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NASA NTRS2021

Mapping the Extent of Mangrove Ecosystem Degradation by Integrating an Ecological Conceptual Model with Satellite Data

Anthropogenic and natural disturbances can cause degradation of ecosystems, reducing their capacity to sustain biodiversity and provide ecosystem services. Understanding the extent of ecosystem degradation is critical for estimating risks to ecosystems, yet there are few existing methods to map degradation at the ecosystem scale and none using freely available satellite data for mangrove ecosystems. In this study, we developed a quantitative classification model of mangrove ecosystem degradation using freely available earth observation data. Crucially, a conceptual model of mangrove ecosystem degradation was established to identify suitable remote sensing variables that support the quantitative classification model, bridging the gap between satellite-derived variables and ecosystem degradation with explicit ecological links. We applied our degradation model to two case-studies, the mangroves of Rakhine State, Myanmar, which are severely threatened by anthropogenic disturbances, and Shark River within the Everglades National Park, USA, which is periodically disturbed by severe tropical storms. Our model suggested that 40% (597 km2) of the extent of mangroves in Rakhine showed evidence of degradation. In the Everglades, the model suggested that the extent of degraded mangrove forest increased from 5.1% to 97.4% following the Category 4 Hurricane Irma in 2017. Quantitative accuracy assessments indicated the model achieved overall accuracies of 77.6% and 79.1% for the Rakhine and the Everglades, respectively. We highlight that using an ecological conceptual model as the basis for building quantitative classification models to estimate the extent of ecosystem degradation ensures the ecological relevance of the classification models. Our developed method enables researchers to move beyond only mapping ecosystem distribution to condition and degradation as well. These results can help support ecosystem risk assessments, natural capital accounting, and restoration planning and provide quantitative estimates of ecosystem degradation for new global biodiversity targets.

Calvin K. F. Lee↗

NASA NTRS2019

Pixel-Based Model For High Latitude Dust Detection

Dust has implications on the energy budget, ocean biodiversity, and economy at regional and global scales. Dust detection relies on spectral sensitivity at visible (RGB) and infrared wavelengths. Radiative properties of high latitude dust and the background surface albedo in these regions (>40°N, >40°S) complicate current dust detection methods. Leveraging supervised machine learning (ML) methods, we propose a new method accounting for regional differences of dust occurrence.

High latitude dust↗

NASA NTRS2008

Space-Based Ornithology - Studying Bird Migration and Environmental Change in North America

Natural fluctuations in the availability of critical stopover sites coupled with anthropogenic destruction of wetlands, land-use change, and anticipated losses due to climate change present migratory birds with a formidable challenge. Space based technology in concert with bird migration modeling and geographical information analysis yields new opportunities to shed light on the distribution and movement of organisms on the planet and their sensitivity to human disturbances and environmental changes. At the NASA Goddard Space Flight Center, we are creating ecological forecasting tools for science and application users to address the consequences of loss of wetlands, flooding, drought or other natural disasters such as hurricanes on avian biodiversity and bird migration. We use an individual-based bird biophysical migration model, driven by remotely sensed land surface data, climate and hydrologic data, and biological field observations to study migratory bird responses to environmental change in North America. Simulation allows us to study bird migration across multiple scales and can be linked to mechanistic processes describing the time and energy budget states of migrating birds. We illustrate our approach by simulating the spring migration of pectoral sandpipers from the Gulf of Mexico to Alaska. Mean stopover length and trajectory patterns are consistent with field observations.

Smith, James A.↗

NASA NTRS2018

SERVIR: Connecting Space to Village

From space, we can view our planet in new ways. SERVIR empowers people in developing countries to use that view for gaining knowledge and insights about their environments and adaptation to a changing climate. We work with regional decision-makers to foster use of Earth observation satellite data, GIS, and predictive models for addressing water and land use, natural disasters, agricultural problems, biodiversity, and more. These tools can improve the lives, livelihoods, safety, and future of people in communities around the world.

Limaye, Ashutosh S.↗

NASA NTRS2018

SERVIR Connecting Space to Village

Puzzi Nicolau, Andrea↗

NASA NTRSDate not supplied

Exploring the Integration of Earth Observations to Support Community Management of a Protected Area in Guatemala

Central America faces increasing challenges of deforestation and habitat fragmentation with complex drivers. Protected areas are one response to these challenges, forming a continuous forest stand subject to national conservation systems and laws. As part of a novel shared-management model, both the community of Santa María Tzejá and the Protected Areas Council of Guatemala (CONAP in Spanish) co-manage Cerro Cantil, a protected area in the Ixcán department of northwestern Guatemala covering approximately 314 ha. The SERVIR program, a joint initiative between NASA and USAID, in partnership with leaders from Santa María Tzejá, began a pilot project to explore how the integration of satellite remote sensing can support forest and biodiversity monitoring and contribute to the community’s reporting requirements. To assess Cerro Cantil’s potential role to protect endemic species between three larger protected areas, we model least cost corridors between Cerro Cantil and Laguna Lachuá, Visi Cabá, and Montes Azules for Alouatta pigra (Black Howler Monkey). Additionally, we evaluate the potential contribution of a forestry-conservation incentives program (PROBOSQUE) to stem fragmentation and support biodiversity by assessing the forest area overlapping both the modeled corridors and plots belonging to families enrolled in PROBOSQUE. Results contribute to community understanding of the value of Cerro Cantil to protect local biodiversity as well as the interaction of a forestry incentive program and protected area designation.

Biodiversity↗

NASA NTRS2021

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

The diverse landscapes of Bhutan host a rich biodiversity of animal and plant species. Asian elephants (Elephas maximus) are a flagship keystone wildlife species whose conservation is essential for the functioning of Bhutan’s forest ecosystems. Despite this, increasing habitat loss and human-elephant conflict continue to be detrimental to the survival of Asian elephants. The lack of information on Bhutan’s elephants and land use and land cover (LULC) trends present major challenges for Bhutan in modeling locations with suitable habitat and biological corridors for elephants. The DEVELOP Southern Bhutan Ecological Forecasting II team at NASA Goddard Space Flight Center partnered with the Bhutan Foundation, Bhutan Tiger Center, and Bhutan Ecological Society to help address this problem. The team mapped LULC in Bhutan for 2010 and 2015 by utilizing NASA Earth observations, including Landsat 5 Thematic Mapper (TM) and Landsat 8 Operational Land Imager (OLI) to acquire information on historical LULC patterns and view apparent land cover change. The team used the Linkage Pathways Tool of the Linkage Mapper Toolbox in ArcMap to derive biological corridor maps from habitat suitability model outputs of the previous term and known locations of protected areas in Bhutan. The corridor maps were used to view and assess corridor suitability and connectivity between protected parks. Project results are being provided to partners to help make informed decisions on the placement and conservation of elephant movement corridors.

Thinley Yidzin Wangden↗

NASA NTRS2006

Space-Based Ornithology: On the Wings of Migration and Biophysics

Understanding bird migration and avian biodiversity is one of the most compelling and challenging problems of modern biology with major implications for human health and conservation biology. Migration and conservation efforts cross national boundaries and are subject to numerous international agreements and treaties. Public interest is high with concerns about avian flu, Katrina and its impacts, and the recent sightings of the ivory-billed woodpecker. Space based technology gives us new opportunities to shed light on the distribution and movement of organisms on the planet and their sensitivity to human disturbances and environmental changes. Together with the USGS and other agencies, we are creating ecological forecasting tools for science and application users to address the consequences of loss of wetlands, flooding, drought or other natural disasters such as hurricanes on avian biodiversity and bird migration. In our work, we use individual organism biophysical models of energy and water balance and drive these models with satellite measurements of spatio-temporal gradients in climate and habitat. Dynamic state variable modeling provides an additional tool for studying bird migration across multiple scales and can be linked to our mechanistic models describing the time and energy budget states of migrating birds. Such models yield an understanding of how a migratory flyway and its component habitats function as a whole and link stop-over ecology with biological conservation and management. We also build upon the canopy done by the Environmental Laboratory over the past few years.

Smith, James A.↗

NASA NTRS2014

SERVIR Presentation for the Hyperwall at the ESRI International Users Conference

From space, we can view our planet in new ways. As a joint initiative of NASA and USAID working in partnership with leading regional organizations, SERVIR connects space to village by helping people in developing countries use that view to gain knowledge and insights about their environments. We teach regional decision-makers to use Earth observation satellite data, Geographic Information Systems, and predictive models for addressing issues such as water and land use, natural disasters, agricultural problems, biodiversity conservation, and more to improve the lives, livelihoods, safety, and future of the people in their countries.

Irwin, Dan↗

NASA NTRSDate not supplied

NASA’s Prototype Spectral Water Inversion Processor and Emulator (SWIPE): Towards Global Coastal and Inland Water Quality and Algal Biodiversity Monitoring

Degradation of Earth’s inland water resources due to anthropogenic perturbations and climate anomalies at both local and global scales continues to place human health at substantial risk. There is now a growing necessity to develop pragmatic approaches that allow timely and effective extrapolation of local processes, to spatially resolved global products, and to promote operational and sustainable resource policy management. This presentation will provide updates on NASA’s prototype open-source aquatic modeling platform, Spectral Water Inversion Processor and Emulator (SWIPE), which is a comprehensive, multi-faceted modeling platform for both forward and inverse modeling of diverse aquatic ecosystems from the benthos to top-of-atmosphere (TOA). SWIPE provides a cohesive application which leverages recent advancements in particle modeling, Big Data analytics, and machine learning to develop a high-fidelity synthetic training ground for sensitivity studies and algorithm development for multispectral or upcoming hyperspectral missions. Some of the prominent features of SWIPE to be discussed include: 1. Advanced hyperspectral modeling of globally diverse algal and non-algal particles using a novel two-layer coated sphere scattering model and radiative transfer modeling, 2. Massive, highly detailed synthetic spectral libraries of Analysis-Ready-Data (ARD) which include spectral libraries of particle microphysics, water biogeophysical and optical properties, as well as surface and TOA reflectances at 1 nm resolution, 3. An ensemble of pre-built analytic, machine learning, and deep learning inversion algorithms for various water quality and biodiversity related retrieval parameters and uncertainty quantification, 4. Sensor-agnostic water quality inversion at wide ranging spatial and spectral resolutions including a codebase for seamless application in the Google Earth Engine and NASA Earth Exchange (NEX) for planetary scale analysis. SWIPE will be a fully open-source platform based in python with comprehensive documentation, tutorials, and options for distributed computing on high performance computing clusters or on single, local machines. Further, we will discuss how we envision SWIPE contributing towards a global analysis of coastal and inland water quality dynamics.

top-of-atmosphere (TOA)↗

NASA NTRS2018

Simulating Forest Dynamics of Lowland Rainforests in Eastern Madagascar

Ecological modeling and forecasting are essential tools for the understanding of complex vegetation dynamics. The parametric demands of some of these models are often lacking or scant for threatened ecosystems, particularly in diverse tropical ecosystems. One such ecosystem and also one of the world's biodiversity hotspots, Madagascar's lowland rainforests, have disappeared at an alarming rate. The processes that drive tree species growth and distribution remain as poorly understood as the species themselves. We investigated the application of the process-based individual-based FORMIND model to successfully simulate a Madagascar lowland rainforest using previously collected multi-year forest inventory plot data. We inspected the model's ability to characterize growth and species abundance distributions over the study site, and then validated the model with an independently collected forest-inventory dataset from another lowland rainforest in eastern Madagascar. Following a comparative analysis using inventory data from the two study sites, we found that FORMIND accurately captures the structure and biomass of the study forest, with r(squared) values of 0.976, 0.895, and 0.995 for 1:1 lines comparing observed and simulated values across all plant functional types for aboveground biomass (tonnes/ha), stem numbers, and basal area (m(squared)/ha), respectively. Further, in validation with a second study forest site, FORMIND also compared well, only slightly over-estimating shade-intermediate species as compared to the study site, and slightly under-representing shade-tolerant species in percentage of total aboveground biomass. As an important application of the FORMIND model, we measured the net ecosystem exchange (NEE, in tons of carbon per hectare per year) for 50 ha of simulated forest over a 1000-year run from bare ground. We found that NEE values ranged between 1 and -1 t Cha(exp -1)year(exp -1), consequently the study forest can be considered as a net neutral or a very slight carbon sink ecosystem, after the initial 130 years of growth. Our study found that FORMIND represents a valuable tool toward simulating forest dynamics in the immensely diverse Madagascar rainforests.

Forest Productivity↗

NASA NTRS2013

Algorithm Development for Predicting Biodiversity Based on Phytoplankton Absorption

Ocean color remote sensing has provided the scientific community with unprecedented global coverage of chlorophyll a, an indicator of phytoplankton biomass. Together, satellite-derived chlorophyll a and knowledge of Phytoplankton Functional Types (PFTs) will improve our limited understanding of marine ecosystem responses to physiochemical climate drivers involved in carbon cycle dynamics and linkages. Using cruise data from the Gulf of Maine and the Middle Atlantic Bight (N 269 pairs of HPLC and phytoplankton absorption samples), two modeling approaches were utilized to predict phytoplankton absorption and pigments. Algorithm I predicts the chlorophyll-specific absorption coefficient (a*(sub ph) (m(exp 2) mg chl a(exp - 1)) using inputs of temperature, light, and chlorophyll a. Modeled r(exp 2) values (400700 nm) ranged from 0.79 to 0.99 when compared to in situ observations with approximately 25 percent lower r(exp 2) values in the UV region. Algorithm II-a utilizes matrix inversion analysis to predict a(sub ph)(m(exp -1), 400700 nm) and r(exp 2) values ranged from 0.89 to 0.99. The prediction of phytoplankton pigments with Algorithm II-b produced r(exp 2) values that ranged from 0.40 to 0.93. When used in combination, Algorithm I, and Algorithm II-a are able to use satellite products of SST, PAR, and chlorophyll a (Algorithm I) to predict pigment concentrations and ratios to describe the phytoplankton community. The results of this study demonstrate that the spatial variation in modeled pigment ratios differ significantly from the 10-year SeaWiFS average chlorophyll a data set. Contiguous observations of chlorophyll a and phytoplankton biodiversity will elucidate ecosystem responses with unprecedented complexity.

phytoplankton↗

NASA NTRS2004

Microbial astronauts: assembling microbial communities for advanced life support systems

Extension of human habitation into space requires that humans carry with them many of the microorganisms with which they coexist on Earth. The ubiquity of microorganisms in close association with all living things and biogeochemical processes on Earth predicates that they must also play a critical role in maintaining the viability of human life in space. Even though bacterial populations exist as locally adapted ecotypes, the abundance of individuals in microbial species is so large that dispersal is unlikely to be limited by geographical barriers on Earth (i.e., for most environments "everything is everywhere" given enough time). This will not be true for microbial communities in space where local species richness will be relatively low because of sterilization protocols prior to launch and physical barriers between Earth and spacecraft after launch. Although community diversity will be sufficient to sustain ecosystem function at the onset, richness and evenness may decline over time such that biological systems either lose functional potential (e.g., bioreactors may fail to reduce BOD or nitrogen load) or become susceptible to invasion by human-associated microorganisms (pathogens) over time. Research at the John F. Kennedy Space Center has evaluated fundamental properties of microbial diversity and community assembly in prototype bioregenerative systems for NASA Advanced Life Support. Successional trends related to increased niche specialization, including an apparent increase in the proportion of nonculturable types of organisms, have been consistently observed. In addition, the stability of the microbial communities, as defined by their resistance to invasion by human-associated microorganisms, has been correlated to their diversity. Overall, these results reflect the significant challenges ahead for the assembly of stable, functional communities using gnotobiotic approaches, and the need to better define the basic biological principles that define ecosystem processes in the space environment. Copyright 2004 Springer-Verlag.

Review↗

NASA NTRS2016

Climate Change Adaptation Activities at the NASA John F. Kennedy Space Center, FL., USA

In 2010, the Office of Strategic Infrastructure and Earth Sciences established the Climate Adaptation Science Investigators (CASI) program to integrate climate change forecasts and knowledge into sustainable management of infrastructure and operations needed for the NASA mission. NASA operates 10 field centers valued at $32 billion dollars, occupies 191,000 acres and employs 58,000 people. CASI climate change and sea-level rise forecasts focus on the 2050 and 2080 time periods. At the 140,000 acre Kennedy Space Center (KSC) data are used to simulate impacts on infrastructure, operations, and unique natural resources. KSC launch and processing facilities represent a valued national asset located in an area with high biodiversity including 33 species of special management concern. Numerical and advanced Bayesian and Monte Carlo statistical modeling is being conducted using LiDAR digital elevation models coupled with relevant GIS layers to assess potential future conditions. Results are provided to the Environmental Management Branch, Master Planning, Construction of Facilities, Engineering Construction Innovation Committee and our regional partners to support Spaceport development, management, and adaptation planning and design. Potential impacts to natural resources include conversion of 50% of the Center to open water, elevation of the surficial aquifer, alterations of rainfall and evapotranspiration patterns, conversion of salt marsh to mangrove forest, reductions in distribution and extent of upland habitats, overwash of the barrier island dune system, increases in heat stress days, and releases of chemicals from legacy contamination sites. CASI has proven successful in bringing climate change planning to KSC including recognition of the need to increase resiliency and development of a green managed shoreline retreat approach to maintain coastal ecosystem services while maximizing life expectancy of Center launch and payload processing resources.

plant communities↗

NASA NTRS1992

Effects of habitat map generalization in biodiversity assessment

Species richness is being mapped as part of an inventory of biological diversity in California (i.e., gap analysis). Species distributions are modeled with a GIS on the basis of maps of each species' preferred habitats. Species richness is then tallied in equal-area sampling units. A GIS sensitivity analysis examined the effects of the level of generalization of the habitat map on the predicted distribution of species richness in the southern Sierra Nevada. As the habitat map was generalized, the number of habitat types mapped within grid cells tended to decrease with a corresponding decline in numbers of species predicted. Further, the ranking of grid cells in order of predicted numbers of species changed dramatically between levels of generalization. Areas predicted to be of greatest conservation value on the basis of species richness may therefore be sensitive to GIS data resolution.

Stoms, David M.↗

NASA NTRS2019

Pixel Based Model for High Latitude Dust Detection

High Latitude Dust (HLD, ≥ 50°𝑁 𝑎𝑛𝑑 ≥ 40°𝑆 ) load has implications on the energy budget, ocean biodiversity and economy on a regional and global scale. Current methods of dust detection rely on spectral sensitivity at visible (RGB) and infrared wavelengths. The characteristics of HLD vary according to the sediments and sedimentary processes operating on the land surface that are the source of the dust particles. Leveraging machine learning (ML) methods, we propose a new detection method based on convolutional neural network (CNN) using true color images.

Priftis, Georgios↗

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 NTRS2026

Adaptation and Response in Drylands (ARID): A Dryland Research Agenda and Campaign Strategy

Dryland ecosystems cover 41% of Earth’s land surfaces, account for 44% of cultivated lands and 60% of food sources, and make large contributions to the global water and carbon cycles. However, these ecosystems are experiencing unprecedented extremes including heatwaves, floods, and droughts as well as hotter temperatures and often declining water resource availability. These ecosystems are some of the most challenging to monitor given their high temporal variability with rapid response to their environment as well as vast spatial variability with intermixing of different plant species and life forms amongst bare soil coverage. The Adaptation and Response in Drylands (ARID) campaign was selected by National Aeronautics and Space Administration (NASA) as a scoping study to develop a research agenda for a dryland field campaign. Here, we detail our ARID science research agenda and implementation plan that were developed based on an extensive community engagement effort in over 160 events with over a thousand scientists, land managers, and Tribal communities between 2023 and 2024. The selected science themes cover drought and climate variability, ecosystem structure, function, and biodiversity, carbon cycle interannual variability and trends, and social ecological systems (land management and adaptation). We then detail our remote sensing, modeling, and field-based strategies to capture high temporal and high spatial resolution processes. Finally, our implementation strategy is presented which includes focus area selections in a core intensive western U.S. domain and distributed international domains. This strategy includes our overarching guiding principles of using multi-temporal airborne acquisitions and super sites as well as enhancing land management in co-development with end-user partners. While originally developed for NASA, our ARID report creates a blueprint for any future dryland field campaign, at any scale, that can be implemented widely for foundational and applied science objectives.

drylands↗