Faculty Opinions recommendation of Isolation by instability: Historical climate change shapes population structure and genomic divergence of treefrogs in the Neotropical Cerrado savanna.

Author(s):  
Ian Wang
2019 ◽  
Vol 28 (7) ◽  
pp. 1748-1764 ◽  
Author(s):  
Mariana M. Vasconcellos ◽  
Guarino R. Colli ◽  
Jesse N. Weber ◽  
Edgardo M. Ortiz ◽  
Miguel T. Rodrigues ◽  
...  

2015 ◽  
Vol 29 (1) ◽  
pp. 93-105 ◽  
Author(s):  
Bo Han ◽  
Shihua Lü ◽  
Yanhong Gao ◽  
Yinhuan Ao ◽  
Ruiqing Li

2017 ◽  
Vol 114 (24) ◽  
pp. 6322-6327 ◽  
Author(s):  
Christine V. Hawkes ◽  
Bonnie G. Waring ◽  
Jennifer D. Rocca ◽  
Stephanie N. Kivlin

Ecosystem carbon losses from soil microbial respiration are a key component of global carbon cycling, resulting in the transfer of 40–70 Pg carbon from soil to the atmosphere each year. Because these microbial processes can feed back to climate change, understanding respiration responses to environmental factors is necessary for improved projections. We focus on respiration responses to soil moisture, which remain unresolved in ecosystem models. A common assumption of large-scale models is that soil microorganisms respond to moisture in the same way, regardless of location or climate. Here, we show that soil respiration is constrained by historical climate. We find that historical rainfall controls both the moisture dependence and sensitivity of respiration. Moisture sensitivity, defined as the slope of respiration vs. moisture, increased fourfold across a 480-mm rainfall gradient, resulting in twofold greater carbon loss on average in historically wetter soils compared with historically drier soils. The respiration–moisture relationship was resistant to environmental change in field common gardens and field rainfall manipulations, supporting a persistent effect of historical climate on microbial respiration. Based on these results, predicting future carbon cycling with climate change will require an understanding of the spatial variation and temporal lags in microbial responses created by historical rainfall.


2021 ◽  
Vol 93 ◽  
pp. 102135
Author(s):  
H.P. Hong ◽  
Q. Tang ◽  
S.C. Yang ◽  
X.Z. Cui ◽  
A.J. Cannon ◽  
...  

2018 ◽  
Vol 13 (1) ◽  
pp. 47-58 ◽  
Author(s):  
Dingrong Wu ◽  
Peijuan Wang ◽  
Chaoyang Jiang ◽  
Jianying Yang ◽  
Zhiguo Huo ◽  
...  

2012 ◽  
Vol 109 (32) ◽  
pp. 12911-12915 ◽  
Author(s):  
T. Wei ◽  
S. Yang ◽  
J. C. Moore ◽  
P. Shi ◽  
X. Cui ◽  
...  

2019 ◽  
Vol 12 (5) ◽  
pp. 791-803 ◽  
Author(s):  
Zhiheng Wang ◽  
Yaoqi Li ◽  
Xiangyan Su ◽  
Shengli Tao ◽  
Xiao Feng ◽  
...  

Abstract Aims Plant height is a key functional trait related to aboveground biomass, leaf photosynthesis and plant fitness. However, large-scale geographical patterns in community-average plant height (CAPH) of woody species and drivers of these patterns across different life forms remain hotly debated. Moreover, whether CAPH could be used as a predictor of ecosystem primary productivity is unknown. Methods We compiled mature height and distributions of 11 422 woody species in eastern Eurasia, and estimated geographic patterns in CAPH for different taxonomic groups and life forms. Then we evaluated the effects of environmental (including current climate and historical climate change since the Last Glacial Maximum (LGM)) and evolutionary factors on CAPH. Lastly, we compared the predictive power of CAPH on primary productivity with that of LiDAR-derived canopy-height data from a global survey. Important Findings Geographic patterns of CAPH and their drivers differed among taxonomic groups and life forms. The strongest predictor for CAPH of all woody species combined, angiosperms, all dicots and deciduous dicots was actual evapotranspiration, while temperature was the strongest predictor for CAPH of monocots and tree, shrub and evergreen dicots, and water availability for gymnosperms. Historical climate change since the LGM had only weak effects on CAPH. No phylogenetic signal was detected in family-wise average height, which was also unrelated to the tested environmental factors. Finally, we found a strong correlation between CAPH and ecosystem primary productivity. Primary productivity showed a weaker relationship with CAPH of the tallest species within a grid cell and no relationship with LiDAR-derived canopy height reported in the global survey. Our findings suggest that current climate rather than historical climate change and evolutionary history determine the geographical patterns in CAPH. However, the relative effects of climatic factors representing environmental energy and water availability on spatial variations of CAPH vary among plant life forms. Moreover, our results also suggest that CAPH can be used as a good predictor of ecosystem primary productivity.


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