Impacts of increased variability in precipitation and air temperature on net primary productivity of the Tibetan Plateau: a modeling analysis

Ye, Jian‐Sheng; Reynolds, James F.; Sun, Guojun; Li, Fengmin

doi:10.1007/s10584-013-0719-2

Cited by 31 publications

(30 citation statements)

References 32 publications

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“…Satellite data show increases in the normalized difference vegetation index (NDVI, a proxy for ANPP) with increasing precipitation over a 40‐yr period (1969–2008) across the Tibetan Plateau (Ye et al. ). Change detection studies using satellite imagery also demonstrate that the area of alpine meadows has decreased from 1967 to 2013 (Wang et al.…”

Section: Introductionmentioning

confidence: 99%

Permafrost and drought regulate vulnerability of Tibetan Plateau grasslands to warming

et al. 2018

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The Tibetan Plateau has the largest expanse of high‐elevation permafrost in the world, and it is experiencing climate warming that may jeopardize the functioning of its alpine ecosystems. Many studies have focused on the effects of climate warming on vegetation production and diversity on the Plateau, but their disparate results have hindered a comprehensive, regional understanding. From a synthesis of twelve warming experiments across the Plateau, we found that warming increased aboveground net primary production (ANPP) and vegetation height at sites with permafrost, but ANPP decreased with warming at non‐permafrost sites. Aboveground net primary production responded more negatively to warming under drier conditions, due to both annual drought conditions and warming‐induced soil moisture loss. Decreases in species diversity with warming were also larger at sites with permafrost. These results support the emerging understanding that water plays a central role in the functioning of cold environments and suggest that as ecosystems cross a threshold from permafrost to non‐permafrost systems, ANPP will decrease across a greater proportion of the Tibetan Plateau. This study also highlights the future convergence of challenges from permafrost degradation and grassland desertification, requiring new collaborations among these currently distinct research and stakeholder groups.

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Section: Introductionmentioning

confidence: 99%

Permafrost and drought regulate vulnerability of Tibetan Plateau grasslands to warming

et al. 2018

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“…A few short-term experiments focused on the effect of intra-annual precipitation variance and reported contrasting results, with null or positive effects in arid systems and negative effects in mesic systems (11)(12)(13)(14). A modeling exercise found that increased interannual precipitation variability and temperature in the Tibetan Plateau led to productivity reduction in grasslands (15). Therefore, long-term manipulative experiments are needed to understand ecosystem responses to changes in resource amount and variability (16) at multiyear time scales.…”

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confidence: 99%

Enhanced precipitation variability decreases grass- and increases shrub-productivity

Gherardi

Sala

2015

Proc. Natl. Acad. Sci. U.S.A.

238

191

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Although projections of precipitation change indicate increases in variability, most studies of impacts of climate change on ecosystems focused on effects of changes in amount of precipitation, overlooking precipitation variability effects, especially at the interannual scale. Here, we present results from a 6-y field experiment, where we applied sequences of wet and dry years, increasing interannual precipitation coefficient of variation while maintaining a precipitation amount constant. Increased precipitation variability significantly reduced ecosystem primary production. Dominant plantfunctional types showed opposite responses: perennial-grass productivity decreased by 81%, whereas shrub productivity increased by 67%. This pattern was explained by different nonlinear responses to precipitation. Grass productivity presented a saturating response to precipitation where dry years had a larger negative effect than the positive effects of wet years. In contrast, shrubs showed an increasing response to precipitation that resulted in an increase in average productivity with increasing precipitation variability. In addition, the effects of precipitation variation increased through time. We argue that the differential responses of grasses and shrubs to precipitation variability and the amplification of this phenomenon through time result from contrasting root distributions of grasses and shrubs and competitive interactions among plant types, confirmed by structural equation analysis. Under drought conditions, grasses reduce their abundance and their ability to absorb water that then is transferred to deep soil layers that are exclusively explored by shrubs. Our work addresses an understudied dimension of climate change that might lead to widespread shrub encroachment reducing the provisioning of ecosystem services to society.C limate-change simulations project increases in precipitation variability as a result of global warming (1-3). The frequency of large precipitation events is expected to increase (3, 4), even in regions where precipitation will decrease (5). Similarly, the occurrence of wet days will decrease, resulting in a highly variable climate with enhanced probabilities of drought and heavy rainfall (5). Precipitation change will occur at intra-, interannual, and decadal scales. Mechanisms explaining such changes differ among temporal scales. At short-time scales, high precipitation variation results from the increased water-holding capacity of a warmer atmosphere that yields large rainfall events interspaced with droughts (6). At the interannual and decadal scales, climate change results in enhanced precipitation variability resulting from changes in atmospheric circulation that affect multiyear rainfall patterns (7).Although precipitation variability changes are part of the public narrative (8) and motivated a special Intergovernmental Panel on Climate Change (IPCC) report on extreme events (9), our understanding of the effect of climate variability on the carbon cycle in grasslands is still weak (10). A...

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“…In general, higher IAV connotes fewer, but larger, rainfall events that lead to larger fluctuations in soil water content. In another modeling study on the TP, Ye et al (2013) found that increasing IAV for both precipitation and temperature increased the IAV of NPP and were able to identify potential ecosystem thresholds of tolerance. In another modeling study on the TP, Ye et al (2013) found that increasing IAV for both precipitation and temperature increased the IAV of NPP and were able to identify potential ecosystem thresholds of tolerance.…”

Section: Discussionmentioning

confidence: 99%

“…Generic values for all parameters are provided, but site-specific ones can be supplied by the user (see Ye et al [2013] for details of parameterization for the TP). This model requires site characteristics (soil type, soil depth, dominant vegetation, elevation, etc.…”

Section: Description Of Biome-bgcmentioning

confidence: 99%

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A mechanistic–bioclimatic modeling analysis of the potential impact of climate change on biomes of the Tibetan Plateau

Reynolds

2014

Ecology

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The Tibetan Plateau (TP) is experiencing high rates of climatic change. We present a novel combined mechanistic-bioclimatic modeling approach to determine how changes in precipitation and temperature on the TP may impact net primary production (NPP) in four major biomes (forest, shrub, grass, desert) and if there exists a maximum rain use efficiency (RUE(MAX)) that represents Huxman et al.'s "boundary that constrain[s] site-level productivity and efficiency." We used a daily mechanistic ecosystem model to generate 40-yr outputs using observed climatic data for scenarios of decreased precipitation (25-100%); increased air temperature (1 degrees - 6 degrees C); simultaneous changes in both precipitation (+/- 50%, +/- 25%) and air temperature (+1 to +6 degrees C) and increased interannual variability (IAV) of precipitation (+1 sigma to +3 sigma, with fixed means, where sigma is SD). We fitted model output from these scenarios to Huxman et al.'s RUE(MAX) bioclimatic model, NPP = alpha + RUE x PPT (where alpha is the intercept, RUE is rain use efficiency, and PPT is annual precipitation). Based on these analyses, we conclude that there is strong support (when not explicit, then trend-wise) for Huxman et al.'s assertion that biomes converge to a common RUE(MAX) during the driest years at a site, thus representing the boundary for highest rain use efficiency; the interactive effects of simultaneously decreasing precipitation and increasing temperature on NPP for the TP is smaller than might be expected from additive, single-factor changes in these drivers; and that increasing IAV of precipitation may ultimately have a larger impact on biomes of the Tibetan Plateau than changing amounts of rainfall and air temperature alone.

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Impacts of increased variability in precipitation and air temperature on net primary productivity of the Tibetan Plateau: a modeling analysis

Cited by 31 publications

References 32 publications

Permafrost and drought regulate vulnerability of Tibetan Plateau grasslands to warming

Permafrost and drought regulate vulnerability of Tibetan Plateau grasslands to warming

Enhanced precipitation variability decreases grass- and increases shrub-productivity

A mechanistic–bioclimatic modeling analysis of the potential impact of climate change on biomes of the Tibetan Plateau

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