Luna van der Loos- Doctor of Philosophy
- Researcher at Naturalis Biodiversity Center
Luna van der Loos
- Doctor of Philosophy
- Researcher at Naturalis Biodiversity Center
About
37
Publications
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619
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Introduction
Studying seaweed biodiversity, ecology, and microbiome interactions.
Current institution
Additional affiliations
January 2020 - present
Publications
Publications (37)
The green seaweed Ulva relies on associated bacteria for morphogenesis and is an important model to study algal-bacterial interactions. Ulva -associated bacteria exhibit high turnover across environmental gradients, leading to the hypothesis that bacteria contribute to the acclimation potential of the host. However, the functional variation of thes...
Third-generation sequencing platforms, such as Oxford Nanopore Technology (ONT), have made it possible to characterize communities through the sequencing of long amplicons. While this theoretically allows for an increased taxonomic resolution compared to short-read sequencing platforms such as Illumina, the high error rate remains problematic for a...
Using a DNA barcoding approach, we document an extensive number of inter-species cryptic introductions of bladed Bangiales (Pyropia) at an historic oyster aquaculture site in the Southern North Sea. We sampled the intertidal of 20 locations along the Belgian and Dutch coastline, ranging from sheltered to exposed, between February 2022 and April 202...
Third-generation sequencing platforms, such as Oxford Nanopore Technology (ONT), have made it possible to characterise communities through the sequencing of long amplicons. Whilst this theoretically allows for an increased taxonomic resolution compared to short-read sequencing platforms such as Illumina, the high error rate remains problematic to a...
The green seaweed Ulva depends on its associated bacteria for morphogenesis and is an important model to study algal-bacterial interactions. Ulva-associated bacteria exhibit high turnover across environmental gradients, leading to the hypothesis that bacteria contribute to the acclimation potential of the host. Yet little is known about the variati...
Effective monitoring of non-indigenous seaweeds and combatting their effects relies on a solid confirmation of the non-indigenous status of the respective species. We critically analysed the status of presumed non-indigenous seaweed species reported from the Mediterranean Sea, the Northeast Atlantic Ocean and Macaronesia, resulting in a list of 140...
Marine macroalgae (seaweeds) are important primary producers and foundation species in coastal ecosystems around the world. Seaweeds currently contribute to an estimated 51% of the global mariculture production, with a long-term growth rate of 6% per year, and an estimated market value of more than US$11.3 billion. Viral infections could have a sub...
Effective monitoring and combatting the effect of non-indigenous seaweeds relies on a solid confirmation of the non-indigenous status of the species. We critically analysed the status of presumed non-indigenous seaweed species reported from the Mediterranean Sea, the Northeast Atlantic Ocean and Macaronesia, resulting in a list of 140 species whose...
Stony corals play a key role in the marine biodiversity of many tropical coastal areas as suppliers of substrate, food and shelter for other reef organisms. Therefore, it is remarkable that coral diversity usually does not play a role in the planning of protected areas in coral reef areas. In the present study we examine how stony coral diversity p...
The green seaweed Ulva is a model system to study seaweed–bacteria interactions, but the impact of environmental drivers on the dynamics of these interactions is little understood. In this study, we investigated the stability and variability of the seaweed‐associated bacteria across the Atlantic–Baltic Sea salinity gradient. We characterized the ba...
Microbes are vitally important for seaweed growth, functioning and reproduction, and are likely to have a big impact on aquaculture. Algae-associated bacteria, however, remain mostly unmonitored in aquaculture. Here, we studied the microbiomes of Ulva australis and Ulva lacinulata, three natural populations and an aquaculture set-up, based on full-...
UPDATED VERSION. These identification cards provide an overview of almost 60 red, brown and green seaweed species that are frequently encountered on Bonaire (Caribbean), to help you explore the macroalgal biodiversity in the marine parks.
Zeewieren komen algemeen voor langs de Nederlandse kust. Toch is het laatste determineerwerk voor onze wieren al bijna veertig jaar oud. In de nieuwe Veldgids Zeewieren worden meer dan 130 groen-, rood- en bruinwieren beschreven en staan bijna 600 foto’s. Uniek is dat deze veldgids zich vooral richt op gebruik in het veld, dus zonder microscoop.
V...
With the growing anthropogenic pressure on marine ecosystems, the need for efficient monitoring of biodiversity grows stronger. DNA metabarcoding of bulk samples is increasingly being implemented in ecosystem assessments and is more cost‐efficient and less time‐consuming than monitoring based on morphology. However, before raw sequences are obtaine...
Coral bleaching due to global warming currently is the largest threat to coral reefs, which may be exacerbated by altered water quality. Elevated levels of the UV filter oxybenzone in coastal waters as a result of sunscreen use have recently been demonstrated. We studied the effect of chronic oxybenzone exposure and elevated water temperature on co...
Summary:
The marine environment of the Netherlands harbours an enormous diversity. Long-term monitoring is of essential importance to be able to understand the complex interactions and processes taking place in this ecosystem. The “Monitoring Project Underwater Shore” (MOO-project), started by the ANEMONE Foundation in 1994, aims to monitor the mar...
We studied the effect of chronic oxybenzone exposure and elevated temperature on coral health. Microcolonies of Stylophora pistillata and Acropora tenuis were cultured in 20 flow-through aquaria, of which 10 were exposed to oxybenzone at a field-relevant concentration of ~0.06 μg L ⁻¹ at 26 °C. After two weeks, half of the corals experienced a heat...
When studying the effects of climate change on eukaryotic organisms we often oversee a major ecological process: the interaction with microbes. Eukaryotic hosts and microbes form functional units, termed holobionts, where microbes play crucial roles in host functioning. Environmental stress may disturb these complex mutualistic relations. Macroalga...
Increased plant biomass is observed in terrestrial systems due to rising levels of atmospheric CO2, but responses of marine macroalgae to CO2 enrichment are unclear. The 200% increase in CO2 by 2100 is predicted to enhance the productivity of fleshy macroalgae that acquire inorganic carbon solely as CO2 (non‐carbon dioxide‐concentrating mechanism [...
On 11 November 2017 one specimen of the Pacific amphipod Aoroides semicurvatus was collected in the southwestern delta area of the Netherlands. This is the first record from Europe outside France. Subsequently, on 18 and 23 November, tens of specimens were collected from about half a liter of red seaweeds from two locations in the Oosterschelde, ne...
To assess the suitability of southern-Australian macroalgae as potential marine resources for fatty acids (FA), and in particular polyunsaturated fatty acids (PUFA), analysis of 61 species, comprising of 11 Chlorophyta, 17 Phaeophyceae (Ochrophyta) and 33 Rhodophyta, was conducted. Total fatty acid (TFA) concentrations varied considerably (between...
This study provides a baseline of the marine algal flora composition around St. Eustatius, Dutch Caribbean, by describing algal community structure in terms of species richness and beta diversity, and by providing a taxonomically reliable DNA barcode collection. A total of 156 species was found, including 91 that represent new records for St. Eusta...
The Polyphysaceae is a well-studied family of green algae occurring in tropical and warm-temperate regions around the world. One of its species, Parvocaulis exiguus (Solms-Laubach) S. Berger et al. (Phycologia 42:506–561, 2003), has previously been reported from both the Indian and the Pacific Oceans. This report presents the first record of Parvoc...
General information Coral reefs and seagrass beds play a vital role in tropical marine environments. In both of these ecosystems, larger algae (macroalgae) play an important part: they provide food for herbivores, and they stabilize the structure of reefs. Algae are also remarkable in that they are responsible for the high productivity that charact...
A new nudibranch species for the Netherlands has been discovered, Eubranchus linensis, but as it turns out, that species has already been here for a long time. The related species Eubranchus pallidus has been found since 1951. However, photo records showed that some of the earlier observations identified as Eubranchus pallidus were Eubranchus linen...
Questions
Questions (4)
I am currently working on an ecological dataset with presence-absence counts. I would like to use a PERMANOVA to test if several factors significantly influence the community composition. However, a few of the factors give a significant PERMDISP result. As the design is unbalanced, I fear this may affect the results. Specifically, as one factor that is significant had greater dispersion in the smaller group (which could be due to the test being too liberal), whereas the factors that were not significant had a greater dispersion in the larger group (could be due to the test being too conservative).
I have read the article by Anderson et al. 2017 on the modified F2 statistics that could handle heterogeneous data (paper: "Some solutions to the multivariate Behrens–Fisher problem for dissimilarity‐based analyses") and I think this could be helpful in my case. However, I am unsure as to how to calculate these statistics for my own dataset, as I am not very experienced with maths.
I am working mainly in R and I read in the article that all simulations described in Sections 3 and 5 were performed using R. However, there is no more explanation than that....
I was wondering if anyone knows if there are pieces of the code are available? Or if there is any software that can calculate F2 statistics?
I tested the effect of pH on the delta 13C isotope change (beginning-end of experiment) in two species.
When I do a two-way ANOVA (two factors: pH and species, both with 2 levels), I get a non-significant interaction, and both pH and species have a significant effect (for pH, the p-value = 0.008).
When I take a subset however (only using species 2), with a one-way ANOVA for pH, pH does not have a significant effect (p-value=0.15).
How do I know which test is correct?
(I have added two barplots to illustrate this. One barplot with the full dataset and one barplot with the subset).
I have rapid light curve data (ETR for each PAR value) for 24 different specimen of macroalgae. The dataset has three factors: species (species 1 and species 2), pH treatment (treatment 1 and treatment 2) and Day (day 1 of the experiment and day 8 of the experiment).
I have fitted a model defined by Webb 1974 to 8 subsets of the data:
species 1,pH treatment 1, day 1
species 1, pH treatment 1, day 8
species 1, pH treatment 2, day 1...etc.
I have plotted the curves of the data that is predicted by the model. The model also gives the values and standard error of two parameters: alpha (the slope of the curve) and Ek (the light saturation coefficient). I have added an image of the scatterplot + 4 curves predicted by the model for species 1 (so each curve has a different combination of the factors pH treatment and Day).
I was wondering what the best way would be to statistically test if the 8 curves differ from each other? (or in other words: how to test if the slopes and Ek of the models are significantly different?). When googling for answers, I found many ways to check which models with your data better, but not how to test if the different treatments also cause differences in rapid light curves.
Any help would be greatly appreciated.
Cheers,
Luna
I am trying to calculate surface areas from a picture to measure growth. I tried to convert the picture to a vector and then calculate the area in Adobe Illustrator or ImageJ, but neither works. I was wondering if anyone knows good software to accurately calculate surfacre areas from pictures or vectors?
