Global Patterns of Species Richness: Spatial Models for Conservation Planning Using Bioindicator and Precipitation Data

2008 ◽  
Vol 12 (4) ◽  
pp. 809-821 ◽  
Author(s):  
David L. Pearson ◽  
Steven S. Carroll
Author(s):  
Riccardo Testolin ◽  
Fabio Attorre ◽  
Peter Borchardt ◽  
Robert F. Brand ◽  
Helge Bruelheide ◽  
...  

2016 ◽  
Vol 51 (8) ◽  
pp. 958-966 ◽  
Author(s):  
Anderson Pedro Bernardina Batista ◽  
José Márcio de Mello ◽  
Marcel Régis Raimundo ◽  
Henrique Ferraço Scolforo ◽  
Aliny Aparecida dos Reis ◽  
...  

Abstract: The objective of this work was to analyze the spatial distribution and the behavior of species richness and diversity in a shrub savanna fragment, in 2003 and 2014, using ordinary kriging, in the state of Minas Gerais, Brazil. In both evaluation years, the measurements were performed in a fragment with 236.85 hectares, in which individual trees were measured and identified across 40 plots (1,000 m2). Species richness was determined by the total number of species in each plot, and diversity by the Shannon diversity index. For the variogram study, spatial models were fitted and selected. Then, ordinary kriging was applied and the spatial distribution of the assessed variables was described. A strong spatial dependence was observed between species richness and diversity by the Shannon diversity index (<25% spatial dependence degree). Areas of low and high species diversity and richness were found in the shrub savanna fragment. Spatial distribution behavior shows relative stability regarding the number of species and the Shannon diversity index in the evaluated years.


2018 ◽  
Vol 28 (2) ◽  
pp. 318-335 ◽  
Author(s):  
Mikko Tiusanen ◽  
Tea Huotari ◽  
Paul D. N. Hebert ◽  
Tommi Andersson ◽  
Ashley Asmus ◽  
...  

2019 ◽  
Vol 12 (4) ◽  
pp. 339-350
Author(s):  
Luciana Motta ◽  
Adriana Ruggiero ◽  
Guillermo de Mendoza ◽  
Julieta Massaferro

2019 ◽  
Vol 88 (1) ◽  
pp. 42-53 ◽  
Author(s):  
Bernhard A. Huber ◽  
Anne Chao

Ratio-like approaches for estimating global species richness have been criticised for their unjustified extrapolation from regional to global patterns. Here we explore the use of cumulative percentages of ‘new’ (i.e., not formally described) species over large geographic areas (‘megatransects’) as a means to overcome this problem. In addition, we take into account undetected species and illustrate these combined methods by applying them to a family of spiders (Pholcidae) that currently contains some 1,700 described species. The raw global cumulative percentage of new species (‘new’ as of the end of 2008, when 1,001 species were formally described) is 75.1%, and is relatively constant across large biogeographic regions. Undetected species are estimated using the Chao2 estimator based on species incidence data (date by species and locality by species matrices). The estimated percentage of new species based on the date by species matrices is 76.0% with an estimated standard error (s.e.) of 2.6%. This leads to an estimated global species richness of about 4,200 with a 95% confidence interval of (3,300, 5,000). The corresponding values based on locality by species matrices are 84.2% (s.e. 3.0%) and 6,300 with a 95% confidence interval of (4,000, 8,600). Our results suggest that the currently known 1,700 species of Pholcidae may represent no more than about 25–40% of the total species richness. The impact of further biasing factors like geography, species size and distribution, cryptic species, and model assumptions needs to be explored.


2018 ◽  
Author(s):  
Petr Keil ◽  
Jonathan M. Chase

What drives biodiversity and where are the most biodiverse places on Earth? The answer critically depends on spatial scale (grain), and is obscured by lack of data and mismatches in their grain. We resolve this with cross-scale models integrating global data on tree species richness (S) from 1338 local forest surveys and 287 regional checklists, enabling estimation of drivers and patterns of biodiversity at any desired grain. We uncover grain-dependent effects of both environment and biogeographic regions on S, with a positive regional effect of Southeast Asia at coarse grain that disappears at fine grains. We show that, globally, biodiversity cannot be attributed to purely environmental or regional drivers, since regions are environmentally distinct. Finally, we predict global maps of biodiversity at two grains, identifying areas of exceptional species turnover in China, East Africa, and North America. Our cross-scale approach unifies disparate results from previous studies regarding environmental versus biogeographic predictors of biodiversity, and enables efficient integration of heterogeneous data.


2021 ◽  
Vol 9 ◽  
Author(s):  
Helen R. P. Phillips ◽  
Erin K. Cameron ◽  
Nico Eisenhauer

For decades, scientists have known where the highest numbers of species that live aboveground are found. So, they made maps of the world showing these patterns. For most of the aboveground groups, the highest numbers of species occur in the tropics and numbers decrease toward the poles. However, until recently, we did not understand such global patterns for many organisms living in the soil. We decided to create global maps of earthworm species richness. Earthworms provide humans with many useful services, such as moving the soils and improving their quality, which can increase the amount of food that is grown. If we want to protect earthworms and the services they provide, these global maps of earthworms are important because we need to understand where they are and why they live there.


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