Dataset Information

Partitioning the Relative Importance of Phylogeny and Environmental Conditions on Phytoplankton Fatty Acids.

ABSTRACT: Essential fatty acids (EFA), which are primarily generated by phytoplankton, limit growth and reproduction in diverse heterotrophs. The biochemical composition of phytoplankton is well-known to be governed both by phylogeny and environmental conditions. Nutrients, light, salinity, and temperature all affect both phytoplankton growth and fatty acid composition. However, the relative importance of taxonomy and environment on algal fatty acid content has yet to be comparatively quantified, thus inhibiting predictions of changes to phytoplankton food quality in response to global environmental change. We compiled 1145 published marine and freshwater phytoplankton fatty acid profiles, consisting of 208 species from six major taxonomic groups, cultured in a wide range of environmental conditions, and used a multivariate distance-based linear model to quantify the total variation explained by each variable. Our results show that taxonomic group accounts for 3-4 times more variation in phytoplankton fatty acids than the most important growth condition variables. The results underscore that environmental conditions clearly affect phytoplankton fatty acid profiles, but also show that conditions account for relatively low variation compared to phylogeny. This suggests that the underlying mechanism determining basal food quality in aquatic habitats is primarily phytoplankton community composition, and allows for prediction of environmental-scale EFA dynamics based on phytoplankton community data. We used the compiled dataset to calculate seasonal dynamics of long-chain EFA (LCEFA; ?C20 ?-3 and ?-6 polyunsaturated fatty acid) concentrations and ?-3:?-6 EFA ratios in Lake Washington using a multi-decadal phytoplankton community time series. These analyses quantify temporal dynamics of algal-derived LCEFA and food quality in a freshwater ecosystem that has undergone large community changes as a result of shifting resource management practices, highlighting diatoms, cryptophytes and dinoflagellates as key sources of LCEFA. Moreover, the analyses indicate that future shifts towards cyanobacteria-dominated communities will result in lower LCEFA content in aquatic ecosystems.

SUBMITTER: Galloway AW

PROVIDER: S-EPMC4468072 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Partitioning the Relative Importance of Phylogeny and Environmental Conditions on Phytoplankton Fatty Acids.

Galloway Aaron W E AW Winder Monika M

PloS one 20150615 6

Essential fatty acids (EFA), which are primarily generated by phytoplankton, limit growth and reproduction in diverse heterotrophs. The biochemical composition of phytoplankton is well-known to be governed both by phylogeny and environmental conditions. Nutrients, light, salinity, and temperature all affect both phytoplankton growth and fatty acid composition. However, the relative importance of taxonomy and environment on algal fatty acid content has yet to be comparatively quantified, thus inh ...[more]

PMID: 26076015

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Project description:BackgroundWhile Expressed Sequence Tags (ESTs) have proven a viable and efficient way to sample genomes, particularly those for which whole-genome sequencing is impractical, phylogenetic analysis using ESTs remains difficult. Sequencing errors and orthology determination are the major problems when using ESTs as a source of characters for systematics. Here we develop methods to incorporate EST sequence information in a simultaneous analysis framework to address controversial phylogenetic questions regarding the relationships among the major groups of seed plants. We use an automated, phylogenetically derived approach to orthology determination called OrthologID generate a phylogeny based on 43 process partitions, many of which are derived from ESTs, and examine several measures of support to assess the utility of EST data for phylogenies.ResultsA maximum parsimony (MP) analysis resulted in a single tree with relatively high support at all nodes in the tree despite rampant conflict among trees generated from the separate analysis of individual partitions. In a comparison of broader-scale groupings based on cellular compartment (ie: chloroplast, mitochondrial or nuclear) or function, only the nuclear partition tree (based largely on EST data) was found to be topologically identical to the tree based on the simultaneous analysis of all data. Despite topological conflict among the broader-scale groupings examined, only the tree based on morphological data showed statistically significant differences.ConclusionBased on the amount of character support contributed by EST data which make up a majority of the nuclear data set, and the lack of conflict of the nuclear data set with the simultaneous analysis tree, we conclude that the inclusion of EST data does provide a viable and efficient approach to address phylogenetic questions within a parsimony framework on a genomic scale, if problems of orthology determination and potential sequencing errors can be overcome. In addition, approaches that examine conflict and support in a simultaneous analysis framework allow for a more precise understanding of the evolutionary history of individual process partitions and may be a novel way to understand functional aspects of different kinds of cellular classes of gene products.

Project description:BackgroundUnderstanding the drivers of large-scale vegetation change is critical to managing landscapes and key to predicting how projected climate and land use changes will affect regional vegetation patterns. This study aimed to improve our understanding of the role, magnitude and spatial distribution of the key environmental factors driving vegetation change in southern African savanna, and how they vary across physiographic gradients.Methodology/principal findingsWe applied Dynamic Factor Analysis (DFA), a multivariate times series dimension reduction technique to ten years of monthly remote sensing data (MODIS-derived normalized difference vegetation index, NDVI) and a suite of environmental covariates: precipitation, mean and maximum temperature, soil moisture, relative humidity, fire and potential evapotranspiration. Monthly NDVI was described by cyclic seasonal variation with distinct spatiotemporal patterns in different physiographic regions. Results support existing work emphasizing the importance of precipitation, soil moisture and fire on NDVI, but also reveal overlooked effects of temperature and evapotranspiration, particularly in regions with higher mean annual precipitation. Critically, spatial distributions of the weights of environmental covariates point to a transition in the importance of precipitation and soil moisture (strongest in grass-dominated regions with precipitation<750 mm) to fire, potential evapotranspiration, and temperature (strongest in tree-dominated regions with precipitation>950 mm).Conclusions/significanceWe quantified the combined spatiotemporal effects of an available suite of environmental drivers on NDVI across a large and diverse savanna region. The analysis supports known drivers of savanna vegetation but also uncovers important roles of temperature and evapotranspiration. Results highlight the utility of applying the DFA approach to remote sensing products for regional analyses of landscape change in the context of global environmental change. With the dramatic increase in global change research, this methodology augurs well for further development and application of spatially explicit time series modeling to studies at the intersection of ecology and remote sensing.

Dataset Information

Partitioning the Relative Importance of Phylogeny and Environmental Conditions on Phytoplankton Fatty Acids.

Publications

Partitioning the Relative Importance of Phylogeny and Environmental Conditions on Phytoplankton Fatty Acids.

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