Trends in Terrestrial Carbon Sinks Driven by Hydroclimatic Change since 1948: Data-Driven Analysis using FLUXNET Trends in Terrestrial Carbon Sinks Driven.

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Trends in Terrestrial Carbon Sinks Driven by Hydroclimatic Change since 1948: Data-Driven Analysis using FLUXNET Trends in Terrestrial Carbon Sinks Driven by Hydroclimatic Change since 1948: Data-Driven Analysis using FLUXNET Christopher Schwalm, Christopher Williams, Kevin Schaefer, Kusum Naithani, Jingfeng Xiao Ameriflux Science Meeting & 3rd NACP All-Investigators Meeting 2011 January 31 – February 4, New Orleans, LA

We ask –What are the carbon consequences of hydrologic change? We merge –Global monitoring network (FLUXNET) –LUH time-varying land cover (IPCC AR5) –NCEP/NCAR Reanalysis We derive –Monthly time series (1948 – 2009) –1° latitude/longitude resolution –Observationally-based estimates of carbon flux solely attributable to hydrologic change Outline

Global monitoring network FLUXNET: Network of regional networks Eddy covariance method: temporally dense in situ CO 2 exchange including gross primary production and ecosystem respiration Ancillary data: soil moisture, temperature, latent heat flux, LAI, etc.

Mapping points to pixels Evaporative Fraction Carbon Flux Extract relationship between hydrologic change and carbon flux Aggregate FLUXNET sites by IGBP land cover class Calculate sensitivity: change in carbon flux to a unit forcing in evaporative fraction (z-score) Sensitivity: g C m -2 month -1 σ -1 Map sensitivities to globe using 1) LUH [gridded land cover class] 2) NCEP/NCAR Reanalysis [gridded EF] Schwalm et al. (2010) Global Change Biology

Spatial scaling: LUH land cover annual snapshots of land cover from Land Use Harmonization (LUH) Crosswalk: LUH → IGBP IGBP maps 18 IGBP land cover classes by pixel FLUXNET sensitivities Vegetated classes – observed Non-vegetated classes – set to zero + Pixel sensitivity [weighted average] = Units: g C m -2 month -1 σ -1 “Points to pixels”

Temporal scaling: NCEP reanalysis EF (σ) NEP sensitivity (g C m -2 mon -1 σ -1 ) δ NEP (g C m -2 mon -1 ) Example – Europe in June 1998

Global time series Sink ( ) = +2.8 Canadell et al. (2007) PNAS

Global trends Trend line (p > 0.44) Visually the same as zero reference line Grey envelope is ±2σ

Continental trends - δ NEP significant not significant More uptake Less uptake

Continental trends – δ P & δ R

Cumulative trend T NEP [g C m -2 62yr -1 ] outgassinguptake

Differential response: Case study Highest density of FLUXNET sites

Geography of hydrologic change

CRU vs. Willmott precipitation

Relating trend to background flux FLUXNET + LUH + NCEP δ NEP δPδP δRδR NEP P R MODIS + CARBONTRACKER Does the trend overpower the mean? What spatial features are present?

Net effect on gross fluxes |δ P | > |δ R | - color contrast Median ratio 40% larger for |T P /P| than for |T R /R| More clusters with |δ P | > P Fewer clusters with |δ R | > R Low productivity areas

Net effect on source/sink Blue: source to sink [4%] Red: sink to source [20%] Green: enhanced uptake [18%] Yellow: enhanced outgassing [12%]

Summary Observationally-based estimates of carbon cycling solely attributable to hydroclimatic variability Range in del equals or exceeds terrestrial carbon sink magnitude or gross fluxes. Hydroclimatic variability has acted to flip sources to sinks and vice versa (25%) over the 62-yr record → “key player”

Net effect on photosynthesis

Net effect on respiration

Net effect on gross fluxes Less assimilation Trend < 0 More assimilation Trend > 0