Abstract
Motivation
Linkage disequilibrium (LD) measures the correlation between genetic loci and is highly informative for association mapping and population genetics. As many studies rely on called ...genotypes for estimating LD, their results can be affected by data uncertainty, especially when employing a low read depth sequencing strategy. Furthermore, there is a manifest lack of tools for the analysis of large-scale, low-depth and short-read sequencing data from non-model organisms with limited sample sizes.
Results
ngsLD addresses these issues by estimating LD directly from genotype likelihoods in a fast, reliable and user-friendly implementation. This method makes use of the full information available from sequencing data and provides accurate estimates of linkage disequilibrium patterns compared with approaches based on genotype calling. We conducted a case study to investigate how LD decays over physical distance in two avian species.
Availability and implementation
The methods presented in this work were implemented in C/C and are freely available for non-commercial use from https://github.com/fgvieira/ngsLD.
Supplementary information
Supplementary data are available at Bioinformatics online.
Reef‐building corals are mixotrophic organisms that can obtain nutrition from endosymbiotic microalgae (autotrophy) and particle capture (heterotrophy). Heterotrophic nutrition is highly beneficial ...to many corals, particularly in times of stress. Yet, the extent to which different coral species rely on heterotrophic nutrition remains largely unknown because it is challenging to quantify.
We developed a quantitative approach to investigate coral nutrition using carbon isotope (δ13C) analysis of six essential amino acids (AAESS) in a common Indo‐Pacific coral (Pocillopora meandrina) from the fore reef habitat of Palmyra Atoll. We sampled particulate organic matter (POM) and zooplankton as the dominant heterotrophic food sources in addition to the coral host and endosymbionts. We also measured bulk tissue carbon (δ13C) and nitrogen (δ15N) isotope values of each sample type.
Patterns among δ13C values of individual AAESS provided complete separation between the autotrophic (endosymbionts) and heterotrophic nutritional sources. In contrast, bulk tissue δ13C and δ15N values were highly variable across the putative food sources and among the coral and endosymbiont fractions, preventing accurate estimates of coral nutrition on Palmyra.
We used linear discriminant analysis to quantify differences among patterns of AAESS δ13C values, or ‘fingerprints’, of the food resources available to corals. This allowed for the development of a quantitative continuum of coral nutrition that can identify the relative contribution of autotrophic and heterotopic nutrition to individual colonies. Our approach revealed exceptional variation in conspecific colonies at scales of metres to kilometres. On average, 41% of AAESS in P. meandrina on Palmyra are acquired via heterotrophy, but some colonies appear capable of obtaining the majority of AAESS from one source or the other.
The use of AAESS δ13C fingerprinting analysis offers a significant improvement on the current methods for quantitatively assessing coral trophic ecology. We anticipate that this approach will facilitate studies of coral nutrition in the field, which are essential for comparing coral trophic ecology across taxa and multiple spatial scales. Such information will be critical for understanding the role of heterotrophic nutrition in coral resistance and/or resilience to ongoing environmental change.
A free Plain Language Summary can be found within the Supporting Information of this article.
A free Plain Language Summary can be found within the Supporting Information of this article.
Kelp forests are highly productive coastal habitats that serve as biodiversity hotspots and provide valuable ecosystem services. Despite being one the largest marine biomes, kelp forests have been ...drastically understudied relative to other marine systems. Notably, while the role of kelp as habitat‐forming, or ‘foundation species', is well‐documented, a comprehensive understanding of kelp forest food web structure is lacking, particularly regarding the importance of kelp‐derived energy/nutrients to consumers. Here, we provide a biogeographic perspective on the energetic underpinning of kelp forests based on published literature. We targeted studies which used geochemical proxies – stable isotope analysis – to examine the transfer of carbon from kelp to local consumers. These studies (n = 94) were geographically skewed, with > 40% from Northern European Seas and Temperate Northeast Pacific. Quantitative estimates for the percentage of kelp energy (or kelp + macroalgae if sources were pooled) incorporated by local consumers came from 43 publications, which studied 141 species and 35 broader taxonomic groups. We examined these data for trends among functional groups and across upwelling regimes. No patterns are evident at present, perhaps due to the paucity or variability of available data. However, energetic subsides from kelps clearly support a wide range of diverse taxa around the globe. We also characterized biogeographic patterns in δ13C values of kelps and particulate organic matter (POM, a phytoplankton proxy), to evaluate potential limitations of stable isotope analysis in disentangling the relative contributions of pelagic versus benthic resources to coastal food webs. Globally, kelps and POM differed by > 4.5‰, but there was substantial variation among regions and kelp species. Accordingly, we discuss advances in stable isotope techniques which are facilitating more precise analysis of these complex energetic pathways. We end by proposing four main avenues of critical future research that will shed light on the resilience of these communities to global change.
Carbon isotope fingerprinting, or multivariate analysis using δ13C values of individual compounds, is a powerful tool in ecological studies, particularly measurements of essential amino acids (EAA ...δ13C). Despite the widespread application of this technique, there has been little methodological validation to determine (a) whether multivariate EAA δ13C signatures (fingerprints) of primary producer groups vary across space and time and (b) what biochemical mechanisms drive these patterns.
Here, we evaluate the spatiotemporal consistency in EAA δ13C fingerprints among nearshore primary producers: Chlorophyta (Ulva sp.), Ochrophyta (kelps), particulate organic matter (POM) and phytoplankton, and Rhodophyta. We analysed 135 samples from 14 genera collected in Alaska, California and Chile. The collections included historical museum samples (1896–1980 CE) of the giant kelp, Macrocystis pyrifera. We employed canonical analysis of principal coordinates and generalized linear models (GLMs) to, respectively, characterize isotopic fingerprints and evaluate the effect of taxonomy, local upwelling regimes, ecological setting, and time on individual EAA δ13C values and associated fingerprints. We also calculated amino acid discrimination values (∆13C) to identify key biochemical pathways responsible for these patterns.
We found remarkable consistency in EAA δ13C fingerprints of marine algae across space and through time. Kelps and rhodophytes exhibited statistically distinct multivariate isotopic patterns regardless of geographical location, species identity or time (kelps). In contrast, isotopic fingerprints of POM/phytoplankton and Ulva overlapped substantially. GLMs indicated that producer family, presumably due to the presence/absence of carbon concentrating mechanisms, and site locality are important determinants of individual amino acid δ13C values. Taxonomy was also a key variable for EAA δ13C fingerprints. The calculated discrimination values suggest variation in (a) metabolism of pyruvate and oxaloacetate‐derived amino acids and (b) production of storage and structural carbohydrates are responsible for taxonomic differences in isotopic fingerprints.
We conclude EAA δ13C fingerprinting is a robust method for tracing the contribution of diverse primary producer taxa to coastal food webs. We show that this technique can be applied to modern and historical samples, as well as consumers collected across continental scales. The high fidelity of EAA δ13C multivariate patterns coupled with biochemical mechanisms provides a powerful framework for future studies of carbon flow across broad biogeographical and ecological contexts.
Read the free Plain Language Summary for this article on the Journal blog.
Read the free Plain Language Summary for this article on the Journal blog.
Ecosystems globally are under threat from ongoing anthropogenic environmental change. Effective conservation management requires more thorough biodiversity surveys that can reveal system-level ...patterns and that can be applied rapidly across space and time. Using modern ecological models and community science, we integrate environmental DNA and Earth observations to produce a time snapshot of regional biodiversity patterns and provide multi-scalar community-level characterization. We collected 278 samples in spring 2017 from coastal, shrub, and lowland forest sites in California, a complex ecosystem and biodiversity hotspot. We recovered 16,118 taxonomic entries from eDNA analyses and compiled associated traditional observations and environmental data to assess how well they predicted alpha, beta, and zeta diversity. We found that local habitat classification was diagnostic of community composition and distinct communities and organisms in different kingdoms are predicted by different environmental variables. Nonetheless, gradient forest models of 915 families recovered by eDNA analysis and using BIOCLIM variables, Sentinel-2 satellite data, human impact, and topographical features as predictors, explained 35% of the variance in community turnover. Elevation, sand percentage, and photosynthetic activities (NDVI32) were the top predictors. In addition to this signal of environmental filtering, we found a positive relationship between environmentally predicted families and their numbers of biotic interactions, suggesting environmental change could have a disproportionate effect on community networks. Together, these analyses show that coupling eDNA with environmental predictors including remote sensing data has capacity to test proposed Essential Biodiversity Variables and create new landscape biodiversity baselines that span the tree of life.
Abstract Carbon isotope fingerprinting, or multivariate analysis using δ 13 C values of individual compounds, is a powerful tool in ecological studies, particularly measurements of essential amino ...acids (EAA δ 13 C). Despite the widespread application of this technique, there has been little methodological validation to determine (a) whether multivariate EAA δ 13 C signatures (fingerprints) of primary producer groups vary across space and time and (b) what biochemical mechanisms drive these patterns. Here, we evaluate the spatiotemporal consistency in EAA δ 13 C fingerprints among nearshore primary producers: Chlorophyta ( Ulva sp.), Ochrophyta (kelps), particulate organic matter (POM) and phytoplankton, and Rhodophyta. We analysed 135 samples from 14 genera collected in Alaska, California and Chile. The collections included historical museum samples (1896–1980 CE) of the giant kelp, Macrocystis pyrifera . We employed canonical analysis of principal coordinates and generalized linear models (GLMs) to, respectively, characterize isotopic fingerprints and evaluate the effect of taxonomy, local upwelling regimes, ecological setting, and time on individual EAA δ 13 C values and associated fingerprints. We also calculated amino acid discrimination values (∆ 13 C) to identify key biochemical pathways responsible for these patterns. We found remarkable consistency in EAA δ 13 C fingerprints of marine algae across space and through time. Kelps and rhodophytes exhibited statistically distinct multivariate isotopic patterns regardless of geographical location, species identity or time (kelps). In contrast, isotopic fingerprints of POM/phytoplankton and Ulva overlapped substantially. GLMs indicated that producer family, presumably due to the presence/absence of carbon concentrating mechanisms, and site locality are important determinants of individual amino acid δ 13 C values. Taxonomy was also a key variable for EAA δ 13 C fingerprints. The calculated discrimination values suggest variation in (a) metabolism of pyruvate and oxaloacetate‐derived amino acids and (b) production of storage and structural carbohydrates are responsible for taxonomic differences in isotopic fingerprints. We conclude EAA δ 13 C fingerprinting is a robust method for tracing the contribution of diverse primary producer taxa to coastal food webs. We show that this technique can be applied to modern and historical samples, as well as consumers collected across continental scales. The high fidelity of EAA δ 13 C multivariate patterns coupled with biochemical mechanisms provides a powerful framework for future studies of carbon flow across broad biogeographical and ecological contexts. Read the free Plain Language Summary for this article on the Journal blog.
Abstract Reef‐building corals are mixotrophic organisms that can obtain nutrition from endosymbiotic microalgae (autotrophy) and particle capture (heterotrophy). Heterotrophic nutrition is highly ...beneficial to many corals, particularly in times of stress. Yet, the extent to which different coral species rely on heterotrophic nutrition remains largely unknown because it is challenging to quantify. We developed a quantitative approach to investigate coral nutrition using carbon isotope (δ 13 C) analysis of six essential amino acids (AA ESS ) in a common Indo‐Pacific coral ( Pocillopora meandrina ) from the fore reef habitat of Palmyra Atoll. We sampled particulate organic matter (POM) and zooplankton as the dominant heterotrophic food sources in addition to the coral host and endosymbionts. We also measured bulk tissue carbon (δ 13 C) and nitrogen (δ 15 N) isotope values of each sample type. Patterns among δ 13 C values of individual AA ESS provided complete separation between the autotrophic (endosymbionts) and heterotrophic nutritional sources. In contrast, bulk tissue δ 13 C and δ 15 N values were highly variable across the putative food sources and among the coral and endosymbiont fractions, preventing accurate estimates of coral nutrition on Palmyra. We used linear discriminant analysis to quantify differences among patterns of AA ESS δ 13 C values, or ‘fingerprints’, of the food resources available to corals. This allowed for the development of a quantitative continuum of coral nutrition that can identify the relative contribution of autotrophic and heterotopic nutrition to individual colonies. Our approach revealed exceptional variation in conspecific colonies at scales of metres to kilometres. On average, 41% of AA ESS in P. meandrina on Palmyra are acquired via heterotrophy, but some colonies appear capable of obtaining the majority of AA ESS from one source or the other. The use of AA ESS δ 13 C fingerprinting analysis offers a significant improvement on the current methods for quantitatively assessing coral trophic ecology. We anticipate that this approach will facilitate studies of coral nutrition in the field, which are essential for comparing coral trophic ecology across taxa and multiple spatial scales. Such information will be critical for understanding the role of heterotrophic nutrition in coral resistance and/or resilience to ongoing environmental change. A free Plain Language Summary can be found within the Supporting Information of this article.
Vicarious calibration approaches using in situ measurements saw first use in the early 1980s and have since improved to keep pace with the evolution of the radiometric requirements of the sensors ...that are being calibrated. The advantage of in situ measurements for vicarious calibration is that they can be carried out with traceable and quantifiable accuracy, making them ideal for interconsistency studies of on-orbit sensors. The recent development of automated sites to collect the in situ data has led to an increase in the available number of datasets for sensor calibration. The current work describes the Radiometric Calibration Network (RadCalNet) that is an effort to provide automated surface and atmosphere in situ data as part of a network including multiple sites for the purpose of optical imager radiometric calibration in the visible to shortwave infrared spectral range. The key goals of RadCalNet are to standardize protocols for collecting data, process to top-of-atmosphere reflectance, and provide uncertainty budgets for automated sites traceable to the international system of units. RadCalNet is the result of efforts by the RadCalNet Working Group under the umbrella of the Committee on Earth Observation Satellites (CEOS) Working Group on Calibration and Validation (WGCV) and the Infrared Visible Optical Sensors (IVOS). Four radiometric calibration instrumented sites located in the USA, France, China, and Namibia are presented here that were used as initial sites for prototyping and demonstrating RadCalNet. All four sites rely on collection of data for assessing the surface reflectance as well as atmospheric data over that site. The data are converted to top-of-atmosphere reflectance within RadCalNet and provided through a web portal to allow users to either radiometrically calibrate or verify the calibration of their sensors of interest. Top-of-atmosphere reflectance data with associated uncertainties are available at 10 nm intervals over the 400 nm to 1000 nm spectral range at 30 min intervals for a nadir-viewing geometry. An example is shown demonstrating how top-of-atmosphere data from RadCalNet can be used to determine the interconsistency between two sensors.
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