification of a class which actually consists of many varied signature classes. Abundant ground truth was available in the form of vegetation maps compiled from color and color infrared photographs. It is believed that with further refinement of training set selection, sufficiently accurate results can be obtained for all categories.

Klemas, V.↗
NASA NTRS1974

Inventories of Delaware's coastal vegetation and land-use utilizing digital processing of ERTS-1 imagery

Digital analysis of ERTS-1 imagery was used in an attempt to map and inventory the significant ecological communities of Delaware's coastal zone. Eight vegetation and land use discrimination classes were selected: (1) phragmites communis (Giant Reed grass); (2) spartina alterniflora (Salt marsh cord grass); (3) spartina patens (Salt marsh hay); (4) shallow water and exposed mud; (5) deep water (2 meters); (6) forest; (7) agriculture; and (8) exposed sand and concrete. Canonical analysis showed that classification accuracy was quite good with spartina alterniflora, exposed sand-concrete, and forested land - all discriminated with between 94% and 100% accuracy. The shallow water-mud and deep water categories were classified with accuracies of 88% and 93% respectively. Phragmites communis showed a classification accuracy of 83% with all confusion occurring with spartina patens which may be due to use of mixed stands of these species as training sets. Discrimination of spartina patens was very poor (accuracy 52%).

Klemas, V.↗
NASA NTRS1987

Symbiont acquisition as neoseme: origin of species and higher taxa

We examine the hypothesis that, in the origin of species and higher taxa of eukaryotes, symbiont acquisition followed by partner integration has been equivalent to neoseme appearance leading to speciation. The formation of stable symbiotic associations involves partner-surface recognition, behavioral and metabolic interaction, and, in some cases, gene product (RNA, protein) and genic (RNA, DNA) integration. This analysis is applied here to examples of neosemes that define specific taxa and to neosemes in plants, fungi, and animals that involve the appearance of new types of tissue. If this hypothesis is correct--if the origin of major genetic variation leading to speciation and even higher taxa may occur through symbiont acquisition and integration--then the analysis of "origins of species and higher taxa" becomes analogous to the study of microbial community ecology.

NASA Discipline Exobiology↗
NASA NTRS2017

Ecological Study of Lagoons Surrounding the John F. Kennedy Space Center, Brevard County, Florida : Theses and Project Reports - Volume 2

Many of the detailed studies done in connection with Ecological Study of the Lagoons surrounding the John F. Kennedy Space Port were performed as Master's Thesis investigations by various graduate students enrolled at F. I. T. during and subsequent to the report. The scope and purpose of what we came to call "the KSC Baseline Study" caught the imagination and interest of our student body. Many who were not financially or otherwise connected with the project found their inspiration in studies that were directly connected with project, and thus added materially to the totality of the knowledge gained. An example of one such study is the first article included in this Volume, A Master's Thesis study performed by Shen Phillip Chen, who chose the site for his investigation so that his results would correlate with and extend the results of others. In addition to the Master's Theses contained in this Volume, six other graduate studies must be acknowledged here as contributing to this Report, although they have not reached the stage of final publication. Ms. Sandra Fettes has completed a study of the amounts of five trace metals in mangrove leaves from plants at various locations around the Kennedy Space Center. Mr. Bernard Cohenour has isolated and identified a number of oil consuming bacteria endemic in the waters of the Indian Rivers. Mr. Charles Waterhouse has analyzed historic data of tidal gauges in the lagoonal area and correlated it with wind field records. Mr. Renkert Meyer has measured the vertical and horizontal currents of the lagoons and is attempting an interpretation of them in terms of the wind field as a driving force. Mr. Richard Campbell has measured the rate of nitrogen fixation in both the water columns and the sediments under them in the lagoons. Mr. Craig Weiderhold has measured thl3 annual variations in the populations of benthic invertebrates in the lagoons. An integral part of the F. I. T. curriculum is a requirement that each undergraduate student perform an independent study during his Senior year and submit his results in the form and format of a professional scientific report. While none of these senior Project Reports have been included in this Volume because of space limitations, many of them aided significantly in the overall study. Typical of these were: light and dark bottle studies of the blue-green algae respiration; writing and executing computer studies comparing the water chemistry data from various sites; detection and identification of nitrogen fixation bacteria in the Indian River; measurement of dissolved oils and greases in the river, photographically recording the benthic life-forms found in the river bottom; measuring the vertical structure of drift and slope currents in too lagoons; and measurement of water level variations along the long axis of a lagoon as a function of wind stress. These articles are published as a part of this Final Report in an effort to make available for the record as much of the basic data as possible. The few articles published on the Indian River have in general not contained much detailed data, so that comparisons of current status to conditions of the past are difficult or impossible. A major effort of both the Oceanographic and Ecological communities for the past decade has been the retrieval and storage of basic data in order to permit determinations of trends or changes in baseline conditions. It is believed that the information compiled here will be of great value in any future investigations.

Source record↗
NASA NTRS2019

Effects of Topography on Tropical Forest Structure Depend on Climate Context

Topography affects abiotic conditions which can influence the structure, function, and dynamics of ecological communities. An increasing number of studies have demonstrated biological consequences of fine-scale topographic heterogeneity but we have a limited understanding of how We merged high-resolution (1 sq. meter) data on topography and canopy height derived from airborne lidar with ground-based data from 15 forest plots in Puerto Rico distributed along a precipitation gradient spanning ca. 800 to 3,500 mm yr(exp -1). Ground-based data included species composition, estimated above-ground biomass (AGB), and two key functional traits (wood density and leaf mass per area, LMA) that reflect resource-use strategies and a trade-off between hydraulic safety and hydraulic efficiency. We used hierarchical Bayesian models to evaluate how the interaction between topography climate is related to metrics of forest structure (i.e., canopy height and AGB), as well as taxonomic and functional alpha- and beta-diversity. Fine-scale topography (characterized with the topographic wetness index, TWI) significantly affected forest structure and the strength (and in some cases direction) of these effects varied across the precipitation gradient. In all plots, canopy height increased with topographic wetness but the effect was much stronger in dry compared to wet forest plots. In dry forest plots, topographically wetter microsites also had higher levels of AGB but in wet forest plots, topographically drier microsites had higher AGB. Fine-scale topography influenced functional composition but had only weak or non-significant effects on taxonomic and functional alpha- and beta-diversity. For instance, community-weighted wood density followed a similar pattern to AGB across plots. We also found a marginally significant association between variation of wood density and topographic heterogeneity that depended on climate context. Synthesis: The effects of fine-scale topographic heterogeneity on tropical forest structure and composition depend on the climate context. Our study demonstrates how a stronger integration of topographic heterogeneity across precipitation gradients could improve estimates of forest structure and biomass, and may provide insight to the ways that topography might mediate species responses to drought and climate change.

Tropical dry forest↗
NASA NTRS2023

Viral Enumeration Using Cost-Effective Wet-Mount Epifluorescence Microscopy for Aquatic Ecosystems and Modern Microbialites

Enumeration is a fundamental measure of community ecology in which viruses represent the most numerous biological identities. Epifluorescence microscopy (EFM) has been the gold standard method for environmental viral enumeration for over 25 years. Currently, standard EFM methods using the Anodisc filters are no longer cost-effective (>$15 per slide) and have yet to be applied to modern microbialites. Microbialites are microbially driven benthic organosedimentary deposits that have been present for most of Earth’s history. We present a cost-effective method for environ mental viral enumeration from aquatic samples, microbial mats, and exopolymeric substances (EPSs) within modern microbialites using EFM. Our integrated approach, which includes filtration, differential centrifugation, chloroform treatment, glutaralde hyde fixation, benzonase nuclease treatment, probe sonication (EPS and mat only), SYBR Gold staining, wet mounting, and imaging, provides a robust method for modern microbialites and aquatic samples. Viral abundances of modern microbialites and aquatic samples collected from Fayetteville Green Lake (FGL) and Great Salt Lake (GSL) did not differ across ecosystems by sample type. EPS and microbial mat samples had an order of magnitude higher viral-like particle abundance when compared to water regardless of the ecosystem (107 vs 106). Viral enumeration allows for estimates of total viral numbers and weights. The entire weight of all the viruses in FGL and GSL are ~598 g and ~2.2 kg, respectively. Further development of EFM methods and software is needed for viral enumeration. Our method provides a robust and cost-effective (~$0.75 per sample) viral enumeration within modern microbialites and aquatic ecosystems.

Madeline Bellanger↗
NASA NTRS2020

Beyond Ecosystem Modeling: A Roadmap to Community Cyberinfrastructure for Ecological Data-Model Integration

In an era of rapid global change, our ability to understand and predict Earth's natural systems is lagging behind our ability to monitor and measure changes in the biosphere. Bottlenecks to informing models with observations have reduced our capacity to fully exploit the growing volume and variety of available data. Here, we take a critical look at the information infrastructure that connects ecosystem modeling and measurement efforts, and propose a roadmap to community cyberinfrastructure development that can reduce the divisions between empirical research and modeling and accelerate the pace of discovery. A new era of data‐model integration requires investment in accessible, scalable, and transparent tools that integrate the expertise of the whole community, including both modelers and empiricists. This roadmap focuses on five key opportunities for community tools: the underlying foundations of community cyberinfrastructure; data ingest; calibration of models to data; model‐data benchmarking; and data assimilation and ecological forecasting. This community‐driven approach is a key to meeting the pressing needs of science and society in the 21st century.

Istem Fer↗
NASA NTRS2024

Effects of Water Limitation and Competition on Tree Carbon Allocation in an Earth System Modeling Framework

Earth system models (ESMs) have a limited capacity to represent plant functional diversity and shifts in trait distributions. Approaches to improving the representation of this complexity in ESMs include (i) optimality-based approaches that predict trait–environment responses and (ii) explicitly modelling coexistence and community assembly. These approaches are expected to converge only when optimality-based approaches identify competitively dominant strategies, which often differ from strategies that maximize ecosystem functioning or fitness components in monoculture. We used two models, LM3-PPA (a vegetation demographic model designed as an ESM component) and BiomeE (a computationally efficient analog for LM3-PPA), to explore how water limitation affects carbon allocation strategies of canopy trees. We compared competitive allocation strategies and those that maximize biomass or productivity in monoculture. We did not explicitly model coexistence or community assembly. Rather, we used model experiments to identify competitive and maximizing strategies in a two-dimensional trait space under different precipitation and mortality scenarios. At 10 eastern US locations, we simulated historical, wet and dry climate scenarios, novel drought and three different mortality scenarios (low, medium or high sensitivity to water deficit). For each site and scenario, we identified the competitive strategy and three maximizing strategies (maximum biomass, productivity or drought-tolerance). Root: leaf ratios tended to increase and leaf area tended to decrease with increasing water stress (increasing water limitation and its effects on mortality). However, relative to maximizing strategies, competitive strategies shifted towards greater allocation to roots and leaves with increasing water stress. Competitive overinvestments (greater allocation to roots and leaves by competitive strategies compared with maximizing strategies) were robust across different modelling contexts, including vegetation parameter sets (Acer vs. Populus), models (LM3-PPA vs. BiomeE) and uncalibrated vs. calibrated BiomeE versions. Synthesis: The theoretical prediction that competitive and maximizing allocation strategies differ under water limitation is confirmed for a demographic model designed as an ESM component. Optimality-based trait predictions can simplify representing trait diversity in ESMs but do not always correspond to competitive outcomes. Explicitly modelling coexistence and community assembly in ESMs is challenging but is likely the most general approach to representing trait diversity.

vegetation demographic model↗
NASA NTRS2022

Un-Numbered Operational Areas PRL 229 Railroad Tie Disposal Area Pond Confirmation Sampling Report

This Confirmatory Sampling (CS) Report (CSR) was prepared for the National Aeronautics and Space Administration (NASA), Kennedy Space Center (KSC), Florida in accordance with the CS Work Plan (CSWP) (HGL, 2022a). The CSR summarizes investigation activities performed on the Railroad Tie Disposal Area (RTDA) of the Un-Numbered Operational Areas (UNOA), Potential Release Location (PRL) 229 located at KSC. HydroGeoLogic, Inc. (HGL) prepared this report under Contract Number 80KSC019D0012. The purpose of the CSR is to provide information to evaluate the level of potential contamination in surface water and sediment samples collected from the RTDA PRL 229 Pond and determine if contaminants pose unacceptable risks to ecological receptors. The CSR provides analytical data of 10 sets of surface water and sediment samples collected in 2021. Surface water samples were analyzed for volatile organic compounds (VOCs), semi-volatile organic compounds (SVOCs), polynuclear aromatic hydrocarbon (PAHs), metals, hardness, and salinity, while sediment samples were analyzed for metals, total organic carbon (TOC), SVOCs, PAHs, and total petroleum hydrocarbons (TPH). The CSR includes a Screening Level Ecological Risk Assessment (SLERA) conducted under KSC’s Resource Conservation and Recovery Act (RCRA) Corrective Action Program to determine if unacceptable risks to ecological receptors exist at PRL 229 Pond. Metals and PAHs were detected in surface water samples, including detections of antimony, arsenic, barium, calcium, copper, lead, magnesium, thallium, zinc, anthracene, benzo(a)anthracene, benzo(a)pyrene, benzo(b)fluoranthene, benzo(g,h,i)perylene, benzo(k)fluoranthene, chrysene, dibenzo(a,h)anthracene, fluoranthene, indeno(1,2,3-c,d)pyrene and pyrene. Based on measured salinity (1.03 to 1.21 parts per thousand), the pond was identified as freshwater. Sediment analytical results also contained detections of metals and PAHs, including antimony, arsenic, barium, beryllium, cadmium, chromium, copper, lead, mercury, nickel, selenium, thallium, zinc, anthracene benzo(a)anthracene, benzo(a)pyrene, benzo(b)fluoranthene, benzo(g,h,i)perylene, benzo(k)fluoranthene, chrysene, dibenzo(a,h)anthracene, fluoranthene, indeno(1,2,3-c,d)pyrene and pyrene. Potential risks to ecological receptors were evaluated in accordance with the SLERA Work Plan and the Decision Process Document for the Resource Conservation and Recovery Act (RCRA) Corrective Action Program at KSC (DPD) (Geosyntec, 2019), and using the 2021 sediment and surface water analytical results. Potential ecological receptors evaluated in the SLERA include the aquatic community, benthic invertebrates, aquatic birds, and aquatic mammals. The SLERA included Steps 2a through 2c of the Ecological Risk Assessment (ERA) process in accordance with the DPD. Using multiple lines of evidence, the SLERA concluded that many of the detected analytes are present at concentrations similar to those in background or reference locations at KSC, and/or at concentrations that would not pose a significant risk to ecological communities. There are no screening values available for the avian community, and PAHs are bioaccumulative compounds. For this reason, food web modeling was completed as a supplement to Step 2c to provide a quantitative evaluation of this exposure pathway. Food web modeling indicates that PAHs are unlikely to pose a risk to birds exposed to site sediment and surface water. Based on the results of the SLERA, the contaminants in sediment and surface water pose no to minimal risk to the ecological communities that could live or forage at the site. Based on the results of the SLERA, no further study is recommended for the RTDA Pond at PRL 229.

Confirmation Sampling↗