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03:29 Institute of Physics (IOP) English 2015

Tipping point of a conifer forest ecosystem under severe drought

Drought-induced tree mortality has recently received considerable attention. Questions have arisen over the necessary intensity and duration thresholds of droughts that are sufficient to trigger rapid forest declines. The values of such tipping points leading to forest declines due to drought are presently unknown. In this study, we have evaluated the potential relationship between the level of tree growth and concurrent drought conditions with data of the tree growth-related ring width index (RWI) of the two dominant conifer species (Pinus edulis and Pinus ponderosa) in the Southwestern United States (SWUS) and the meteorological drought-related standardized precipitation evapotranspiration index (SPEI). In this effort, we determined the binned averages of RWI and the 11 month SPEI within the month of July within each bin of 30 of RWI in the range of 0–3000. We found a significant correlation between the binned averages of RWI and SPEI at the regional-scale under dryer conditions. The tipping point of forest declines to drought is predicted by the regression model as SPEItp = −1.64 and RWItp = 0, that is, persistence of the water deficit (11 month) with intensity of −1.64 leading to negligible growth for the conifer species. When climate conditions are wetter, the correlation between the binned averages of RWI and SPEI is weaker which we believe is most likely due to soil water and atmospheric moisture levels no longer being the dominant factor limiting tree growth. We also illustrate a potential application of the derived tipping point (SPEItp = −1.64) through an examination of the 2002 extreme drought event in the SWUS conifer forest regions. Distinguished differences in remote-sensing based NDVI anomalies were found between the two regions partitioned by the derived tipping point.
  • Published: 2015
  • Publisher: Institute of Physics (IOP)
  • Language: English
04:57 Institute of Physics (IOP) English 2012

Climate extremes and grassland potential productivity

The considerable interannual variability (IAV) (~5 PgC yr−1) observed in atmospheric CO2 is dominated by variability in terrestrial productivity. Among terrestrial ecosystems, grassland productivity IAV is greatest. Relationships between grassland productivity IAV and climate drivers are poorly explained by traditional multiple-regression approaches. We propose a novel method, the perfect-deficit approach, to identify climate drivers of grassland IAV from observational data. The maximum daily value of each ecological or meteorological variable for each day of the year, over the period of record, defines the 'perfect' annual curve. Deficits of these variables can be identified by comparing daily observational data for a given year against the perfect curve. Links between large deficits of ecosystem activity and extreme climate events are readily identified. We applied this approach to five grassland sites with 26 site-years of observational data. Large deficits of canopy photosynthetic capacity and evapotranspiration derived from eddy-covariance measurements, and leaf area index derived from satellite data occur together and are driven by a local-dryness index during the growing season. This new method shows great promise in using observational evidence to demonstrate how extreme climate events alter yearly dynamics of ecosystem potential productivity and exchanges with atmosphere, and shine a new light on climate–carbon feedback mechanisms.
  • Published: 2012
  • Publisher: Institute of Physics (IOP)
  • Language: English
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