This study examined the spatial and temporal variability of soil N2O and CH4 fluxes along a degradation gradient in a palm swamp peat forest in the Peruvian Amazon. The researchers measured fluxes monthly for 3 years at intact, medium degradation, and high degradation sites. At the microscale, N2O and CH4 fluxes varied between hummocks and hollows and between live and cut palm trees depending on the degradation level. At the macroscale, annual N2O fluxes were similar across sites but annual CH4 fluxes increased with precipitation. Water table level, temperature, and soil nitrification rates influenced the fluxes. While degradation altered microscale emissions, site-scale emissions were homogeneous. Climate change may increase CH4

1. Kristell Hergoualc’h, N Dezzeo, LV Verchot, C Martius, J
van Lent, J Del Aguila Pasquel, M Lopez
Spatial and temporal variability of soil N2O
and CH4 fluxes along a degradation
gradient in a palm swamp peat forest in the
Peruvian Amazon
13th International Symposium on Biogeochemistry
of Wetlands, 24th March 2021

2. Peruvian peatlands
 Key contributor tropical peatlands
Gumbricht et al (201
 Amazonian peatlands mainly Mauritia
flexuosa-dominated forests (Draper et al. 2014)
 C-dense ecosystems (850 Mg C ha-1) (Draper et al. 2014)
 Recurrent degradation over 30 years: M. flexuosa
palms cut for fruit collection (Horn et al. 2018)
 73% M. flexuosa-dominated stands degraded in
pilot area (Hergoualc’h et al. 2017)

3. Objectives
 How do N2O and CH4 fluxes vary
spatially at the microscale and
macroscale under undegraded and
degraded conditions?
 How do the fluxes vary intra-annually
and inter-annually?
 How do environmental variables
control the spatial and temporal
variation of the fluxes?
Caballero Rodriguez

4. Experiment
Highly
deg.
Medium
deg.
Intact
 Iquitos, Northern Peruvian
Amazon
 Degradation gradient
I: Intact
mD: medium degradation
hD: high degradation
 3 years (including El Niño/La Niña episodes) monthly monitoring of:
→ Soil fluxes of CH4, N2O
→Environmental variables (rainfall, temperature, moisture, soil
mineral N content and dynamic)

5. Experiment
 Disaggregation by microtopography (hummock vs. hollow), and palm
status (live vs. cut)
 Degradation impacts on forest structure & soil microtopography
considered for site-scale assessments
0
50
100
150
200
250
Intact mDeg hDeg
M.
flexuosa
(#
ha
-1
)
Cut
Live
Live M. flexuosa Cut M. flexuosa
Hummock
size reduced
by 30%

6. Soil N2O fluxes
 Microscale
b, 2
a
0
2
4
6
8
10 Intact
b, 1
a
b
a
0
2
4
6
8
10 Medium Degradation
Live hummock Live hollow
Cut hummock Cut hollow
b, 2
a a
a
0
2
4
6
8
10 High Degradation
N2O hummock > N2O hollow (except for cut palms at hDeg)
N2O mDeg < N2O Intact, N2O hDeg for hummock live palm
 Macroscale
Site-scale emissions relatively steady over years
N2O mDeg (0.5) < N2O Intact (1.3), N2O hDeg (1.1) (kg N ha-1 y-1)
=> Heterogeneous soil WFPS fluctuations along the forest complex

7. Controls of soil N2O fluxes
 Water-filled pore space (WFPS)
 Water table level (WT)
 WT and Net
nitrification

8. Soil CH4 fluxes
a, 1
b, 2
0
250
500
750
1000
1250
Intact
b, 2
a, 1
b
a
Medium Degradation
Live hummock Live hollow
Cut hummock Cut hollow b, 2
a, 1
b
a
High Degradation
 Microscale
CH4 hummock < CH4 hollow at the Intact, opposite at degraded sites
CH4 Intact < CH4 degraded for hummock, opposite for hollow
 Macroscale
Site-scale emissions increased with
precipitation
No diff. in CH4 annual emissions among
sites (161-226 kg C ha-1 y-1)

9. Controls of soil CH4 fluxes
 Water table level (WT)
 Air temperature
 Soil net nitrification rate

10. Concluding remarks
 Impacts forest degradation on GHG emissions in tropical peatlands
→ Complex to monitor: Micro- to macro-scale & specific to degradation
type
→ Degradation altered micro-scale N2O and CH4 emissions, but site-
scale emissions were homogeneous among sites
→ Impact on peat C budget and ecosystem-level losses (Vegetation C
stocks + soil GHG changes) remain to be addressed
 Climate change impacts?
Projected greatest precipitation in the study area may foster CH4
emissions which is not considered in current modeling efforts (Wang et
al 2018)

11. Thank you! Questions?