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NASA NTRS2011

From Parasite Encounter to Infection: Multiple-Scale Drivers of Parasite Richness in a Wild Social Primate Population

Host parasite diversity plays a fundamental role in ecological and evolutionary processes, yet the factors that drive it are still poorly understood. A variety of processes, operating across a range of spatial scales, are likely to influence both the probability of parasite encounter and subsequent infection. Here, we explored eight possible determinants of parasite richness, comprising rainfall and temperature at the population level, ranging behavior and home range productivity at the group level, and age, sex, body condition, and social rank at the individual level. We used a unique dataset describing gastrointestinal parasites in a terrestrial subtropical vertebrate (chacma baboons, Papio ursinus), comprising 662 faecal samples from 86 individuals representing all age-sex classes across two groups over two dry seasons in a desert population. Three mixed models were used to identify the most important factor at each of the three spatial scales (population, group, individual); these were then standardised and combined in a single, global, mixed model. Individual age had the strongest influence on parasite richness, in a convex relationship. Parasite richness was also higher in females and animals in poor condition, albeit at a lower order of magnitude than age. Finally, with a further halving of effect size, parasite richness was positively correlated to day range and temperature. These findings indicate that a range of factors influence host parasite richness through both encounter and infection probabilities, but that individual-level processes may be more important than those at the group or population level.

Benavides J. A.↗

NASA NTRS2012

Data Assimilation of Photosynthetic Light-use Efficiency using Multi-angular Satellite Data: II Model Implementation and Validation

Spatially explicit and temporally continuous estimates of photosynthesis will be of great importance for increasing our understanding of and ultimately closing the terrestrial carbon cycle. Current capabilities to model photosynthesis, however, are limited by accurate enough representations of the complexity of the underlying biochemical processes and the numerous environmental constraints imposed upon plant primary production. A potentially powerful alternative to model photosynthesis through these indirect observations is the use of multi-angular satellite data to infer light-use efficiency (ε) directly from spectral reflectance properties in connection with canopy shadow fractions. Hall et al. (this issue) introduced a new approach for predicting gross ecosystem production that would allow the use of such observations in a data assimilation mode to obtain spatially explicit variations in ε from infrequent polar-orbiting satellite observations, while meteorological data are used to account for the more dynamic responses of ε to variations in environmental conditions caused by changes in weather and illumination. In this second part of the study we implement and validate the approach of Hall et al. (this issue) across an ecologically diverse array of eight flux-tower sites in North America using data acquired from the Compact High Resolution Imaging Spectroradiometer (CHRIS) and eddy-flux observations. Our results show significantly enhanced estimates of ε and therefore cumulative gross ecosystem production (GEP) over the course of one year at all examined sites. We also demonstrate that ε is greatly heterogeneous even across small study areas. Data assimilation and direct inference of GEP from space using a new, proposed sensor could therefore be a significant step towards closing the terrestrial carbon cycle.

Hilker, Thomas↗

NASA NTRS2013

Classification of Dust Days by Satellite Remotely Sensed Aerosol Products

Considerable progress in satellite remote sensing (SRS) of dust particles has been seen in the last decade. From an environmental health perspective, such an event detection, after linking it to ground particulate matter (PM) concentrations, can proxy acute exposure to respirable particles of certain properties (i.e. size, composition, and toxicity). Being affected considerably by atmospheric dust, previous studies in the Eastern Mediterranean, and in Israel in particular, have focused on mechanistic and synoptic prediction, classification, and characterization of dust events. In particular, a scheme for identifying dust days (DD) in Israel based on ground PM10 (particulate matter of size smaller than 10 nm) measurements has been suggested, which has been validated by compositional analysis. This scheme requires information regarding ground PM10 levels, which is naturally limited in places with sparse ground-monitoring coverage. In such cases, SRS may be an efficient and cost-effective alternative to ground measurements. This work demonstrates a new model for identifying DD and non-DD (NDD) over Israel based on an integration of aerosol products from different satellite platforms (Moderate Resolution Imaging Spectroradiometer (MODIS) and Ozone Monitoring Instrument (OMI)). Analysis of ground-monitoring data from 2007 to 2008 in southern Israel revealed 67 DD, with more than 88 percent occurring during winter and spring. A Classification and Regression Tree (CART) model that was applied to a database containing ground monitoring (the dependent variable) and SRS aerosol product (the independent variables) records revealed an optimal set of binary variables for the identification of DD. These variables are combinations of the following primary variables: the calendar month, ground-level relative humidity (RH), the aerosol optical depth (AOD) from MODIS, and the aerosol absorbing index (AAI) from OMI. A logistic regression that uses these variables, coded as binary variables, demonstrated 93.2 percent correct classifications of DD and NDD. Evaluation of the combined CART-logistic regression scheme in an adjacent geographical region (Gush Dan) demonstrated good results. Using SRS aerosol products for DD and NDD, identification may enable us to distinguish between health, ecological, and environmental effects that result from exposure to these distinct particle populations.

satellite remote sensing↗

NASA NTRSDate not supplied

A Lunar Ground Truth of Microbes that are Integral to Sustaining Biological Life Support Systems

A lunar outpost such as Gateway or a Mars transit vehicle will use a semi-closed to closed loop biological life support system (BLSS) adapted for microgravity and high levels of radiation. A moon habitat will likely exist under partial gravity conditions and sustained levels of high radiation as a semi-closed loop system able to get resources from Earth via Gateway. Additionally, the moon will act as a closed-loop testbed for Mars habitat operations and will employ various elements of in situ resource utilization (ISRU). Perhaps the longest running BLSS collective study to date is that of the European MELiSSA (Micro Ecological Life Support System Alternative) project, a circular life support system, established to gain knowledge on regenerative systems aimed at the highest degree of autonomy to produce food, water and oxygen from mission wastes. This setup has evaluated the use of discrete microbial compartments and a higher plant compartment to carry out the necessary life support functions to support crew. Such compartments utilize thermophilic anaerobes to break down human and inedible plant wastes, photoheterotrophic bacteria that can further metabolize volatile fatty acids, nitrifying bacteria that can convert ammonium to plant and microalgae available nitrates, and photoautotrophic bacteria and higher plants which will convert carbon dioxide to oxygen, purify water, and provide food for human consumption. This being the most advanced BLSS model example to date -aside from the Yuegong-1, Chinese Lunar Palace- with the most defined compartment composition, and the assumption that other BLSSs will build upon such models, it becomes relevant to study the effects of the lunar environment upon the microbes that are integral to a BLSS. In ramping up to advanced stage BLSS systems, relatively simple experiments can be conducted on Artemis missions using continuous culturing and sampling of the model microbes, subsequently subjected to DNA sequencing for mutational analysis monitoring and chemical analysis to assess the sustained ability to carry out their hallmark biochemical processes efficiently. A suite of microbes should be assessed, prioritizing those with the duel capacity to be utilized in an BLSS and the ability to biochemically facilitate ISRU goals, such as the ability to transform the biogeochemistry of Moon or Martian regolith into materials that can support crop growth or extract elements of industrial significance such as aluminum or iron.

Biological Life Support Systems↗

NASA NTRS2014

Myanmar Ecological Forecasting: Utilizing NASA Earth Observations to Monitor, Map, and Analyze Mangrove Forests in Myanmar for Enhanced Conservation

Mangroves supply many essential environmental amenities, such as preventing soil erosion, filtering water pollution, and protecting shorelines from harmful waves, floods, storms and winds. The Mangroves in Myanmar not only provide citizens with a food source, but they also offer firewood, charcoal, and construction materials. The depletion of mangroves is threatening more than the biodiversity however; Myanmar's fiscal livelihood is also in harm's way. Mangroves are valued at $100,000 to $277,000 per square kilometer and if managed in a sustainable fashion, can infuse constant income to the emerging Myanmarese economy. This study analyzed three coastline regions, the Ayeyarwady Delta, Rakhine and Tanintharyi, and mapped the spatial extent of mangrove forest during the dry season in 2000 and 2013. The classifications were derived from Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and Landsat 8 Operation Land Imager (OLI) imagery, as well as the Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) digital elevation model information. This data was atmospherically corrected, mosaicked, masked and classified in ENVI, followed by ArcGIS to perform raster calculations and create final products. Forest degradation collected from 2000 to 2013 was later used to forecast the density and health of Mangroves in the year 2030. These results were subsequently presented to project partners Dr. Peter Leimgruber and Ellen Aiken at the Smithsonian Conservation Biology Institute in Front Royal, VA. After the presentation of the project to the partners, these organizations formally passed on to the Myanmar Ministry of Environment, Conservation and Forestry for policy makers and forest managers to utilize in order to protect the Myanmar mangrove ecosystem while sustaining a healthy economy.

Weber, Samuel J.↗

NASA NTRSDate not supplied

Synthetic Hyperspectral Data for Global Water Quality Algorithm Development

Eutrophication and increasing prevalence of potentially toxic algal blooms (cyanoHABs) among global inland water bodies have become a major ecological concern and require direct attention. There is now a growing necessity to develop pragmatic approaches that allow timely and effective extrapolation of local aquatic processes, to spatially resolved global products. Planned aquatic biogeochemistry remote sensing data products from hyperspectral imagers such as NASA’s Surface Biology and Geology (SBG) mission and relevant aquatic sensor sensitivity precursor airborne imaging spectrometer data provide unprecedented radiometric resolution and sensor sensitivity for characterizing complex aquatic ecosystems. However, scarcity of high-quality freshwater in-situ optical data hinders our capability to develop and validate robust retrieval algorithms. A state-of-the-art synthetic dataset of paired top-of-atmosphere, bottom-of-atmosphere, and optical and biogeophysical data was developed through radiative transfer modeling to simulate natural freshwater ecosystems. A synthetic or precursor dataset for SBG is being used to train robust machine learning models to derive water quality products pertinent to SBG mission objectives. The dataset is also used to show the potential of performing vigorous aquatic sensitivity studies and explored pathways for how best to optimize hyperspectral data for machine learning development. A processing pipeline and resultant global synthetic/precursor dataset for inland waters is presented to establish the innovation for water quality studies of inland waters globally. Optical Society of America Imaging and Applied Optics Congress, Hyperspectral Imaging and Sounding of the Environment (OSA HISE) Meeting, 19-23 July 2021, Virtual Meeting, https://www.osa.org/enus/meetings/osa_meetings/optical_sensors_and_sensing_congress/program/hyperspectral_imaging_and_sounding_of_the_environm/

Synthetic↗

NASA NTRS1993

The dynamics of hydroponic crops for simulation studies of the CELSS initial reference configurations

During the past several years, the NASA Program in Controlled Ecological Life Support Systems (CELSS) has continued apace with crop research and logistic, technological, and scientific strides. These include the CELSS Test Facility planned for the space station and its prototype Engineering Development Unit, soon to be active at Ames Research Center (as well as the advanced crop growth research chamber at Ames); the large environmental growth chambers and the planned human test bed facility at Johnson Space Center; the NSCORT at Purdue with new candidate crops and diverse research into the CELSS components; the gas exchange data for soy, potatoes, and wheat from Kennedy Space Center (KSC); and the high-precision gas exchange data for wheat from Utah State University (USU). All these developments, taken together, speak to the need for crop modeling as a means to connect the findings of the crop physiologists with the engineers designing the system. A need also exists for crop modeling to analyze and predict the gas exchange data from the various locations to maximize the scientific yield from the experiments. One fruitful approach employs what has been called the 'energy cascade'. Useful as a basis for CELSS crop growth experimental design, the energy cascade as a generic modeling approach for CELSS crops is a featured accomplishment in this report. The energy cascade is a major tool for linking CELSS crop experiments to the system design. The energy cascade presented here can help collaborations between modelers and crop experimenters to develop the most fruitful experiments for pushing the limits of crop productivity. Furthermore, crop models using the energy cascade provide a natural means to compare, feature for feature, the crop growth components between different CELSS experiments, for example, at Utah State University and Kennedy Space Center.

Volk, Tyler↗

NASA NTRSDate not supplied

New York Ecological Forecasting: Utilizing NASA Earth Observations to Map Ash Distribution and Inform Emerald Ash Borer Control

Since their first sightings in the U.S. in 2002, emerald ash borer beetles (Agrilus planipennis; EAB) have killed millions of native ash (Fraxinus spp.) trees across 35 states. Infected ash stands frequently exhibit complete mortality, with the predicted result being the functional extinction of native ash in U.S. forests. In August of 2020, EAB was discovered in the 6.1-million-acre Adirondack Park. The team’s partners at the Adirondack Park Invasive Plant Program (APIPP) desired ash tree distribution and EAB susceptibility information to help improve EAB bio-control efficiency and apply the methodology to future invasive programs. To assist, the team mapped ash tree distribution using NASA Earth observations from Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and Shuttle Radar Topography Mission (SRTM), along with hyperspectral imagery from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). Field data from the Monitoring and Managing Ash (MaMA) project, iMapInvasives and iNaturalist databases, and the New York State Department of Environmental Conservation (NYSDEC) provided ground truthing for mapping and modeling. Results indicate that for ash detection, the team’s Spectral Angle Mapping (SAM) hyperspectral classification is slightly more sensitive but less accurate than multispectral Random Forest (RF) classification, though neither method was above a ~20% detection rate. End products include maps of ash extent derived from both imagery types, a model forecasting future spread scenarios based on current EAB presence, and outreach materials. These products inform APIPP’s management decisions and facilitate public awareness of EAB’s threat to communities within the region.

Liam Megraw↗

NASA NTRS1979

Soil stabilization by a prokaryotic desert crust - Implications for Precambrian land biota

The ecology of the cyanophyte-dominated stromatolitic mat forming the ground cover over desert areas of Utah and Colorado is investigated and implications for the formation of mature Precambrian soils are discussed. The activation of the growth of the two species of filamentous cyanophyte identified and the mobility of their multiple trichromes upon wetting are observed, accompanied by the production and deposition of a sheath capable of accreting and stabilizing sand and clay particles. The formation of calcium carbonate precipitates upon the repeated wetting and drying of desert crust is noted, and it is suggested that the desert crust community may appear in fossil calcrete deposits as lithified microscopic tubes and cellular remains of algal trichromes. The invasion of dry land by both marine and freshwater algae on the model of the desert crust is proposed to be responsible for the accumulation, stabilization and biogenic modification of mature Precambrian soils.

Campbell, S. E.↗

NASA NTRS1992

Techniques for optimal crop selection in a controlled ecological life support system

A Controlled Ecological Life Support System (CELSS) utilizes a plant's natural ability to regenerate air and water while being grown as a food source in a closed life support system. Current plant research is directed toward obtaining quantitative empirical data on the regenerative ability of each species of plant and the system volume and power requirements. Two techniques were adapted to optimize crop species selection while at the same time minimizing the system volume and power requirements. Each allows the level of life support supplied by the plants to be selected, as well as other system parameters. The first technique uses decision analysis in the form of a spreadsheet. The second method, which is used as a comparison with and validation of the first, utilizes standard design optimization techniques. Simple models of plant processes are used in the development of these methods.

Mccormack, Ann↗

NASA NTRS1993

Techniques for optimal crop selection in a controlled ecological life support system

Mccormack, Ann↗

NASA NTRS2013

Phylogenetic Conservatism in Plant Phenology

Phenological events defined points in the life cycle of a plant or animal have been regarded as highly plastic traits, reflecting flexible responses to various environmental cues. The ability of a species to track, via shifts in phenological events, the abiotic environment through time might dictate its vulnerability to future climate change. Understanding the predictors and drivers of phenological change is therefore critical. Here, we evaluated evidence for phylogenetic conservatism the tendency for closely related species to share similar ecological and biological attributes in phenological traits across flowering plants. We aggregated published and unpublished data on timing of first flower and first leaf, encompassing 4000 species at 23 sites across the Northern Hemisphere. We reconstructed the phylogeny for the set of included species, first, using the software program Phylomatic, and second, from DNA data. We then quantified phylogenetic conservatism in plant phenology within and across sites. We show that more closely related species tend to flower and leaf at similar times. By contrasting mean flowering times within and across sites, however, we illustrate that it is not the time of year that is conserved, but rather the phenological responses to a common set of abiotic cues. Our findings suggest that species cannot be treated as statistically independent when modelling phenological responses.Closely related species tend to resemble each other in the timing of their life-history events, a likely product of evolutionarily conserved responses to environmental cues. The search for the underlying drivers of phenology must therefore account for species' shared evolutionary histories.

phylogenetic conservatism↗

NASA NTRS2002

Data from TRMM Field Experiments at the Goddard Earth Sciences (GES) DISC DAAC Tropical Rainfall Measuring Mission Field Experiments (TRMM FEs)

The basic objectives of TRMM Field Experiments (FEs) are to evaluate the physical assumptions made by TRMM. rainfall algorithms, initialize and validate the cloud resolving models, test latent heating retrievals from TRMM mea- surements, and evaluate methods to estimate rainfall and latent heating from ground-based radars. The field experiments were designed as a group, so that specific measure ments could be compared between experiments in order to gain insight into the regional dependence of any findings. The TExas FLorida UNderflight Experiments (TEFLUN) were designed to provide validation measurements for TRMM and for the enhancement of TRMM precipitation algorithms. TEFLUN-A focused on east Texas. TEFLUN-B was conducted in close coordination with the Third Convection And Moisture Experiment (CAMEX-3) in Florida. The TRMM-LBA was conducted in coordination with the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA). The LBA objectives are to further our understanding of the climatological, ecological, bie geochemical, and hydrological processes in Amazonia and the impact of land use/land change on these processes. Specifically, TRMM-LBA addressed issues related to land precipitation algorithms. The Kwa jalein Experiment (KWAJEX), conducted on the Kwajalein Island in the Republic of Marshall Islands (RMI), was designed to address issues of TRMM products over the ocean. The purpose of the South China Sea Monsoon Experiment (SCSMEX) was to study the water and energy cycle of the Asian monsoon in order to provide better understanding and improve prediction. and instruments of the TRMM FEs. The platforms and instruments of the TRMM FEs are given.

Source record↗

NASA NTRS2023

New York Ecological Conservation: Evaluating Agricultural Conservation Easement Impact Using Earth Observations to Examine Avoided Soil Carbon Loss to Development

Farmland provides ecosystems and communities with services ranging from habitat conservation to food security. As total U.S. farmland continues to decline, agricultural lands near urban areas are especially vulnerable. Our project partners—Finger Lakes Land Trust, Genesee Land Trust, and Saratoga Preserving Land and Nature (PLAN)—can use study results to better profile farmland vulnerability, issuing conservation easements to protect maximum acreage in Saratoga County and the Finger Lakes Region of New York. Multiple existing studies effectively use remote sensing imagery to analyze historical land cover and forecast future change. This study examined soil carbon stocks and land cover change to estimate avoided soil carbon loss. We also predicted farmland vulnerability. We completed these analyses using European Space Agency (ESA) and NASA Earth observations that include Landsat 5 Thematic Mapper (TM), Landsat 8 Operational Land Imager (OLI), Landsat 9 OLI-2, Sentinel-2 Multispectral Instrument (MSI), and Suomi National Polar-Orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) for nighttime lights data that aided in the land change model analysis. We determined that the conversion of agriculture to development from 1990 to 2022 occurred at rates of 0.91% (Finger Lakes) and 7% (Saratoga). Urban development is predicted to increase surrounding urban centers through 2030 and 2050. We also estimate that between 26.5 and 348,101 kilotons (Finger Lakes) and 3.7 and 58,006 kilotons (Saratoga) of soil carbon losses have been avoided through agricultural easements. Findings from this study will support our partners in determining agricultural conservation easement benefits and prioritizing the acquisition of future easement sites.

Agriculture↗

NASA NTRS2019

Assessing the Use of SAR/Optical Data Fusion and TensorFlow for Improved Mangrove Mapping

Mangrove forests are found in intertidal zones of tropical regions around the world and provide important ecological and economic benefits – they are considered carbon sequesters, habitats for flora and fauna, and natural barriers to hurricanes and tsunamis. Wood from mangrove forests are used as fuel and building materials in surrounding coastal communities, therefore promoting local livelihoods. Despite the importance of these ecosystems, mangrove forests have historically been degraded in natural processes such as severe weather, and anthropogenic factors like conversion to agriculture and aquaculture. This study assesses change in mangrove forests in Nigeria and Mozambique from 2015 to 2018 using SAR and optical data fusion. Due to frequent cloud cover over the study area, SAR and optical data is fused to obtain gap-free imagery without clouds. Landsat-8 OLI and Sentinel-1 imagery is fused with TensorFlow, an open source platform used in developing machine learning models. The resulting images are classified to discriminate mangrove forest cover from other land cover types, and change is estimated using image differencing. Understanding the rates and magnitude of mangrove change across space and time can aid in identifying priority areas for forest regeneration, and can help construct sustainable management practices for the future.

Strattman, Katherine↗

NASA NTRS1993

A comparison of spectral mixture analysis an NDVI for ascertaining ecological variables

In this study, we compare the performance of spectral mixture analysis to the Normalized Difference Vegetation Index (NDVI) in detecting change in a grassland across topographically-induced nutrient gradients and different management schemes. The Konza Prairie Research Natural Area, Kansas, is a relatively homogeneous tallgrass prairie in which change in vegetation productivity occurs with respect to topographic positions in each watershed. The area is the site of long-term studies of the influence of fire and grazing on tallgrass production and was the site of the First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment (FIFE) from 1987 to 1989. Vegetation indices such as NDVI are commonly used with imagery collected in few (less than 10) spectral bands. However, the use of only two bands (e.g. NDVI) does not adequately account for the complex of signals making up most surface reflectance. Influences from background spectral variation and spatial heterogeneity may confound the direct relationship with biological or biophysical variables. High dimensional multispectral data allows for the application position of techniques such as derivative analysis and spectral curve fitting, thereby increasing the probability of successfully modeling the reflectance from mixed surfaces. The higher number of bands permits unmixing of a greater number of surface components, separating the vegetation signal for further analyses relevant to biological variables.

Wessman, Carol A.↗

NASA NTRS1986

An analysis of the productivity of a CELSS continuous algal culture system

One of the most attractive aspects of using algal cultures as plant components for a Closed Ecological Life Support Systems (CELSS) is the efficiency with which they can be grown. Although algae are not necessarily intrinsically more efficient than higher plants, the ease which they can be handled and manipulated (more like chemical reagents than plants), and the culturing techniques available, result in much higher growth rates than are usually attainable with higher plants. Furthermore, preliminary experiments have demonstrated that algal growth and physiology is not detectable altered in a microgravity environment, (1) whereas the response of higher plants to zero gravity is unknown. In order to rationally design and operate culture systems, it is necessary to understand how the macroparameters of a culture system, e.g., productivity, are related to the physiological aspects of the algal culture. A first principles analysis of culture system is discussed, and a mathematical model that describes the relationship of culture productivity to the cell concentration of light-limited culture is derived. The predicted productivity vs cell concentration curve agrees well with the experimental data obtained to test this model, indicating that this model permits an accurate prediction of culture productivity given the growth parameters of the system.

Radmer, R.↗

NASA NTRS2021

Louisiana Water Resources: Using NASA Earth Observations to Monitor Historical Changes in the Extension of Seagrass Meadows in the Breton National Wildlife Refuge in Louisiana

The barrier islands of Louisiana’s Breton National Wildlife Refuge (BNWR) are disappearing due to sea level rise, extreme hurricanes, sediment starvation, and the Deepwater Horizon oil spill. This decline in land area has damaged important bird habitat and reduced the islands’ ability to protect coastal Louisiana from storm surges. The persistence of the islands is synergetic to that of the surrounding seagrass beds; seagrass binds together land, protecting the islands from erosion, and the loss of land exposes the seagrass and accelerates its decline. Furthermore, seagrass is independently important, absorbing excess nutrients and providing habitat for marine ecosystems. Here we present the Tool for Coastal Remote Ecological Observations in Louisiana (Tool CREOL), a Google Earth Engine Tool built to easily access data from Landsat 5 TM, Landsat 7 ETM+, Landsat 8 OLI, and Aqua and Terra MODIS. We show, using time series and maps generated using the tool, how land area and seagrass have responded to destructive events from the past 36 years (1984-2021). In only 7 years, Hurricane Georges (1998), Ivan (2004), and Katrina (2005) reduced land area by approximately 85%, accompanied by a major decline in seagrass extent. Tool CREOL will have strategic utility in planning upcoming restoration and revegetation efforts planned by Louisiana’s Coastal Protection and Restoration Authority in the Breton National Wildlife Refuge and will provide up-to-date monitoring of the results of that project. The tool serves as a basic model which can be adapted to study similar coastal regions in the world.

Mariam Moeen↗