A dataset of European marine mites (Trombidiformes, Halacaridae)

Abstract

We present a data set on marine mites (family Halacaridae) in European waters. The data set gathers all the published records of marine mites from the North European Seas, Lusitania, Mediterranean Sea and Black Sea marine provinces, all belonging to the temperate North Atlantic geographical realm. The database includes 3006 records collected from 260 original publications. For each record, the dataset provides complementary taxonomic, geographical, and ecological information, as well as remarks regarding the sampling methods used in each study. We use this dataset to briefly discuss potential knowledge gaps and biases across marine regions and habitats. We hope these data will provide a baseline for further studies in biogeography and ecology.

Biases and distribution patterns in hard‐bodied microscopic animals (Acari: Halacaridae): Size does not matter, but generalism and sampling effort do

“…We prefer this more conservative approach, though, rather than assuming that collections were always performed next to the station because we did not want to favour our working hypothesis a priori, but rather evaluate to what extent the hypothesis is sustained despite the issues implicit to the available data. Additionally, the variation in species richness was explained by the number of records and published articles associated with each marine station, indicating that our knowledge of diversity patterns is influenced by the number of researchers working in a given area (Fontaneto et al, 2012; Rubio‐López et al, 2022). Sampling intensity does not drive actual species richness, but it does condition our knowledge of species richness and distribution patterns, acting as a confounding factor when patterns of diversity are to be inferred (Fontaneto et al, 2012).…”

“…We used a data set previously assembled (Rubio‐López et al, 2022) with all occurrences of marine halacarids recorded between 70°N–20°N and 50°W–50°E. We divided our studied area according to marine provinces and countries following the Marine Ecoregions of the World (Spalding et al, 2007) and the Biodiversity Information Standards of the Taxonomic Database Working Group (http://www.tdwg.com).…”

“…In other words, we assume that scientists prefer sampling nearby a marine station, but as their sampling localities move away from a marine station, the importance of the distance would decay rapidly. Given the uncertainty in assigning coordinates for some records (Rubio‐López et al, 2022), we did not use the exact coordinates, which could be biased, but alleviated the uncertainties by grouping the records in six distance bins, following the Sturges approximation, which determines the optimal number of classes in a frequency distribution. Each bin has been included as a continuous integer variable in our analyses.…”

“…p values for significant predictors are marked in bold. is influenced by the number of researchers working in a given area (Fontaneto et al, 2012;Rubio-López et al, 2022). Sampling intensity does not drive actual species richness, but it does condition our knowledge of species richness and distribution patterns, acting as a confounding factor when patterns of diversity are to be inferred (Fontaneto et al, 2012).…”

“…(H2) Regardless of these biases, we expect that differences in species composition between marine provinces will explain the overall differences in species replacement across European marine stations. Yet, given the uneven sampling effort (Rubio-López et al, 2022), the species known in stations with fewer published papers and records will represent a subsample of the species known in the stations that have been better sampled. (H3) Finally, larger and generalist species might be easier to find and capable to thrive in more localities, accumulating more records than smaller or more ecologically specialised species.…”