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NASA NTRS2015

Is There Ecological Information in Optical Polarization Data?

Optical linear polarization? In remote sensing it's due to specular reflection. The first surface that incident light encounters - a smooth water surface or the waxy first surface of a leaf's cuticle, if it's even somewhat smooth (i.e. shiny) - will specularly reflect and linearly polarize the incident light. We provide three examples of the types of ecological information contained in remotely sensed optical linear polarization measurements. Remove the surface reflection to better see the interior. The linearly polarized light reflected by leaf surfaces contains no information about cellular pigments, metabolites, or water contained in the leaf interiors of a plant canopy, because it never enters the leaf interior to interact with them. Thus, for purposes of remotely sensing the leaf interiors of a plant canopy, the linearly polarized light should be subtracted from the total reflected light, because including it would add noise to the measurement. In particular 'minus specular' vegetation indices should allow improved monitoring of a plant canopy's physiological processes. Estimate plant development stage and yield. Wheat and sorghum grain heads, following emergence, rapidly extend upward and very quickly tower over nearby leaves, partially blocking our view of the sunlight reflected by those leaf surfaces. The resulting decrease in the amount of surface reflected and polarized sunlight, if monitored over time, potentially allows per-field estimates of the dates of the heading and flowering development stages to be interleaved with weather data in models, which is key to better estimating per-field grain yield. Similar polarization changes may occur in other grasses, such as oats, barley, corn and rice, each a crop so widely grown that it potentially affects climate at the regional scale. Wetlands Mapping. The sunlight specularly reflected by surface waters is blindingly bright, spectrally flat and polarized - all of which telegraphs that the ground area is inundated. Inundated soils exchange methane with the atmosphere; non-inundated soils, carbon dioxide. Aquatic plants growing through the water surface pipe the soil-produced methane via the stomata to the atmosphere, enhancing exchanges rates by factors of 10-20 compared to ebullition (bubbling) or diffusion through the water column to the atmosphere. Thus, mapping wetland areas into three community types - inundated areas with emergent vegetation, open water and uplands - provides potentially key information to water, carbon and energy budgets at landscape to global scales.

Water↗

NASA NTRS2016

Beyond 3-D: The New Spectrum of Lidar Applications for Earth and Ecological Sciences

Capturing and quantifying the world in three dimensions (x,y,z) using light detection and ranging (lidar) technology drives fundamental advances in the Earth and Ecological Sciences (EES). However, additional lidar dimensions offer the possibility to transcend basic 3-D mapping capabilities, including i) the physical time (t) dimension from repeat lidar acquisition and ii) laser return intensity (LRIλ) data dimension based on the brightness of single- or multi-wavelength (λ) laser returns. The additional dimensions thus add to the x,y, and z dimensions to constitute the five dimensions of lidar (x,y,z, t, LRIλ1... λn). This broader spectrum of lidar dimensionality has already revealed new insights across multiple EES topics, and will enable a wide range of new research and applications. Here, we review recent advances based on repeat lidar collections and analysis of LRI data to highlight novel applications of lidar remote sensing beyond 3-D. Our review outlines the potential and current challenges of time and LRI information from lidar sensors to expand the scope of research applications and insights across the full range of EES applications.

Eitel, Jan U. H.↗

NASA NTRS2016

Everglades Ecological Forecasting II: Utilizing NASA Earth Observations to Enhance the Capabilities of Everglades National Park to Monitor & Predict Mangrove Extent to Aid Current Restoration Efforts

Mangroves act as a transition zone between fresh and salt water habitats by filtering and indicating salinity levels along the coast of the Florida Everglades. However, dredging and canals built in the early 1900s depleted the Everglades of much of its freshwater resources. In an attempt to assist in maintaining the health of threatened habitats, efforts have been made within Everglades National Park to rebalance the ecosystem and adhere to sustainably managing mangrove forests. The Everglades Ecological Forecasting II team utilized Google Earth Engine API and satellite imagery from Landsat 5, 7, and 8 to continuously create land-change maps over a 25 year period, and to allow park officials to continue producing maps in the future. In order to make the process replicable for project partners at Everglades National Park, the team was able to conduct a supervised classification approach to display mangrove regions in 1995, 2000, 2005, 2010 and 2015. As freshwater was depleted, mangroves encroached further inland and freshwater marshes declined. The current extent map, along with transition maps helped create forecasting models that show mangrove encroachment further inland in the year 2030 as well. This project highlights the changes to the Everglade habitats in relation to a changing climate and hydrological changes throughout the park.

Kirk, Donnie↗

NASA NTRS2017

A Probabilistic Method of Assessing Carbon Accumulation Rate at Imnavait Creek Peatland, Arctic Long Term Ecological Research Station, Alaska

Arctic peatlands are an important part of the global carbon cycle, accumulating atmospheric carbon as organic matter since the Late glacial. Current methods for understanding the changing efficiency of the peatland carbon sink rely on peatlands with an undisturbed stratigraphy. Here we present a method of estimating primary carbon accumulation rate from a site where permafrost processes have either vertically or horizontally translocated nearby carbon-rich sediment out of stratigraphic order. Briefly, our new algorithm estimates the probability of the age of deposition of a random increment of sediment in the core. The method assumes that if sediment age is measured at even depth increments, dates are more likely to occur during intervals of higher accumulation rate and vice versa. Multiplying estimated sedimentation rate by measured carbon density yields carbon accumulation rate. We perform this analysis at the Imnavait Creek Peatland, near the Arctic Long Term Ecological Research network site at Toolik Lake, Alaska. Using classical radiocarbon age modeling, we find unreasonably high rates of carbon accumulation at various Holocene intervals. With our new method, we find accumulation rate changes that are in improved agreement within the context of other sites throughout Alaska and the rest of the Circum-Arctic region.

carbon accumulation;Imnavait;peatlands;permafrost;↗

NASA NTRS2016

Permanent Draft Genome of Strain ESFC-1: Ecological Genomics of a Newly Discovered Lineage of Filamentous Diazotrophic Cyanobacteria

The nonheterocystous filamentous cyanobacterium, strain ESFC-1, is a recently described member of the order Oscillatoriales within the Cyanobacteria. ESFC-1 has been shown to be a major diazotroph in the intertidal microbial mat system at Elkhorn Slough, CA, USA. Based on phylogenetic analyses of the 16S RNA gene, ESFC-1 appears to belong to a unique, genus-level divergence; the draft genome sequence of this strain has now been determined. Here we report features of this genome as they relate to the ecological functions and capabilities of strain ESFC-1. The 5,632,035 bp genome sequence encodes 4914 protein-coding genes and 92 RNA genes. One striking feature of this cyanobacterium is the apparent lack of either uptake or bi-directional hydrogenases typically expected within a diazotroph. Additionally, a large genomic island is found that contains numerous low GC-content genes and genes related to extracellular polysaccharide production and cell wall synthesis and maintenance.

R Craig Everroad↗

NASA NTRS2018

Biology IS the Technology: the Microbial Ecology of Space Food Production and the Power of Aquaponics as a Learning Tool

To accomplish the objective of human missions to Mars and/or the long-term colonization of the moon, bioregenerative life support systems and food production systems will be absolutely necessary. Microbes are an essential and unavoidable component of these systems. In fact, these systems are driven by complex microbial communities about which we know very little, a glaring strategic knowledge gap in our ability to support extended human exploration in closed systems. Our laboratory has been working to use molecular ecological methods, including nanopore sequencing technology already deployed on the International Space Station, to understand the microbes in food production systems on Earth. Our ultimate goal is to inform the implementation of food production systems off-world. To date, we have sampled and sequenced the microbiomes of aquaponics systems, hydroponics systems, and fish ponds. Our results have revealed that the microbial communities in these systems are extremely diverse, and highly variable between systems. Along the way, we have discovered the power of aquaponics systems as teaching tools, and the capacity of students to perform high quality citizen science. By designing, constructing, and operating aquaponics systems, students better understand the role of microbes in the cycling of the elements in natural ecosystems, and in the human built environment. In partnership with schools and colleges, contributing new knowledge as citizen scientists, we are now exploring the relationships between the functioning of these systems and their microbial flora.

Bebout, Brad↗

NASA NTRSDate not supplied

Identifying Optimal Site Location for Wind Energy Farms Considering Ecological and Social Impacts

With the increasing cost and declining availability of fossil fuels, renewable energy, specifically wind power, has become one of the fastest growing sources of energy in New Mexico. To assist with the goals set by the state’s Renewables Standard Portfolio established in 2004, the NASA DEVELOP team created three Optimal Wind Farm Suitability maps that consider social impact, ecological impact, and power production efficiency. The team utilized datasets from February 2013 – May 2018 that show vulnerable species, average wind patterns, and US Air Force Base locations. These three maps were combined into a final suitability map for optimal wind farm placement.

Joy Marich↗

NASA NTRS2020

Fisher's Peak Ecological Forecasting - Mapping Biomass to Inform Conservation Planning of a Future State Park in Southern Colorado

Fisher’s Peak is a 77.5 km2 property southeast of Trinidad, Colorado that is planned to become Colorado’s newest state park. The area has experienced limited anthropogenic disturbance and is home to an abundance of unique habitats and species. A rapid, approximately 900 m change in elevation over the extent of the area nurtures a variety of plants and animals, including the endangered New Mexico meadow jumping mouse. In 2019, the State of Colorado obtained Fisher’s Peak with plans to make it Colorado’s second largest state park. A diverse group of collaborators, including the Colorado State Forest Service and The Nature Conservancy, worked closely to design the state park to maximize recreation opportunity while conserving the property’s rich habitats and biodiversity. The Fisher’s Peak Ecological Forecasting Team utilized Light Detection and Ranging (LiDAR) surveys, in situ forest inventory data, and Earth observations from Landsat 8 Operational Land Imager (OLI), Sentinel-1 C-band Synthetic Aperture Radar (C-SAR), Sentinel-2 Multispectral Instrument (MSI), Advanced Land Observing Satellite 2 (ALOS-2) Phased Array type L-band Synthetic Aperture Radar (PALSAR-2) and the Shuttle Radar Topography Mission (SRTM) to quantify and map biomass over the extent of the study area. The results from modeling biomass had an out-of-bag root mean square error of 55 Mg/ha and an R2 of 12. The resulting map indicates areas where carbon storage on the property is high, informing decision-making processes for future park development. While more in situ training data may improve modeling capacity for biomass in the Fisher’s Peak area, this work represents a feasible attempt to better understand biomass distribution using earth observation

Lauren Lad↗

NASA NTRS2020

Southern Bhutan Ecological Forecasting Tech Paper: Modeling Asian Elephant (Elephas maximus) Habitat Suitability along the Southern Bhutan Border with NASA Earth Observations

Asian elephants (Elephas maximus) are a flagship species essential for the functioning of forest ecosystems, and they also have cultural significance in Bhutan. Elephants receive the highest legal protection as listed under Schedule I of the Bhutan Forests and Nature Conservation Act, 1995. Yet, they face threats of extinction due to poaching for ivory as well as the loss and fragmentation of their habitat. Due to the recent clearing of forests and the growing populations in these areas, there has been an increase in incidents of human-elephant conflict. These conflicts have been detrimental to farmer’s annual harvests and livelihoods and have led to retaliatory killing and injury of elephants in southern Bhutan. The DEVELOP Southern Bhutan Ecological Forecasting team partnered with the Bhutan Foundation and Bhutan Tiger Center to help address this problem. The team integrated NASA Earth observations, including Landsat 5 Thematic Mapper (TM), Landsat 8 Operational Land Imager (OLI), Terra Moderate Resolution Imaging Spectroradiometer (MODIS), and the Shuttle Radar Topography Mission (SRTM) to acquire information on land cover change and elephant habitat suitability along the southern border of Bhutan. The team utilized Esri ArcGIS Pro and Software for Assisted Habitat Modeling (SAHM) for data analysis, modeling, and visualization. The team used elephant occurrence data and environmental variables to model current habitat suitability for migrating elephant populations. This analysis provided partners with maps to inform decisions about the placement and conservation of elephant corridors and helped build their capacity to use satellite data for future studies and project planning.

Palchen Wangchuk↗

NASA NTRS2020

Southern Bhutan Ecological Forecasting Project Summary - Modeling Asian Elephant (Elephas Maximus) Habitat Suitability along the Southern Bhutan Border with NASA Earth Observations

DEVELOP Project Summary↗

NASA NTRS2020

Fisher's Peak Ecological Forecasting: Mapping Biomass to Inform Conservation Planning of a Future State Park in Southern Colorado

Fisher’s Peak is a 77.5 km2 property southeast of Trinidad, Colorado that is planned to become Colorado’s newest state park. The area has experienced limited anthropogenic disturbance and is home to an abundance of unique habitats and species. A rapid, approximately 900 m change in elevation over the extent of the area nurtures a variety of plants and animals, including the endangered New Mexico meadow jumping mouse. In 2019, the State of Colorado obtained Fisher’s Peak with plans to make it Colorado’s second largest state park. A diverse group of collaborators, including the Colorado State Forest Service and The Nature Conservancy, worked closely to design the state park to maximize recreation opportunity while conserving the property’s rich habitats and biodiversity. The Fisher’s Peak Ecological Forecasting Team utilized Light Detection and Ranging (LiDAR) surveys, in situ forest inventory data, and Earth observations from Landsat8 Operational Land Imager (OLI), Sentinel-1 C-band Synthetic Aperture Radar (C-SAR), Sentinel-2 Multispectral Instrument (MSI), Advanced Land Observing Satellite 2 (ALOS-2) Phased Array type L-band Synthetic Aperture Radar (PALSAR-2) and the Shuttle Radar Topography Mission (SRTM) to quantify and map biomass over the extent of the study area. The results from modeling biomass had an out-of-bag root mean square error of 55 Mg/ha and an R2 of 12. The resulting map indicates areas where carbon storage on the property is high, informing decision-making processes for future park development. While more in situ training data may improve modeling capacity for biomass in the Fisher’s Peak area, this work represents a feasible attempt to better understand biomass distribution using earth observation.

DEVELOP Tech Paper↗

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 NTRS2020

Spatial validation reveals poor predictive performance of large-scale ecological mapping models

Mapping aboveground forest biomass is central for assessing the global carbon balance. However, current large-scale maps show strong disparities, despite good validation statistics of their underlying models. Here, we attribute this contradiction to a flaw in the validation methods, which ignore spatial autocorrelation (SAC) in data, leading to overoptimistic assessment of model predictive power. To illustrate this issue, we reproduce the approach of large-scale mapping studies using a massive forest inventory dataset of 11.8 million trees in central Africa to train and validate a random forest model based on multispectral and environmental variables. A standard nonspatial validation method suggests that the model predicts more than half of the forest biomass variation, while spatial validation methods accounting for SAC reveal quasi-null predictive power. This study underscores how a common practice in big data mapping studies shows an apparent high predictive power, even when predictors have poor relationships with the ecological variable of interest, thus possibly leading to erroneous maps and interpretations.

biomass↗

NASA NTRS2022

Western Montana Ecological Forecasting II: Enhancing Habitat Suitability Modeling of Mustelid Species and Contaminant Monitoring in Northern Montana Using NASA Earth Observations

Environmental contaminants in aquatic ecosystems threaten both human and ecosystem health. Western Montana’s rivers possess great economic and ecological value, yet the status of contaminants in these systems can be unclear. Contaminants such as brominated flame-retardants, heavy metals, and pharmaceuticals negatively affect ecosystem health by traveling through the food chain and bioaccumulating in apex predators. Exposure to these contaminants can result in neurological, endocrine, and reproductive impairments in wildlife and humans. American mink (Neovison vison) and North American river otter (Lontra canadensis) have a predominantly aquatic diet and serve as reliable indicator species of environmental health. Working Dogs for Conservation (WD4C) uses detection dogs to locate scat samples of these species which are assessed for contaminants by the Virginia Institute of Marine Science (VIMS). With Software for Assisted Habitat Modeling (SAHM), the team generated current (2013-2020) and projected (2021-2040) habitat suitability models for mink and otter utilizing NASA Earth observations from Terra Moderate Resolution Imaging Spectroradiometer (MODIS), Global Precipitation Measurement Integrated Multi-Satellite Retrievals for GPM (GPM IMERG), Shuttle Radar Topography Mission (SRTM), and Soil Moisture Active Passive (SMAP). The habitat suitability maps’ study region encompassed Flathead National Forest and Blackfeet Indian Reservation. Additionally, the team created site accessibility and precipitation anomaly maps that display the viability of survey locations. The current habitat suitability models performed well (AUC-PR=0.88). The most important predictor variables for suitable habitat were distance to rivers, elevation, and land cover. These end products will further inform WD4C survey site selection and contaminant monitoring.

Chelsea Morton↗

NASA NTRS2021

The sensitivity of runoff generation to spatial snowpack uniformity in an alpine watershed: Green Lakes Valley, Niwot Ridge Long-Term Ecological Research station

Seasonal water storage in high-elevation alpine catchments are critical sources of water for mountainous regions like the western U.S. The spatial distribution of snow in these topographically complex catchments is primarily governed by orography, solar radiation, and wind redistribution. While the effect of solar shading is relatively consistent from year-to-year, the redistribution of snow due to wind is more variable–capable of producing snowpacks that have varying degrees of uniformity across these hydrologically-important catchments. A reasonable hypothesis is that a warmer climate will cause snowfall to become more dense (i.e. wetter and heavier), possibly leading to less wind redistribution and thus produce a more uniformly distributed snowpack across the landscape. In this study, we investigate the role of increasingly uniform spatial snowpack distributions on streamflow generation in the Green Lakes Valley Niwot Ridge Long Term Ecological Research station, within the headwaters of the Boulder Creek watershed in Colorado. A set of idealized hydrologic simulation experiments driven by reconstructed snowpacks spanning 2001–2014 show that more a more uniform spatial snowpack distribution leads to an earlier melt-out of31 days on average and tends to produce less total streamflow, with maximum decreases as large as 7.5%. Isolating the role of snowpack heterogeneity from melt-season precipitation, we find that snowpack uniformity reduces total streamflow by as much as 13.2%. Reductions in streamflow are largely explained by greater expo-sure to solar radiation in the uniformly distributed case relative to a more heterogeneous snowpack, with this exposure driving shifts towards earlier snowmelt and changes in soil water storage. Overall, we find that the runoff efficiency from shallower snowpacks is more sensitive to the effects of uniformity than deeper snowpacks, which has potential implications for a warming climate where shallower snowpacks and enhanced sensitivities may be present.

Alpine catchment↗

NASA NTRS2021

Southern Bhutan Ecological Forecasting III: Utilizing NASA Earth Observations to Model Land Cover Change and Elephant Wildlife Corridors in Southern Bhutan

Habitat loss of the endangered Asian elephants (Elephas maximus) accompanied by rapid urbanization has contributed to the rising human-elephant conflict (HEC) crisis in southern Bhutan. This poses a serious threat to the survival of Asian elephants, a keystone wildlife species essential for maintaining Bhutan’s forest ecosystems and rich biodiversity. With expanding urban areas, HECs present challenges to conservation efforts in the region. The team partnered with the Bhutan Foundation, the Bhutan Tiger Center, and Bhutan Ecological Society to help mitigate this issue using remote sensing technology and NASA Earth observations. The team refined Land Use and Land Cover (LULC) maps for 2010–2019 generated in previous terms and elephant corridor maps to include information on human settlements using Landsat 5 Thematic Mapper (TM) and Landsat 8 Operational Land Imager (OLI) data. We generated LULC change maps and forecasted the LULC to 2030 using TerrSet Land Change Modeler, providing insights into future elephant habitat suitability in southern Bhutan. The results indicated that built-up areas increased approximately 688.9% from 2010 to 2019 and the forecasted 2030 LULC also predicted an increase in built-up areas compared to 2019. Suitable corridors in Gelephu intersect cultivated and built-up areas, indicating close proximity of elephants to humans and a need to research alternative corridor strategies. The end products from this project will aid partner organizations in decision-making processes in urban planning and future conservation strategies that include the refined placement of biological corridors to aid elephant movement and reduce the risk of HECs.

Thinley Yidzin Wangden↗

NASA NTRS2022

Maine Ecological Forecasting II: Identifying Forest Cover and Assessing Federally Endangered Atlantic Salmon Habitat in Maine Using Earth Observations

Major declines in Atlantic salmon (Salmo salar) populations have occurred alongside dam construction, shifting temperatures, and changing land use and land cover (LULC), restricting the last remaining wild population in the United States to Maine. In collaboration with the Maine Department of Marine Resources and the Downeast Salmon Federation, the NASA DEVELOP team utilized Earth observations to assess changes within critical salmon habitat. The team used the Landsat 5 Thematic Mapper (TM), Landsat 8 Operation Land Imager (OLI), Sentinel-2 MultiSpectral Instrument (MSI), and National Land Cover Database (NLCD) to refine historical LULC maps from 1985 to 2021. The team also used elevation data from the Shuttle Radar Topography Mission (SRTM) and IDRISI TerrSet Land Change Modeler to forecast LULC change to 2040. From Terra Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) data, the team derived a time series, summer averages, and anomaly maps between 2000 and 2021. The team analyzed LST in relation to LULC classes, specifically forest cover type, and in-situ stream temperature from the Spatial Hydro-Ecological Decision System (EcoSHEDS). LULC trends from 1985 to 2021 revealed a net transition of coniferous forest to other classes, such as deciduous forest and developed land. The team found an association between warmer temperatures and a greater presence of developed and mixed forest classes per 10,000 acres across Maine. These visualizations and analyses will aid partners in identifying riparian locations with ideal or unfavorable habitat conditions to inform Atlantic salmon population recovery efforts.

Tony Bowman↗

NASA NTRS2022

Grand Valley Ecological Forecasting : Assessing Trends in Pinyon-Juniper Habitat Relative to Drought, Beetle Infestation, Wildland Fires, and Treatment to Plan Future Management Strategies

Drought, beetle infestation, and more frequent wildfires are changing the composition and distribution of the pinyon-juniper woodland and sagebrush ecosystems of the Grand Valley in western Colorado. Land managers must consider short- and long-term goals for restoration as well as budgetary and personnel limitations after such disturbances. Satellite remote sensing can provide long-term and continuous vegetation monitoring to assess where restoration is needed most and where treatment practices are most likely to succeed. Harnessing Earth observation data, our team set out to observe trends in disturbances and the distribution of pinyon-juniper woodlands and sagebrush communities of National Park Service (NPS) and Bureau of Land Management (BLM) lands within the Grand Valley. We used imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Aqua and Terra satellites, and Landsat sensors to map landcover change within these ecosystems from 1984-2021. Additionally, we analyzed disturbed areas and treatment sites to understand their effect on long-term vegetation health and recovery. Results showed that pinyon-juniper woodland has expanded in extent more than other landcover types, indicating woody encroachment into sagebrush ecosystems. We also found that wildfire disturbances had lasting impacts up to 20 years post-disturbance. Pre-fire treatment practices showed mixed results regarding their effectiveness at stopping fires and promoting post-fire recovery. These results will provide context to public land managers in the Grand Valley when developing management plans, ecological monitoring locations, and implementing treatment practices for future disturbances.

Garrett Powers↗