2017
DOI: 10.1111/jbi.13156
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What makes the Sino‐Himalayan mountains the major diversity hotspots for pheasants?

Abstract: Aim The Sino‐Himalayas have higher species richness than adjacent regions, making them a global biodiversity hotspot. Various mechanisms, including ecological constraints, energetic constraints, diversification rate (DivRate) variation, time‐for‐speciation effect and multiple colonizations, have been posited to explain this pattern. We used pheasants (Aves: Phasianidae) as a model group to test these hypotheses and to understand the ecological and evolutionary processes that have generated the extraordinary di… Show more

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Cited by 59 publications
(53 citation statements)
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“…However, this discrepancy might have been caused by methodological issues. The estimate of the same split by Stein et al (2015) based on fossil calibration was 3 Ma, while that of Cai et al (2018) again based on fossil calibration was more in line with our result. Also the divergence among the strauchi-vlangalii and the torquatus group estimated by Liu et al (2010) is in line with our temporal framework.…”
Section: Discussionsupporting
confidence: 89%
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“…However, this discrepancy might have been caused by methodological issues. The estimate of the same split by Stein et al (2015) based on fossil calibration was 3 Ma, while that of Cai et al (2018) again based on fossil calibration was more in line with our result. Also the divergence among the strauchi-vlangalii and the torquatus group estimated by Liu et al (2010) is in line with our temporal framework.…”
Section: Discussionsupporting
confidence: 89%
“…The common pheasant seems to have originated at the eastern edge of the Qinghai-Tibetan plateau or the adjacent south-west or central Chinese mountains. The Sino-Himalayan region is a diversity hotspot and a diversification center of pheasants in general (Cai et al , 2018). While the avifaunal assemblages of the Himalayas are generally the result of immigration (Johansson et al , 2007; Päckert et al , 2012; Price et al , 2014), the south-west and central Chinese Mountains were revealed as a species-pump in other studies (Päckert et al , 2015; Liu et al , 2016).…”
Section: Discussionmentioning
confidence: 99%
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“…Specifically, energy is the basis of survival for all kinds of living beings, and net primary productivity (NPP) is an appropriate index for representing the energy produced by vegetation. Habitats with high productivity have more available sources and sustain more individual populations, increasing the survival probability of species [43][44][45][46][47]. Habitat connectivity is crucial for maintaining ecological processes in good condition.…”
Section: Establishment Of a Biodiversity Constraint Indicatormentioning
confidence: 99%
“…Biodiversity hotspot analysis A broad definition of 'biodiversity hotspots'refers to any area or region with exceptionally high biodiversity at the ecosystem, species and genetic levels [51]. Spatial autocorrelation analysis can be used to identify biodiversity hotspots [43,66]. The * G i index is the most commonly used coefficient for spatial autocorrelation analysis.…”
Section: Habitat Quality Assessment By the Invest Modelmentioning
confidence: 99%