Tropical peat forests are a globally important reservoir of carbon, but little is known about CO2 exchange on an annual basis. We measured CO2 exchange between the atmosphere and tropical peat swamp forest in Sarawak, Malaysia using the eddy covariance technique over 4 years from 2011 to 2014. The CO2 fluxes varied between seasons and years. A small carbon uptake took place during the rainy season at the beginning of 2011, while a substantial net efflux of >600 g C/m2 occurred over a 2 month period in the middle of the dry season. Conversely, the peat ecosystem was a source of carbon during both the dry and rainy seasons in subsequent years and more carbon was lost during the rainy season relative to the dry season. Our results demonstrate that the forest was a net source of CO2 to the atmosphere during every year of measurement with annual efflux ranging from 183 to 632 g C m-2 year-1 , noting that annual flux values were sensitive to gap filling methodology. This is in contrast to the typical view of tropical peat forests which must have acted as net C sinks over time scales of centuries to millennia to create the peat deposits. Path analyses revealed that the gross primary productivity (GPP) and ecosystem respiration (RE) were primarily affected by vapour pressure deficit (VPD). Results suggest that future increases in VPD could further reduce the C sink strength and result in additional net CO2 losses from this tropical peat swamp forest in the absence of plant acclimation to such changes in atmospheric dryness.
Tropical rainforests control the exchange of water and energy between the land surface and the atmosphere near the equator and thus play an important role in the global climate system. Measurements of latent (LE) and sensible heat exchange (H) have not been synthesized across global tropical rainforests to date, which can help place observations from individual tropical forests in a global context. We measured LE and H for four years in a tropical peat forest ecosystem in Sarawak, Malaysian Borneo using eddy covariance, and hypothesize that the study ecosystem will exhibit less seasonal variability in turbulent fluxes than other tropical ecosystems as soil water is not expected to be limiting in a tropical forested wetland. LE and H show little variability across seasons in the study ecosystem, with LE values on the order of 11 MJ m-2 day and H on the order of 3 MJ m-2 day-1. Annual evapotranspiration (ET) did not differ among years and averaged 1579 ± 47 mm year-1. LE exceeded characteristic values from other tropical rainforest ecosystems in the FLUXNET2015 database with the exception of GF-Guy near coastal French Guyana, which averaged 8-11 MJ m-2 day-1. The Bowen ratio (Bo) in tropical rainforests in the FLUXNET2015 database either exhibited little seasonal trend, one seasonal peak, or two peaks. Volumetric water content (VWC) and VPD explained a trivial amount of the variability of LE and Bo in some of the tropical rainforests including the study ecosystem, but were strong controls in others, suggesting differences in stomatal regulation and/or the partitioning between evaporation and transpiration. Results demonstrate important differences in the seasonal patterns in water and energy exchange across different tropical rainforest ecosystems that need to be understood to quantify how ongoing changes in tropical rainforest extent will impact the global climate system.
Wetland methane (CH4) emissions ([Formula: see text]) are important in global carbon budgets and climate change assessments. Currently, [Formula: see text] projections rely on prescribed static temperature sensitivity that varies among biogeochemical models. Meta-analyses have proposed a consistent [Formula: see text] temperature dependence across spatial scales for use in models; however, site-level studies demonstrate that [Formula: see text] are often controlled by factors beyond temperature. Here, we evaluate the relationship between [Formula: see text] and temperature using observations from the FLUXNET-CH4 database. Measurements collected across the globe show substantial seasonal hysteresis between [Formula: see text] and temperature, suggesting larger [Formula: see text] sensitivity to temperature later in the frost-free season (about 77% of site-years). Results derived from a machine-learning model and several regression models highlight the importance of representing the large spatial and temporal variability within site-years and ecosystem types. Mechanistic advancements in biogeochemical model parameterization and detailed measurements in factors modulating CH4 production are thus needed to improve global CH4 budget assessments.