The relationships between terrestrial vertebrate species richness in China’s nature reserves and environmental variables

2006 ◽  
Vol 84 (9) ◽  
pp. 1368-1374 ◽  
Author(s):  
Shuqing Zhao ◽  
Jingyun Fang ◽  
Changhui Peng ◽  
Zhiyao Tang
Keyword(s):  
Species Richness ◽  
Primary Productivity ◽  
Environmental Variables ◽  
Net Primary Productivity ◽  
Nature Reserves ◽  
Vertebrate Species ◽  
Terrestrial Vertebrate ◽  
Physiologically Based ◽  
Richness Patterns ◽  
Terrestrial Vertebrate Species

Explaining species richness patterns over broad geographic scales is a central issue of biogeography and macroecology. In this study, we took spatial autocorrelation into account and used terrestrial vertebrate species richness data from 211 nature reserves, together with climatic and topographical variables and reserve area, to explain terrestrial vertebrate species richness patterns in China and to test two climatically based hypotheses for animals. Our results demonstrated that species richness patterns of different terrestrial vertebrate taxa were predicted by the environmental variables used, in a decreasing order, as reptiles (56.5%), followed by amphibians (51.8%), mammals (42%), and birds (19%). The endothermic vertebrates (mammals and birds) were closely correlated with net primary productivity (NPP), which supports the productivity hypothesis, whereas the ectothermic vertebrates (amphibians and reptiles) were strongly associated with both water and energy variables but weakly with NPP, which supports the physiologically based ambient climate hypothesis. The differences in the dependence of endothermic and ectothermic vertebrates on productivity or ambient climate may be due in part to their different thermoregulatory mechanisms. Consistent with earlier studies, mammals were strongly and positively related to geomorphologic heterogeneity, measured by elevation range, implying that the protection of mountains may be especially important in conserving mammalian diversity.

scholarly journals Testing the Effectiveness of Environmental Variables to Explain European Terrestrial Vertebrate Species Richness across Biogeographical Scales

PLoS ONE ◽  
2015 ◽  
Vol 10 (7) ◽  
pp. e0131924 ◽  
Author(s):  
Maud Mouchet ◽  
Christian Levers ◽  
Laure Zupan ◽  
Tobias Kuemmerle ◽  
Christoph Plutzar ◽  
...  
Keyword(s):  
Species Richness ◽  
Environmental Variables ◽  
Vertebrate Species ◽  
Terrestrial Vertebrate ◽  
Terrestrial Vertebrate Species

scholarly journals Gap Analysis Project (GAP) Terrestrial Vertebrate Species Richness Maps for the Conterminous U.S.

2019 ◽  
Author(s):  
Kevin J. Gergely ◽  
Kenneth G. Boykin ◽  
Alexa J. McKerrow ◽  
Matthew J. Rubino ◽  
Nathan M. Tarr ◽  
...  
Keyword(s):  
Species Richness ◽  
Gap Analysis ◽  
Vertebrate Species ◽  
Terrestrial Vertebrate ◽  
Terrestrial Vertebrate Species

scholarly journals Shortfalls and opportunities in terrestrial vertebrate species discovery

2020 ◽  
Author(s):  
Mario R. Moura ◽  
Walter Jetz
Keyword(s):  
Sustainable Management ◽  
Vertebrate Species ◽  
Species Discovery ◽  
Terrestrial Vertebrate ◽  
Policy Goals ◽  
Discovery Potential ◽  
Living Species ◽  
Automated Sensors ◽  
Species Descriptions ◽  
Terrestrial Vertebrate Species

AbstractMeter-resolution imagery of our world and myriad biodiversity records collected through citizen scientists and automated sensors belie the fact that much of the planet’s biodiversity remains undiscovered. Conservative estimates suggest only 13 to 18% of all living species may be known at this point 1–4, although this number could be as low as 1.5% 5. This biodiversity shortfall 6,7 strongly impedes the sustainable management of our planet’s resources, as the potential ecological and economic relevance of undiscovered species remains unrecognized 8. Here we use model-based predictions of terrestrial vertebrate species discovery to estimate future taxonomic and geographic discovery opportunities. Our model identifies distinct taxonomic and geographic unevenness in future discovery potential, with greatest opportunities for amphibians and reptiles and for Neotropical and IndoMalayan forests. Brazil, Indonesia, Madagascar, and Colombia emerge as holding greatest discovery opportunities, with a quarter of future species descriptions expected there. These findings highlight the significance of international support for taxonomic initiatives and the potential of quantitative models to aid the discovery of species before their functions are lost in ignorance 8. As nations draw up new policy goals under the post-2020 global biodiversity framework, a better understanding of the magnitude and geography of this known unknown is critical to inform goals and priorities 9 and to minimize future discoveries lost to extinction10.

scholarly journals Worldwide patterns in species richness of falconiformes: analytical null models, geometric constraints, and the mid-domain effect

2004 ◽  
Vol 64 (2) ◽  
pp. 209-308
Author(s):  
T. F. L.V. B. Rangel ◽  
J. A. F. Diniz-filho
Keyword(s):  
Species Richness ◽  
Primary Productivity ◽  
Net Primary Productivity ◽  
Empirical Support ◽  
Null Models ◽  
Geometric Constraints ◽  
Global Level ◽  
Spatial Gradients ◽  
Available Energy ◽  
Surrogate Variable

Recently, the hypothesis that the geographic distribution of species could be influenced by the shape of the domain edges, the so-called Mid-Domain Effect (MDE), has been included as one of the five credible hypotheses for explaining spatial gradients in species richness, despite all the unsuccessful current attempts to prove empirically the validity of MDE. We used data on spatial worldwide distributions of Falconiformes to evaluate the validity of MDE assumptions, incorporated into two different sorts of null models at a global level and separately across five domains/landmasses. Species richness values predicted by the null models of the MDE and those values predicted by Net Primary Productivity, a surrogate variable expressing the effect of available energy, were compared in order to evaluate which hypothesis better predicts the observed values. Our tests showed that MDE continues to lack empirical support, regardless of its current acceptability, and so, does not deserve to be classified as one possible explanation of species richness gradients.

Net primary productivity and seasonality of temperature and precipitation are predictors of the species richness of the Damselflies in the Amazon

2019 ◽  
Vol 35 ◽  
pp. 45-53 ◽  
Author(s):  
Leandro Schlemmer Brasil ◽  
Divino Vicente Silverio ◽  
Helena Soares Ramos Cabette ◽  
Joana Darc Batista ◽  
Thiago Bernardi Vieira ◽  
...  
Keyword(s):  
Species Richness ◽  
Primary Productivity ◽  
Net Primary Productivity ◽  
Temperature And Precipitation

scholarly journals Testing Seven Hypotheses to Determine What Explains the Current Planthopper (Fulgoridae) Geographical and Species Richness Patterns in China

Insects ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 892
Author(s):  
Zheng-Xue Zhao ◽  
Lin Yang ◽  
Jian-Kun Long ◽  
Zhi-Min Chang ◽  
Zheng-Xiang Zhou ◽  
...  
Keyword(s):  
Species Richness ◽  
Large Scale ◽  
Net Primary Productivity ◽  
Model Averaging ◽  
Ordinary Least Squares ◽  
Environmental Variable ◽  
Vital Role ◽  
Mean Annual Temperature ◽  
Spatial Error ◽  
Richness Patterns

Although many hypotheses have been proposed to understand the mechanisms underlying large-scale richness patterns, the environmental determinants are still poorly understood, particularly in insects. Here, we tested the relative contributions of seven hypotheses previously proposed to explain planthopper richness patterns in China. The richness patterns were visualized at a 1° × 1° grid size, using 14,722 distribution records for 1335 planthoppers. We used ordinary least squares and spatial error simultaneous autoregressive models to examine the relationships between richness and single environmental variables and employed model averaging to assess the environmental variable relative roles. Species richness was unevenly distributed, with high species numbers occurring in the central and southern mountainous areas. The mean annual temperature change since the Last Glacial Maximum was the most important factor for richness patterns, followed by mean annual temperature and net primary productivity. Therefore, historical climate stability, ambient energy, and productivity hypotheses were supported strongly, but orogenic processes and geological isolation may also play a vital role.

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