Science Enabled by Specimen Data
Granja‐Fernández, R., E. J. Ramírez‐Chávez, F. A. Rodríguez‐Zaragoza, and A. López‐Pérez. 2024. Ophiuroidea Gray, 1840 potential species richness across the eastern Pacific: An approach using species distribution modelling. Journal of Biogeography. https://doi.org/10.1111/jbi.14990
Aim To estimate patterns of potential species richness (PSR) and identify shallow‐water Ophiuroidea hotspots based on their modelled distribution throughout the eastern Pacific Ocean (EP).LocationEastern Pacific Ocean.TaxonEchinodermata: Ophiuroidea.MethodsWe compiled and analysed the occurrence of 137 shallow‐water (≤200 m) species of Ophiuroidea from the EP using Species Distribution Models (SDM; use of Maxent) and buffering for rare species to create the first maps of PSR of the class in the EP to gain insight into their patterns.ResultsThe highest PSR was found in mid‐latitudes, decreasing towards high latitudes, denoting a robust latitudinal pattern. All PSR hotspots were found in mid‐latitudes and correspond to northern Mexico, the area between Corinto (Nicaragua) and the Gulf of Panama, and the Galapagos Islands. The pattern is mainly linked to topographic configuration, although the models also suggest temperature and other environmental factors as important. Additionally, the pattern correlates (R = 98) with the pattern of the family Amphiuridae, suggesting that its richness can be used as a proxy for exploring Ophiuroidea richness patterns elsewhere.Main ConclusionsThe richness of Ophiuroidea from the EP follows a latitudinal pattern as do other invertebrate groups. The Gulf of California, Central America, and Galapagos Islands are confirmed as hotspots of Ophiuroidea richness. However, other significant areas include the west coast of southern Baja California, Chiapas, Guatemala, and Nicaragua. PSR patterns are influenced by diverse environmental variables and the distribution patterns of the most conspicuous families. SDMs are useful for understanding large‐scale distribution patterns. This work is the first PSR assessment of marine invertebrates from the EP.
Martin, D., M. T. Aguado, M.-A. Fernández Álamo, T. A. Britayev, M. Böggemann, M. Capa, S. Faulwetter, et al. 2021. On the Diversity of Phyllodocida (Annelida: Errantia), with a Focus on Glyceridae, Goniadidae, Nephtyidae, Polynoidae, Sphaerodoridae, Syllidae, and the Holoplanktonic Families. Diversity 13: 131. https://doi.org/10.3390/d13030131
Phyllodocida is a clade of errantiate annelids characterized by having ventral sensory palps, anterior enlarged cirri, axial muscular proboscis, compound chaetae (if present) with a single ligament, and of lacking dorsolateral folds. Members of most families date back to the Carboniferous, although …
Newbold, T., L. N. Hudson, S. Contu, S. L. L. Hill, J. Beck, Y. Liu, C. Meyer, et al. 2018. Widespread winners and narrow-ranged losers: Land use homogenizes biodiversity in local assemblages worldwide H. Morlon [ed.],. PLOS Biology 16: e2006841. https://doi.org/10.1371/journal.pbio.2006841
Human use of the land (for agriculture and settlements) has a substantial negative effect on biodiversity globally. However, not all species are adversely affected by land use, and indeed, some benefit from the creation of novel habitat. Geographically rare species may be more negatively affected by…
Newbold, T., P. Oppenheimer, A. Etard, and J. J. Williams. 2020. Tropical and Mediterranean biodiversity is disproportionately sensitive to land-use and climate change. Nature Ecology & Evolution 4: 1630–1638. https://doi.org/10.1038/s41559-020-01303-0
Global biodiversity is undergoing rapid declines, driven in large part by changes to land use and climate. Global models help us to understand the consequences of environmental changes for biodiversity, but tend to neglect important geographical variation in the sensitivity of biodiversity to these …
Zhang, X., and A. C. J. Vincent. 2018. Predicting distributions, habitat preferences and associated conservation implications for a genus of rare fishes, seahorses (Hippocampusspp.) M. Beger [ed.],. Diversity and Distributions 24: 1005–1017. https://doi.org/10.1111/ddi.12741
Aim: To identify useful sources of species data and appropriate habitat variables for species distribution modelling on rare species, with seahorses as an example, deriving ecological knowledge and spatially explicit maps to advance global seahorse conservation. Location: The shallow seas. Methods: …