Restoration of Oyster (Crassostrea virginica) Habitat for Multiple Estuarine Species Benefits

Increase in nitrogen concentration and declining eelgrass beds in Great Bay Estuary have been observed in the last decades. These two parameters are clear indicators of the impending problems for NH’s estuaries. The NH Department of Environmental Services (DES) in collaboration with the New Hampshire Estuaries Project (NHEP) adopted the assumption that eelgrass survival can be used as the water quality target for nutrient criteria development for NH’s estuaries. One of the hypotheses put forward regarding eelgrass decline is that a possible eutrophication response to nutrient increases in the Great Bay Estuary has been the proliferation of nuisance macroalgae, which has reduced eelgrass area in Great Bay Estuary. To test this hypothesis, mapping of eelgrass and nuisance macroalgae beds using hyperspectral imagery was suggested. A hyperspectral imagery was conducted by SpecTIR in August 2007 using an AISA Eagle sensor. The collected dataset was used to map eelgrass and nuisance macroalgae throughout the Great Bay Estuary. This report outlines the configured procedure for mapping the macroalgae and eelgrass beds using hyperspectral imagery. No ground truth measurements of eelgrass or macroalgae were collected as part of this project, although eelgrass ground truth data was collected as part of a separate project. Guidance from eelgrass and macroalgae experts was used for identifying training sets and evaluating the classification results. The results produced a comprehensive eelgrass and macroalgae map of the estuary. Three recommendations are suggested following the experience gained in this study: conducting ground truth measurements at the time of the HS survey, acquiring the current DEM model of Great Bay Estuary, and examining additional HS datasets with expert eelgrass and macroalgae guidance. These three issues can improve the classification results and allow more advanced applications, such as identification of macroalgae types

Macroalgae and eelgrass mapping in Great Bay Estuary using AISA hyperspectral imagery

Increase in nitrogen concentration and declining eelgrass beds in Great Bay Estuary have been observed in the last decades. These two parameters are clear indicators of the impending problems for NH’s estuaries. The NH Department of Environmental Services (DES) in collaboration with the New Hampshire Estuaries Project (NHEP) adopted the assumption that eelgrass survival can be used as the water quality target for nutrient criteria development for NH’s estuaries. One of the hypotheses put forward regarding eelgrass decline is that a possible eutrophication response to nutrient increases in the Great Bay Estuary has been the proliferation of nuisance macroalgae, which has reduced eelgrass area in Great Bay Estuary. To test this hypothesis, mapping of eelgrass and nuisance macroalgae beds using hyperspectral imagery was suggested. A hyperspectral imagery was conducted by SpecTIR in August 2007 using an AISA Eagle sensor. The collected dataset was used to map eelgrass and nuisance macroalgae throughout the Great Bay Estuary. This report outlines the configured procedure for mapping the macroalgae and eelgrass beds using hyperspectral imagery. No ground truth measurements of eelgrass or macroalgae were collected as part of this project, although eelgrass ground truth data was collected as part of a separate project. Guidance from eelgrass and macroalgae experts was used for identifying training sets and evaluating the classification results. The results produced a comprehensive eelgrass and macroalgae map of the estuary. Three recommendations are suggested following the experience gained in this study: conducting ground truth measurements at the time of the HS survey, acquiring the current DEM model of Great Bay Estuary, and examining additional HS datasets with expert eelgrass and macroalgae guidance. These three issues can improve the classification results and allow more advanced applications, such as identification of macroalgae types

Multiscale collection and analysis of submerged aquatic vegetation spectral profiles for Eurasian watermilfoil detection

The ability to differentiate a non-native aquatic plant, Myriophyllum spicatum (Eurasian watermilfoil or EWM), from other submerged aquatic vegetation (SAV) using spectral data collected at multiple scales was investigated as a precursor to mapping of EWM. Spectral data were collected using spectroradiometers for SAV taken out of the water, from the side of a boat directly over areas of SAV and from a lightweight portable radiometer system flown from an unmanned aerial system (UAS). EWM was spectrally different from other SAV when using 651 spectral bands collected in ultraviolet to near-infrared range of 350 to 1000 nm but does not provide a practical system for EWM mapping because this exceeds the capabilities of available airborne hyperspectral imaging systems. Using only six spectral bands corresponding to an available multispectral camera or eight wetlands-centric bands did not reliably differentiate EWM from other SAV and assemblages. However, a modified version of the normalized difference vegetation index (mNDVI), using a ratio of red-edge to red light, was significantly different among dominant vegetation groups. Also, averaging the full range of spectral to 65 10-nm wide bands, similar to available hyperspectral imaging systems, provided the ability to identify EWM separately from other SAV. The UAS-collected spectral data had the lowest remote sensing reflectance versus the out-of-water and boatside data, emphasizing the need to collect optimized data. The spectral data collected for this study support that with relatively clear and calm water, hyperspectral data, and mNDVI, it is likely that UAS-based imaging can help with mapping and monitoring of EWM

Applying Island Biogeography Theory and Ecoacoustic Approaches to Explore the Species Composition, Richness, and Biodiversity in Northern Temperate Salt Marsh Pools of the Little River Estuary

Salt marsh habitats are prevalent throughout coastal New England and offer a wide rangeof ecological services, including serving as nursery habitats to both transient and resident species, trapping sediment and nutrients to keep pace with rising sea levels, and improving water quality through filtration of runoff. These complex habitats remain poorly understood, especially regarding the biological communities that occupy them. The northern temperate salt marshes that characterize the coast of Northern New England contain northern temperate salt marsh pools (NTSPs) that serve as important wildlife habitats with unique abiotic conditions and biotic communities. The isolated nature of these pools from their estuary mainland, with the exception of inputs from infrequent tidal flooding, allows them to be characterized as islands in the context of island biogeography theory. Here, I assess two island biogeography variables, island size (pool volume) and connectivity (distance of pools from a tidal creek), to determine their effect on the abundance, species richness, and biodiversity of NTSPs. Data from this study indicated that NTSP size is positively correlated with both organism abundance and species richness, while NTSP connectivity is correlated with biodiversity. The monitoring of ecosystems using passive acoustic techniques has gained increasing popularity in recent years, as it is cost effective, and less time intensive than traditional biodiversity surveys. To expedite the process of analyzing recordings, many acoustic indices have been developed to analyze soundscape recordings. During this study, I used passive acoustic methods to monitor 20 NTSPs during the summer of 2021 to determine whether acoustic indices in the R packaged soundecology and seewave (H, BIO, ACI, ADI, AEI, and NDSI) highlight relationships between NTSP soundscapes with the abundance, species richness, and/or biodiversity of their inhabitants. This analysis determined that the AEI index had the strongest correlation with organism abundance and species richness, while only the maximum values produced by the BIO index correlated with NTSP biodiversity. This analysis also determined that the abiotic variable pool volume was positively correlated with ACI and AEI index values, as well as maximum values from the BIO index. While correlations between both biotic and abiotic variables and acoustic indices were found, it is recommended that acoustic indices designed for aquatic use are created, as there are many differences between aquatic and terrestrial soundscapes

Remote Sensing Methods and Applications for Detecting Change in Forest Ecosystems

Forest ecosystems are being altered by climate change, invasive species, and additional stressors. Our ability to detect these changes and quantify their impacts relies on detailed data across spatial and temporal scales. This dissertation expands the ecological utility of long-term satellite imagery by developing high quality forest mapping products and examining spatiotemporal changes in tree species abundance and phenology across the northeastern United States (US; the ‘Northeast’). Species/genus-level forest composition maps were developed by integrating field data and Landsat images to model abundance at a sub-pixel scale. These abundance maps were then used to 1) produce a more detailed, accurate forest classification compared to similar products and 2) construct a 30-year time-series of abundance for eight common species/genera. Analyzing the time-series data revealed significant abundance trends in notable species, including increases in American beech (Fagus grandifolia) at the expense of sugar maple (Acer saccharum). Climate was the dominant predictor of abundance trends, indicating climate change may be altering competitive relationships. Spatiotemporal trends in deciduous forest phenology – start and end of the growing season (SOS/EOS) – were examined based on MODIS imagery from 2001-2015. SOS exhibited a slight advancing trend across the Northeast, but with a distinct spatial pattern: eastern ecoregions showed advance and western ecoregions delay. EOS trended substantially later almost everywhere. SOS trends were linked to winter-spring temperature and precipitation trends; areas with higher elevation and fall precipitation anomalies had negative associations with EOS trends. Together, this work demonstrates the value of remote sensing in furthering our understanding of long-term forest responses to changing environmental conditions. By highlighting potential changes in forest composition and function, the research presented here can be used to develop forest conservation and management strategies in the Northeast

Multiple approaches for assessing mangrove biophysical and biochemical variables using in situ and remote sensing techniques

Mangrove forests are important ecosystems and play a key role in maintaining the equilibrium in coastal lagoons and estuaries. However, in recent years, there has been a considerable loss of mangrove extension due to anthropogenic activities. Recent studies suggest that multiple in situ and remote sensing approaches must be carried out to understand the dynamics in these complex ecosystems. Therefore, the objective for this PhD dissertation is to develop multiple techniques for monitoring the seasonal biophysical and biochemical conditions of the mangrove forests. Particular objectives will include: i. Test the feasibility of using a Chlorophyll Content Index from a CCM-200 unit as an estimator of the variation of leaf pigments (chlorophyll-a, chlorophyll-b) content for a range of mangrove species. ii. Assess changes in chlorophyll-a, leaf area, leaf length, and Leaf Area Index between the dry and rainy seasons in a variety of mangrove classes. iii. Assess the seasonal importance of in situ hyperspectral measurements (e.g. 450-1000 nm) for chlorophyll-a determination in a variety of mangrove species. And finally, iv. Determine whether an object-based image analysis approach can provide an accurate classification of mangroves from spaceborne Synthetic Aperture Radar data. The results from these studies could provide reliable information regarding seasonal ecological assessments of mangrove forests using in situ and remote sensing methods

Multitemporal Remote Sensing Based on an FVC Reference Period Using Sentinel-2 for Monitoring Eichhornia crassipes on a Mediterranean River

International audienceInvasive aquatic plants are a serious global ecological and socio-economic problem because they can cause local extinction of native species and alter navigation and fishing. Eichhornia crassipes (water hyacinth) is a dangerous invasive floating plant that is widely distributed throughout the world. In Lebanon, it has spread since 2006 in the Al Kabir River. Remote sensing techniques have been widely developed to detect and monitor dynamics and extents of invasive plants such as water hyacinth over large areas. However, they become challenging to use in narrow areas such as the Al Kabir River and we developed a new image-analysis method to extract water hyacinth areas on the river. The method is based on a time series of a biophysical variable obtained from Sentinel-2 images. After defining a reference period between two growing cycles, we used the fractional vegetation cover (FVC) to estimate the water hyacinth surface area in the river. This method makes it possible to monitor water hyacinth development and estimate the total area it colonizes in the river corridor. This method can help ecologists and other stakeholders to map invasive plants in rivers and improve their control

Assessing land use and land cover change in Los Molinos reservoir watershed and the effect on the reservoir water quality

Understanding and modelling land use and land cover (LULC) change have become one of the major subjects of interest for environmental management due to the negative effects that human activities generate on the normal functioning and dynamics of freshwater resources. Remote sensing and geographic information systems (GIS) are essential tools for assessing the drivers that cause LULC change and its relationship with lake and reservoir water quality. The objective of this study was to assess the spatial and temporal dynamics of LULC change in the watershed of Los Molinos reservoir (Argentina), and to investigate its relationship with the reservoir's water quality. Four Landsat imagery was used to analyse the LULC change in the studied watershed and in different buffer zones from 1990 to 2020. Further, the Normalized Difference Vegetation Index (NDVI) derived from a MODIS time-series dataset (2001–2020) was used to explain the effects of LULC change on the status of the reservoir. Results showed that the most significant LULC change started two decades ago and it has intensified during the last ten years. This change is related to the intensification of agriculture activities, and to the increasing conversion into urban areas, mainly on the shores of Los Molinos reservoir. During the period 2010–2020, urbanization located in the 1 km buffer zone defined from the shore of the reservoir increased at an annual rate of 18.02%. The degradation trend of LULC in Los Molinos watershed significantly contributed to the degradation of water quality of the reservoir. This was corroborated by analysing the MODIS NDVI time-series, which showed that since 2014 the NDVI trend-line presented an increasing behaviour and extreme values of NDVI, related to algal blooms, were more frequently observed.Fil: Bonansea, Matias. Universidad Nacional de Río Cuarto. Facultad de Ciencias Exactas Fisicoquímicas y Naturales. Instituto de Ciencias de la Tierra, Biodiversidad y Ambiente - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Ciencias de la Tierra, Biodiversidad y Ambiente; Argentina. Universidad Nacional de Río Cuarto. Facultad de Agronomía y Veterinaria; ArgentinaFil: Bazán, Raquel del Valle. Comisión Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; ArgentinaFil: German, Alba. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Comisión Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; ArgentinaFil: Ferral, Anabella. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Comisión Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; ArgentinaFil: Beltramone, Giuliana Beatriz. Comisión Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Cossavella, Ana Maria. Universidad Nacional de Córdoba; ArgentinaFil: Pinotti, Lucio Pedro. Universidad Nacional de Río Cuarto. Facultad de Ciencias Exactas Fisicoquímicas y Naturales. Instituto de Ciencias de la Tierra, Biodiversidad y Ambiente - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Ciencias de la Tierra, Biodiversidad y Ambiente; Argentin