Faster diversification on land than sea helps explain global biodiversity patterns among habitats and animal phyla

2015 ◽  
Vol 18 (11) ◽  
pp. 1234-1241 ◽  
Author(s):  
John J. Wiens
Keyword(s):  
Biodiversity Patterns ◽  
Animal Phyla ◽  
Global Biodiversity

Developing a Theory of Global Biodiversity

2018 ◽  
pp. 93-123
Author(s):  
Boris Worm ◽  
Derek P. Tittensor
Keyword(s):  
Species Richness ◽  
First Principles ◽  
Predictive Power ◽  
Global Distribution ◽  
Biodiversity Patterns ◽  
Modeling Approach ◽  
Possibility Space ◽  
Competing Hypotheses ◽  
Global Biodiversity

This chapter develops a body of theory to capture and test the key processes governing the global distribution of biodiversity. From this theory, it devises a spatial metacommunity model that enables the reconstruction of documented patterns of species richness from first principles and the prediction of their major features. The chapter starts with a simple, flexible, and tractable framework that can be built on and expanded in order to test competing hypotheses. This modeling approach may be described as an experimental toolbox for global biodiversity patterns. The aim is not necessarily to achieve the highest predictive power, but to explore the possibility space of global biodiversity patterns and their drivers.

Global biodiversity patterns of marine phytoplankton and zooplankton

Nature ◽  
2004 ◽  
Vol 429 (6994) ◽  
pp. 863-867 ◽  
Author(s):  
Xabier Irigoien ◽  
Jef Huisman ◽  
Roger P. Harris
Keyword(s):  
Marine Phytoplankton ◽  
Biodiversity Patterns ◽  
Global Biodiversity

scholarly journals Remotely-sensed productivity clusters capture global biodiversity patterns

2018 ◽  
Vol 8 (1) ◽  
Author(s):  
Nicholas C. Coops ◽  
Sean P. Kearney ◽  
Douglas K. Bolton ◽  
Volker C. Radeloff
Keyword(s):  
Remotely Sensed ◽  
Biodiversity Patterns ◽  
Global Biodiversity

scholarly journals Effectively and accurately mapping global biodiversity patterns for different regions and taxa

2021 ◽  
Author(s):  
Alice C. Hughes ◽  
Michael C. Orr ◽  
Qinmin Yang ◽  
Huijie Qiao
Keyword(s):  
Biodiversity Patterns ◽  
Global Biodiversity

Observed Patterns of Global Biodiversity

2018 ◽  
pp. 10-53
Author(s):  
Boris Worm ◽  
Derek P. Tittensor
Keyword(s):  
Species Richness ◽  
Deep Sea ◽  
Biodiversity Patterns ◽  
Space And Time ◽  
Marine Realm ◽  
Species Groups ◽  
Global Biodiversity ◽  
Biodiversity Changes ◽  
Terrestrial Biodiversity ◽  
Unimodal Pattern

This chapter summarizes and synthesizes known biodiversity patterns, and analyzes them for congruency over space and time. The discussion is limited to macroecological patterns at continental to global scales (thousands of km). The chapter also focuses on the simplest measure of biodiversity—namely, species richness. The discussions cover marine coastal biodiversity, marine pelagic biodiversity, deep-sea biodiversity, terrestrial biodiversity, changes in biodiversity patterns through time, and robustness of documented biodiversity patterns. Among the findings is that averaging across all known species groups on land and in the sea, tropical peaks in species richness were as common as subtropical peaks, whereas species groups cresting in temperate or polar latitudes were more exceptional. Thus, the oft-cited unimodal pattern of biodiversity appears frequently, particularly on land, but there is also evidence that supports a newly emerging paradigm of asymmetric unimodal or bimodal peaks often in the subtropics, and particularly in the marine realm.

scholarly journals Effectively and accurately mapping global biodiversity patterns for different regions and taxa

2020 ◽  
Author(s):  
Alice Hughes ◽  
Michael Orr ◽  
Qinmin Yang ◽  
Huije Qiao
Keyword(s):  
Biodiversity Patterns ◽  
Global Biodiversity

scholarly journals Complexity matters: Evaluating the impact of bioinformatics parameters on eukaryotic MOTU delimitation and taxonomy assignment

2021 ◽  
Vol 4 ◽  
Author(s):  
Holly Bik
Keyword(s):  
Recent Work ◽  
Marine Sediment ◽  
Dna Sequences ◽  
Environmental Dna ◽  
Microbial Eukaryotes ◽  
Dna Metabarcoding ◽  
Animal Phyla ◽  
Global Biodiversity ◽  
Intragenomic Variation ◽  
The Impact

Microbial metazoans (e.g. nematodes, copepods, tardigrades and other 'minor' animal phyla < 1mm in size) are ubiquitous and abundant across most ecosystems on earth. In marine sediment habitats, microbial metazoa exhibit high biodiversity but suffer from poor taxonomy and an ongoing lack of reference DNA sequences in public databases. Environmental DNA metabarcoding thus represents an increasingly critical tool for rapidly assessing the global biodiversity and phylogeographic patterns of such neglected metazoan groups. However, there are significant bioinformatics hurdles facing the study of microbial eukaryotes. Most software pipelines and databases have been designed and optimized for smaller (e.g. bacteria/archaea) or larger (e.g. vertebrate) taxa, and emphasize "standard" metabarcoding loci such as COI which are not useful for groups such as nematodes which lack universal COI primer binding regions. In addition, the sparsity of public reference barcodes for microbial metazoa often precludes accurate taxonomy assignments for unknown MOTUs in metabarcoding datasets. Here, I will present recent work focused on the refinement of bionformatics workflows for microbial metazoan groups, including efforts to account for intragenomic variation observed in rRNA loci, discrepancies in results across OTU vs. ASV generation pipelines, and biases in sequence-based taxonomhy assignment methods.

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