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Nicole Chin Taylor

Publications and source records attributed to Nicole Chin Taylor.

3 recordsLinked to original sources

Multi-scale spectroscopy to map intertidal microbial biofilm community and trait diversity

Intertidal microbial biofilms, or microphytobenthos, support estuarine biogeochemical cycling, the physical stability of mudflats, and food webs, particularly those of migratory shorebirds. Photosynthetic biofilms dominated by diatoms, cyanobacteria, and chlorophytes represent a significant fraction of biofilm biomass and contain pigments that can be detected with remote sensing. These diverse biofilm community types vary in indicator pigments and functional traits related to biogeochemical cycling and nutritional quality. We modeled and mapped spatial variation in intertidal biofilm distribution, quantity, diversity, and functional traits using multi-scale spectroscopic data collected within southern San Francisco Bay, California, USA (South SFB). We developed a new biofilm index (B-index) from 5 mm HySpex spectra to detect biofilm presence. We developed single and multiple response partial least squares regression (PLS) models of chlorophyll -a (chl -a ; biomass indicator), indicator pigments: fucoxanthin and diadinoxanthin (diatoms), zeaxanthin (cyanobacteria), and chl -b (chlorophytes), and functional traits: carbohydrates, lipids, and total organic carbon from paired in situ biofilm data and field spectra. The B-index and PLS models were scaled to South SFB with a 3.7 m AVIRIS-NG hyperspectral image. The model %RMSE calculated from AVIRIS-NG test samples ranged from 12.7% for chl -a to 49% for chl -b ; for six of the eight models, %RMSE was 23% or below. Mapped community types differed in mapped traits, with average lipid concentrations three times higher in areas indicated as diatoms compared to other groups. Available maps depict for the first time the spatial variation of an important shorebird food resource and inform the contribution of intertidal biofilm in carbon and nutrient cycling.

California

Department of the Interior: DOI

Remotely sensed data and derived information contribute substantially to mission-critical work across the Department of the Interior (DOI). 1 This DOI section highlights a sample of DOI remote sensing applications and illustrates a range of technology, platforms, and specialized sensors employed.

conterminous United States

Variation in leaf reflectance spectra across the California flora partitioned by evolutionary history, geographic origin, and deep time

Evolutionary relatedness underlies patterns of functional diversity in the natural world. Hyperspectral remote sensing has the potential to detect these patterns in plants through inherited patterns of leaf reflectance spectra. We collected leaf reflectance data from across the California flora from plants grown in a common garden. Regions of the reflectance spectra vary in the depth and strength of phylogenetic signal. We also show that these differences are much greater than variation due to the geographic origin of the plant. At the phylogenetic extent of the California flora, spectral variation explained by the combination of ecotypic variation (divergent evolution) and convergent evolution of disparate lineages was minimal (3 to 7 %) but statistically significant. Interestingly, at the extent of a single genus ( Arctostaphylos ) no unique variation could be attributed to geographic origin. However, up to 18% of the spectral variation among Arctostaphylos individuals was shared between phylogeny and intraspecific variation stemming from ecotypic differences (i.e., geographic origin). Future studies could conduct more structured experiments (e.g., transplants or observations along environmental gradients) to disentangle these sources of variation and include other intraspecific variation (e.g., plasticity). We constrain broad scale spectral variability due to ecotypic sources, providing further support for the idea that phylogenetic clusters of species might be detectable through remote sensing. Phylogenetic clusters could represent a valuable dimension of biodiversity monitoring and detection.

California