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31	Correlation of Watershed NDVI Values to Benthic Macroinvertebrate Biodiversity in Eight North American Wadeable Streams Gallagher, Denice Lynne 05 1900 (has links) Water quality of a stream or river is influenced by the surrounding landscape and vegetation. The Normalized Difference Vegetation Index (NDVI) is commonly used to characterize landcover and vegetation density. Benthic macroinvertebrates are ubiquitous in freshwater streams and are excellent indicators of the quality of freshwater habitats. Data from one NDVI remote sensing flight and one macroinvertebrate sampling event for eight wadeable stream study sites in the National Ecological Observatory Network (NEON) were acquired. Proportions of high, moderate, and sparse vegetation were calculated for each stream watershed using ArcGIS. Functional feeding groups and tolerance values were assigned to macroinvertebrate taxa. The Fourth-corner and RLQ methods of analysis, available in the ade4 package for R software, were used to evaluate the relationships of macroinvertebrate traits with environmental variables. Hypothesis testing using Model 6 in the ade4 package resulted in p-values of 0.066 and 0.057 for global (overall) significance. Mean NDVI values of moderately vegetated areas and proportion of sparse vegetation were found to be significant to percent shredders at alpha ≤ 0.05. Results of these methods of analysis, when combined with traditional macroinvertebrate sampling metrics, show that NDVI can be a useful, additional tool to characterize a watershed and its effects on macroinvertebrate community composition and structure. watershed normalized difference vegetation index RLQ and Fourth-corner ecology remote sensing geographic information system (GIS) functional feeding groups tolerance value water quality vegetation coverage riparian
32	Linear and segmented linear trend detection for vegetation cover using GIMMS normalized difference vegetation index data in semiarid regions of Nigeria Osunmadewa, Babatunde A., Wessollek, Christine, Karrasch, Pierre 06 September 2019 (has links) Quantitative analysis of trends in vegetation cover, especially in Kogi state, Nigeria, where agriculture plays a major role in the region’s economy, is very important for detecting long-term changes in the phenological behavior of vegetation over time. This study employs the use of normalized difference vegetation index (NDVI) [global inventory modeling and mapping studies 3g (GIMMS)] data from 1983 to 2011 with detailed methodological and statistical approach for analyzing trends within the NDVI time series for four selected locations in Kogi state. Based on the results of a comprehensive study of seasonalities in the time series, the original signals are decomposed. Different linear regression models are applied and compared. In order to detect structural changes over time a detailed breakpoint analysis is performed. The quality of linear modeling is evaluated by means of statistical analyses of the residuals. Standard deviations of the regressions are between 0.015 and 0.021 with R2 of 0.22–0.64. Segmented linear regression modeling is performed for improvement and a decreasing standard deviation of 33%–40% (0.01–0.013) and R2 up to 0.82 are obtained. The approach used in this study demonstrates the added value of long-term time series analyses of vegetation cover for the assessment of agricultural and rural development in the Guinea savannah region of Kogi state, Nigeria. info:eu-repo/classification/ddc/530 ddc:530 info:eu-repo/classification/ddc/610 ddc:610
33	Multispectral imaging of Sphagnum canopies: measuring the spectral response of three indicator species to a fluctuating water table at Burns Bog Elves, Andrew 02 May 2022 (has links) Northern Canadian peatlands contain vast deposits of carbon. It is with growing urgency that we seek a better understanding of their assimilative capacity. Assimilative capacity and peat accumulation in raised bogs are linked to primary productivity of resident Sphagnum species. Understanding moisture-mediated photosynthesis of Sphagnum spp. is central to understanding peat production rates. The relationship between depth to water table fluctuation and spectral reflectance of Sphagnum moss was investigated using multispectral imaging at a recovering raised bog on the southwest coast of British Columbia, Canada. Burns Bog is a temperate oceanic ombrotrophic bog. Three ecohydrological indicator species of moss were chosen for monitoring: S. capillifolium, S. papillosum, and S. cuspidatum. Three spectral vegetation indices (SVIs) were used to characterize Sphagnum productivity: the normalized difference vegetation index 660, the chlorophyll index, and the photochemical reflectance index. In terms of spectral sensitivity and the appropriateness of SVIs to species and field setting, we found better performance for the normalized difference vegetation index 660 in the discrimination of moisture mediated species-specific reflectance signals. The role that spatiotemporal scale and spectral mixing can have on reflectance signal fidelity was tested. We were specifically interested in the relationship between changes in the local water table and Sphagnum reflectance response, and whether shifting between close spatial scales can affect the statistical strength of this relationship. We found a loss of statistical significance when shifting from the species-specific cm2 scale to the spectrally mixed dm2 scale. This spatiospectral uncoupling of the moisture mediated reflectance signal has implications for the accuracy and reliability of upscaling from plot based measurements. In terms of species-specific moisture mediated reflectance signals, we were able to effectively discriminate between the three indicator species of Sphagnum along the hummock-to-hollow gradient. We were also able to confirm Sphagnum productivity and growth outside of the vascular growing season, establishing clear patterns of reflectance correlated with changes in the local moisture regime. The strongest relationships for moisture mediated Sphagnum productivity were found in the hummock forming species S. capillifolium. Each indicator Sphagnum spp. of peat has distinct functional traits adapted to its preferred position along the ecohydrological gradient. We also discovered moisture mediated and species-specific reflectance phenologies. These phenospectral characteristics of Sphagnum can inform future monitoring work, including the creation of a regionally specific phenospectral library. It’s recommended that further close scale multispectral monitoring be carried out incorporating more species of moss, as well as invasive and upland species of concern. Pervasive vascular reflectance bias in remote sensing products has implications for the reliability of peatland modelling. Avoiding vascular bias, targeted spectral monitoring of Sphagnum indicator species provides a more reliable measure for the modelling of peatland productivity and carbon assimilation estimates. / Graduate peatland peatland restoration peatland monitoring peatland modelling peat peat moss multispectral multispectral imaging multicamera array multitemporal multiple linear regression linear mixed effects Sphagnum sphagna Sphagnum capillifolium Sphagnum papillosum Sphagnum cuspidatum spatiospectral uncoupling near-sensing remote sensing phenospectral phenology phenologies phenospectral bias phenospectral libraries carbon assimilation carbon dioxide carbon dynamics carbon emissions carbon geographies carbon mineralization carbon sequestration carbon source carbon sink carbon storage irrecoverable carbon climate forcing methane Ecological Restoration restoration ecology ecohydrology ecohydrological restoration hydrology ecohydrological gradients ecological integrity reflectance nature based solutions ombrotrophic moss raised peatland mires mires photochemical reflectance index normalized difference vegetation index chlorophyll index climate change climate forcing climate envelope climatope nonvascular vascular bias plant functional type plant functional types structure equation models spectral vegetation indices hummock hollow acrotelm catotelm diplotelmic biocrusts organic soil periodicity moisture deficit senescence rejuvenescence productivity photosynthesis light use efficiency photosynthetic function photosynthetically active radiation water table hydrology rewetting depth to water table landscape change landscape degradation peat subsidence Burns Bog

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