Enhanced precipitation variability decreases grass- and increases shrub-productivity

Gherardi, Laureano A.; Sala, Osvaldo E.

doi:10.1073/pnas.1506433112

Cited by 233 publications

(220 citation statements)

References 35 publications

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“…In temperate grasslands, increasing intervals between rains, or increasing interannual variability, without reducing total rainfall, reduced herbaceous productivity (81) while at the same time increasing shrub productivity (82). Drought-Net is a recently established CDE coordinating water manipulation field experiments across ecosystem types.…”

Section: Experimentally Manipulating Global Change Factorsmentioning

confidence: 99%

Global change and terrestrial plant community dynamics

Franklin

Serra‐Diaz

Syphard

et al. 2016

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

317

225

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This contribution is part of a special series of Inaugural Articles by members of the National Academy of Sciences elected in 2014.Contributed by Janet Franklin, February 2, 2016 (sent for review October 8, 2015; reviewed by Gregory P. Asner, Monica G. Turner, and Peter M. Vitousek)Anthropogenic drivers of global change include rising atmospheric concentrations of carbon dioxide and other greenhouse gasses and resulting changes in the climate, as well as nitrogen deposition, biotic invasions, altered disturbance regimes, and land-use change. Predicting the effects of global change on terrestrial plant communities is crucial because of the ecosystem services vegetation provides, from climate regulation to forest products. In this paper, we present a framework for detecting vegetation changes and attributing them to global change drivers that incorporates multiple lines of evidence from spatially extensive monitoring networks, distributed experiments, remotely sensed data, and historical records. Based on a literature review, we summarize observed changes and then describe modeling tools that can forecast the impacts of multiple drivers on plant communities in an era of rapid change. Observed responses to changes in temperature, water, nutrients, land use, and disturbance show strong sensitivity of ecosystem productivity and plant population dynamics to water balance and long-lasting effects of disturbance on plant community dynamics. Persistent effects of land-use change and human-altered fire regimes on vegetation can overshadow or interact with climate change impacts. Models forecasting plant community responses to global change incorporate shifting ecological niches, population dynamics, species interactions, spatially explicit disturbance, ecosystem processes, and plant functional responses. Monitoring, experiments, and models evaluating multiple change drivers are needed to detect and predict vegetation changes in response to 21st century global change.climate change | drought | forests | global change | land-use change T errestrial plant communities include forests, woodlands, shrublands, and grasslands; they support economic activities including forestry and grazing and provide other ecosystem services (1) such as carbon sequestration and water delivery. Plant communities play a key role in global biogeochemical cycles of carbon, oxygen, water, and nitrogen, with feedbacks to the oceans, atmosphere, and climate. The distribution of animals on land is often influenced by the distribution of vegetation, and therefore, plant community dynamics affect biodiversity. Changes in the Earth's vegetation in response to climate change, and associated faunal changes, may have played a role in the evolution of the human lineage (2, 3). Thus, human populations have a vested interest in understanding rapid global change effects on terrestrial plant communities.Anthropogenic drivers of global change include rising atmospheric concentrations of CO 2 and other greenhouse gasses and associated changes in the climate, as well...

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Section: Experimentally Manipulating Global Change Factorsmentioning

confidence: 99%

Global change and terrestrial plant community dynamics

Franklin

Serra‐Diaz

Syphard

et al. 2016

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

317

225

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“…While WA is rather dominated by grass/crop type vegetation, SWA is strongly dominated by savanna and shrub type vegetation. Thus, rainfall variability may have an indirect effect on vegetation composition with higher CVP promoting shrub type vegetation whereas lower CVP favours grass type vegetation (Gherardi and Sala, 2015). 10 We note that rainfall from previous years may well contribute to explaining the patterns of β we have observed.…”

Section: Vegetation Type Specific Response To Rainfallmentioning

confidence: 78%

Dryland vegetation functional response to altered rainfall amounts and variability derived from satellite time series data

Ratzmann

Gangkofner²,

Tietjen

et al. 2016

Preprint

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Abstract. Vegetation net productivity is a key variable in ecosystem functioning. Understanding how its functional response to rainfall in drylands is affected by altered rainfall amounts and variability is therefore vitally important to understand consequences of climatic change for those water-limited ecosystems. Here, we show how this functional response is affected by below and above 30-year-average rainfall conditions in two arid to semi arid subtropical regions in West and South West during dry periods for mean annual precipitation < 500 mm and spatially more variable, the responses to climate for West Africa are generally low and spatially less dynamic. Those patterns follow differences in interannual rainfall amount variability (higher in South West Africa). Regional peaks of vegetation response to rainfall along mean annual precipitation are found at precipitation values with similar interannual variability in growing season length. Vegetation type (MODIS MCD12C) specific response to rainfall mostly follows observed responses along rainfall gradients leading to region specific 25 responses for each vegetation type. We conclude that higher rainfall amount variability enhances regional-scale vegetation response to rainfall plasticity and thus dryland ecosystem resilience to dry periods. Those results apply irrespective of vegetation type and thus evidence the fundamental role of rainfall variability in ecosystem functioning. Presented results moreover imply that the Sahel region (West Africa) although currently recovering from drought might be highly susceptible to future dry periods. 30

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Section: Vegetation Type-specific Response To Rainfallmentioning

confidence: 99%

Dryland Vegetation Functional Response to Altered Rainfall Amounts and Variability Derived from Satellite Time Series Data

Ratzmann

Gangkofner²,

Tietjen

et al. 2016

Remote Sensing

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Vegetation productivity is an essential variable in ecosystem functioning. Vegetation dynamics of dryland ecosystems are most strongly determined by water availability and consequently by rainfall and there is a need to better understand how water limited ecosystems respond to altered rainfall amounts and variability. This response is partly determined by the vegetation functional response to rainfall (β) approximated by the unit change in annual vegetation productivity per unit change in annual rainfall. Here, we show how this functional response from 1983 to 2011 is affected by below and above average rainfall in two arid to semi-arid subtropical regions in West Africa (WA) and South West Africa (SWA) differing in interannual variability of annual rainfall (higher in SWA, lower in WA). We used a novel approach, shifting linear regression models (SLRs), to estimate gridded time series of β. The SLRs ingest annual satellite based rainfall as the explanatory variable and annual satellite-derived vegetation productivity proxies (NDVI) as the response variable. Gridded β values form unimodal curves along gradients of mean annual precipitation in both regions. β is higher in SWA during periods of below average rainfall (compared to above average) for mean annual precipitation <600 mm. In WA, β is hardly affected by above or below average rainfall conditions. Results suggest that this higher β variability in SWA is related to the higher rainfall variability in this region. Vegetation type-specific β follows observed responses for each region along rainfall gradients leading to region-specific responses for each vegetation type. We conclude that higher interannual rainfall variability might favour a more dynamic vegetation response to rainfall. This in turn may enhance the capability of vegetation productivity of arid and semi-arid regions to better cope with periods of below average rainfall conditions.

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Enhanced precipitation variability decreases grass- and increases shrub-productivity

Cited by 233 publications

References 35 publications

Global change and terrestrial plant community dynamics

Global change and terrestrial plant community dynamics

Dryland vegetation functional response to altered rainfall amounts and variability derived from satellite time series data

Dryland Vegetation Functional Response to Altered Rainfall Amounts and Variability Derived from Satellite Time Series Data

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