Productivity in Cloud Forests in the Andes

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Merry Manning
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1 Productivity in Cloud Forests in the Andes Carbon cycle measurements and model results from JULES Toby Marthews Leeds, 10th June 2010 at the Oxford University Centre for the Environment (OUCE) in association with the Andes Biodiversity and Ecosystem Research Group (ABERG) and the RAINFOR network

com Leeds, 10th June 2010 at the Oxford University Centre for the Environment

2 Cloud Forests Cloud forests (=upper montane forest =ceja de la montaña) only represent 0.26% of the world s land surface, but are a high conservation priority: If the Amazon warms by 2-4 C then will the cloud forest biome go extinct or migrate to higher elevations? Worldwide Cloud Forest distribution

26% of the world s land surface, but are a high conservation priority: If

3 Most of my work concerns a transect of forest census plots in the Kosñipata Valley in SE Peru (Wayqecha - San Pedro - Tono). I am also using a pseudo-transect Tambopata - Manaus - Caxiuanã to compare with the lowland Amazon.

4 We are using the RAINFOR network coordinated by University of Leeds

8 Kosñipata Ridge 200m 1250m 1000m 1500m 1750m 2000m 2250m 2500m 2750m 3450m 3250m 3000m

9 Kosñipata Ridge: a natural ecosystem laboratory 26.4 o C 21 o C 22.1 o C 19 o C 16.7 o C 15.3 o C 14.8o C 13.3 o C 11.9 o C 8.5 o C 9.2 o C 10.5 o C

10 1 ha plots S, W Fire PUNA PUNA Plot 1 (3391m) Plot 2 (3205m) Plot 3 (3033m) Plot 4 (2745m) Plot 2 (3205m) Plot 3 (3033m) Plot 1 (3391m) Plot 4 (2745m) Plot 5 (2540m) Plot 6 (2290m) CLOUD MONTANE RAINFORESTS Plot 5 (2540m) Plot 6 (2290m) Plot 7 (2038m) Plot 7 (2038m) Plot 8 (1855m) Plot 7 (1855m) Plot 9 (210m) Plot 10 (194m) LOWLAND RAINFORESTS CLOUD FORESTS LOW MONTANE FORESTS SUBMONTANE FORESTS N 0 1km S, W Kosñipata Valley, SE Peru Source: Dr. Roman-Cuesta (2006)

Plot 4 (2745m) Plot 5 (2540m) Plot 6 (2290m) CLOUD MONTANE RAINFORESTS Plot 5 (2540m) Plot 6 (2290m) Plot 7 (2038m) Plot 7

11 Forest-grasslands tree line, 3600 m elevation

12 Upper montane cloud forest, 3000 m elevation

13 Upper montane cloud forest, 2750 m elevation

14 Submontane forest, 1500 m elevation

15 Presumably, half a mountainside & several tree snags are busy heading along the Amazon from San Pedro to the Atlantic...

17 The Carbon Cycle of a Forest Source: Dr. Cécile Girardin

18 Above-ground biomass growth Canopy production 0.1 mm nylon mesh 0.5 m 0.5 m ~ 1 m Root production

22 Manaus lowland forest: 75 m asl GPP = 30.4 R Total = 29.3±4.7 R Aut = 19.8±4.6 R Het = 9.6±1.2 NPP Total = 10.1±1.4 NPP Ag = 7.3±1.3 NPP Bg = 2.8±0.7 NPP leaves,flowers,fruit = 3.6±0.7 NPP VOC = 0.13±0.06 R leaf = 10.0±4.0 NPP branch turnover = 1.0±1.0 R stem = 4.2±1.0 D Fine litterfall = 3.6±0.7 Predicted R soil = 12.6±2.3 Measured R soil = 12.1±1.7 R CWD = 2.5±0.3 NPP stem = 2.58±0.06 D CWD = 3.58±1.0 R roots = 5.6±2.0 R soil het. =7.1±1.1 NPP coarse roots = 0.8±0.2 NPP fine roots = 2.1±0.7 D Root = 2.8±0.7 ALL UNITS ARE t C / ha per year F doc = 0.19±0.07

23 Wayqecha cloud forest: 3025 m asl R Total = 15.7±2.0 R Aut = 9.8±1.7 R Het = 5.9±1.0 GPP estimated =16.2±2.5 GPP(canopy physiology) = 14 NPP Total = 5.2±0.7 NPP Ag = 3.6±0.5 NPP Bg = 1.6±0.4 NPP leaves,flowers,fruit =1.9±0.1 R leaf = 6.0±1.2 NPP branch turnover = 0.5±0.5 R stem = 1.1±0.2 D Fine litterfall =1.9±0.1 Predicted R soil = 9.2±1.9 Measured R soil = 11.6±0.1 R CWD = 0.6±0.2 NPP stem = 1.2±0.1 D CWD = 2.4±0.6 R roots = 3.9±1.6 R soil het. =5.3±1.1 NPP coarse roots = 0.4±0.1 NPP fine roots = 1.2±0.4 D Root = 1.6±0.4 ALL UNITS ARE t C / ha per year

24 NPP: Net Primary Productivity (NPP) in µmol CO2/m2s WAY SP TON TAM CAX MAN JULES v2.1.1 simulations with can_rad_mod=4: Solid line = 24 hr mean Broken lines = daytime & nighttime means Dotted lines = 24 hr min & max Points = Field measurements Grey band is an estimate from Clark et al. (2001, Ecol Appl) ON THE Y-AXIS 30 t C / ha per year is approx. 7.9 µmol C/m2 per sec flux Mean annual temperature in ºC Girardin et al. (in press GCB). Net primary productivity and its allocation along a tropical forest elevational transect in the Peruvian Andes. Marthews et al. (in prep). Carbon fluxes in six Amazonian and Andean forests: ecosystem productivity and carbon use efficiency.

25 GPP: Gross Primary Productivity (GPP) in µmol CO2/m2s WAY SP TON TAM CAX JULES v2.1.1 simulations with can_rad_mod=4: Solid line = 24 hr mean Broken lines = daytime & nighttime means Dotted lines = 24 hr min & max Points = Field measurements MAN Grey band is an estimate from Clark et al. (2001, Ecol Appl) and Piao et al.(2010, Ecology). ON THE Y-AXIS 30 t C / ha per year is approx. 7.9 µmol C/m2 per sec flux Mean annual temperature in ºC Girardin et al. (in press GCB). Net primary productivity and its allocation along a tropical forest elevational transect in the Peruvian Andes. Marthews et al. (in prep). Carbon fluxes in six Amazonian and Andean forests: ecosystem productivity and carbon use efficiency.

26 CUE = NPP/GPP (undefined at night when GPP=0): 0.8 JULES v2.1.1 simulations with can_rad_mod=4: Solid line = 24 hr mean Broken lines = daytime & nighttime means Dotted lines = 24 hr min & max Points = Field measurements Carbon use efficiency (CUE) WAY SP TON TAM CAX MAN Grey band is an estimate from Piao et al.(2010, Ecology) Mean annual temperature in ºC Girardin et al. (in press GCB). Net primary productivity and its allocation along a tropical forest elevational transect in the Peruvian Andes. Marthews et al. (in prep). Carbon fluxes in six Amazonian and Andean forests: ecosystem productivity and carbon use efficiency.

27 The Future: Scaling up to Regional Simulations (last slide!)

28 THANKS FOR LISTENING

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