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Dag O. Hessen and Vigdis Vandvik

CO 2 , corresponding to temperature increases of 1.5°–4.5°C ( ). While the higher end of these estimates is becoming increasingly unlikely ( Hausfather and Peters 2020 ), a warming in the range of 2.2°–2.7°C by 2100 may be expected ( IPCC 2022 ). The prospects for humanity, even by the most optimistic among these scenarios, are dramatic, as evidenced by the harmful and costly effects already apparent from the current CO 2 levels and associated warming of

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Paul C. Fiedler, Roy Mendelssohn, Daniel M. Palacios, and Steven J. Bograd

, as a baseline for seasonal and interannual cyclic variations, means that these changes may have effects disproportionate to their relative amplitude. Rice (2001) suggested that the effect of environmental variations on ecosystem dynamics depends on their temporal scale relative to the generation time of important species such as top predators. Our focus in this paper is to describe these longer-term variations and to discuss implications for ecosystem productivity and processes. 2. Data and

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Tristan Ballard, Richard Seager, Jason E. Smerdon, Benjamin I. Cook, Andrea J. Ray, Balaji Rajagopalan, Yochanan Kushnir, Jennifer Nakamura, and Naomi Henderson

., 13 pp . Gleason , R. A. , N. H. Euliss , B. A. Tangen , and M. K. Laubhan , 2011 : USDA conservation program and practice effects on wetland ecosystem services in the Prairie Pothole Region . Ecol. Appl. , 21 , S65 – S81 , doi: 10.1890/09-0216.1 . Harris , I. , P. D. Jones , T. J. Osborn , and D. H. Lister , 2014 : Updated high-resolution grids of monthly climatic observations—The CRU TS3.10 . Int. J. Climatol. , 34 , 623 – 642 , doi: 10.1002/joc.3711 . Johnson , R

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Shizuo Suzuki, Masayuki Yokozawa, Kazuyuki Inubushi, Toshihiko Hara, Michitoshi Kimura, Shoichi Tsuga, Yasuhiro Tako, and Yuji Nakamura

from seconds to years, by measuring the covariance between the fluctuations in vertical wind velocity and CO 2 mixing ratio ( Baldocchi 2003 ). Quantifying the temporal variation in ecosystem CO 2 exchange rates at one site helps to clarify the effects of environmental variation on ecosystem physiological processes. Data gathered during fluctuations in environmental conditions are useful to develop physiological response curves for whole-ecosystem response to changes in temperature, light, and so

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Ayman Suleiman, Jawad Al-Bakri, Mohammad Duqqah, and Rich Crago

and is home to a wide range of highly adapted organisms. Sudanian Penetration : provides unique ecosystems, with altitudes varying from the lowest elevation on earth at 400 m below the sea level (at the Dead Sea in the Rift Valley) up to 1200 m in the south. This region is characterized by very hot summers and warm winters, with a mean annual rainfall of 50 mm or less. Vegetation is dominated by Acacia sp. in the low-altitude region and scattered shrubs in the high-altitude region. Six

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Sönke Zaehle, Chris D. Jones, Benjamin Houlton, Jean-Francois Lamarque, and Eddy Robertson

ecosystem models accounting for all relevant C–N interactions. In the following, we discuss the implications of these assumptions. a. Methodological limitations Lacking a framework to account for potential changes in tissue C:N ratios, we did not include such effects. Foliar C:N ratios have been reported to increase with elevated CO 2 ( Ainsworth and Long 2005 ), while they decrease with N additions ( Hyvönen et al. 2007 ). However, the C:N of the entire vegetation were largely unaffected in free

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Yang Hong, Thomas Connor, Huan Luo, Xiaoxing Bian, Zhaogang Duan, Zhuo Tang, and Jindong Zhang

relative lack of research on snow leopards and their alpine ecosystem. For example, research on livestock grazing effects has been concentrated in low-elevation areas within giant panda habitat ( Wang et al. 2019 ), while there has been no research on the effects of livestock grazing on the ecology and conservation of snow leopards in Wolong Nature Reserve. Fig . 1. Map and location of Wolong Nature Reserve in Sichuan. Livestock and snow leopard locations in LGDAs and HGDAs are also depicted. Snow

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S. C. Chapman, E. J. Murphy, D. A. Stainforth, and N. W. Watkins

, summers and winters is an increasing research focus ( Felton and Smith 2017 ). A series of recent studies have examined the impacts of these climatic extremes, in the sense of atypical extended warmer and colder periods, on individual plant and animal species, communities, and ecosystems and on agricultural systems. The temporal structure of temperature variability is important in determining the magnitude of any ecological effects. Experimental analyses showed that changes in temporal clustering of

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Peiyun Zhu, Susan J. Cheng, Zachary Butterfield, Gretchen Keppel-Aleks, and Allison L. Steiner

the global diffuse fertilization effects from clouds. Spatial resolution may also influence other factors that affect the relationship between COT and ecosystem productivity at the spatial and temporal scales implemented in this study. For example, a 1° × 1° area will have wide ranges of water and nutrient availability in soils, which are important environmental drivers of productivity that we did not explore in the study. Clouds also exhibit a strong variability across these spatial scales, with

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Aiwen Lin, Hongji Zhu, Lunche Wang, Wei Gong, and Ling Zou

). Especially in the arid region of northwestern China, the significant changes in climate may lead to the changes in vegetation growth ( Zhao et al. 2011 ). In southern China, the subtropical forests are threatened by their lack of resilience against long-term climate change ( Zhou et al. 2013 ). To evaluate the effects of climate change on terrestrial ecosystems, the gross primary production (GPP) and the net primary production (NPP) are widely used in literature ( Fang et al. 2013 ). For example, one

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