Abstract: This study is part of the activities carried out to monitor tow-impact logging operations in humid tropical forests. The sustainability of these activities is highly dependent on the scale of logging damage, and managers therefore need to carry out effective checks on the quality of forestry work. In this study, remote sensing was used to track the extension of logging operations and to assess damage, through images acquired during and after logging in each parcel. Analysis of the high-resolution images (10 m) clearly identifies logged-over clearings and some skidding tracks, allowing assessments of gaps opening up in the canopy. Several parcels were monitored in this French Guiana study. A simple diagnostic procedure was established for each parcel to assess logging intensity and identify new logging tracks and timber losses. The remote sensing toot thus helps to make more accurate assessments of logging quality and to draw relevant conclusions for the logging company. The study has demonstrated the usefulness of remote sensing to identify damage after logging. The quality of restitution of the damage was validated by means of a database on the logging terrain and through field missions. This post-logging inspection tool can now be automated for fully operational use by forest managers.

Abstract: Soil samples were collected in six South American countries in a total of 71 different 1 ha forest plots across the Amazon Basin as part of the RAINFOR project. They were analysed for total and exchangeable cations, C, N, pH with various P fractions also determined. Physical properties were also examined and an index of soil physical quality proposed. A diverse range of soils was found. For the western areas near the Andean cordillera and the southern and northern fringes, soils tend to be distributed among the lower pedogenetic levels, while the central and eastern areas of Amazonia have more intensely weathered soils. This gives rise to a large variation of soil chemical and physical properties across the Basin, with soil properties varying predictably along a gradient of pedogenic development. Nutrient pools generally increased slightly in concentration from the youngest to the intermediate aged soils after which a gradual decline was observed with the lowest values found in the most weathered soils. Soil physical properties were strongly correlated with soil fertility, with favourable physical properties occurring in highly weathered and nutrient depleted soils and with the least weathered, more fertile soils having higher incidence of limiting physical properties. Soil phosphorus concentrations varied markedly in accordance with weathering extent and appear to exert an important influence on the nitrogen cycle of Amazon forest soils.

Abstract: Accurate CO2 concentration gradient measurements are needed for the computation of advective flux terms, which are part of the full Net Ecosystem Exchange (NEE) budget equation. A typical draw back of current gradient measurement designs in advection research is the inadequate sampling of complex flow phenomena using too few observation points in space and time. To overcome this draw back, a new measurement design is presented which allows the parallel measurement of several sampling points at a high frequency. Due to the multi-analyzer nature of the design, inter-instrument bias becomes more of a concern compared to conventional setups. Therefore a statistical approach is presented which allows for accurate observations of concentration gradients, which are typically small in relation to analyzer accuracy, to be obtained. This bias correction approach applies a conditional, time dependent signal correction. The correction depends on a mixing index based on cross correlation analysis, which characterizes the degree of mixing of the atmosphere between individual sample points. The approach assumes statistical properties of probability density functions (pdf) of concentration differences between a sample point and the field average which are common to the pdf's from several sample points. The applicability of the assumptions made was tested by Large Eddy Simulation (LES) using the model PALM and could be verified for a test case of well mixed conditions. The study presents concentration time series before and after correction, measured at a 2 m height in the sub-canopy at the FLUXNET spruce forest site Waldstein-Weidenbrunnen (DE-Bay), analyzes the dependence of statistical parameters of pdf's from atmospheric parameters such as stratification, quantifies the errors and evaluates the performance of the bias correction approach. The improvements that are achieved by applying the bias correction approach are one order of magnitude larger than possible errors associated with it, which is a strong incentive to use the correction approach. In conclusion, the presented bias correction approach is well suited for – but not limited to – horizontal gradient measurements in a multi-analyzer setup, which would not have been reliable without this approach. Finally, possible future improvements of the bias correction approach are outlined and further fields of application indicated.

Abstract: Measuring in situ soil fluxes of carbon dioxide (CO 2 ), methane (CH 4 ), and nitrous oxide (N 2 O) continuously at high frequency requires appropriate technology. We tested the combination of a commercial automated soil CO 2 flux chamber system (LI-8100A) with a CH 4 and N 2 O analyzer (Picarro G2308) in a tropical rainforest for 4 months. A chamber closure time of 2 min was sufficient for a reliable estimation of CO 2 and CH 4 fluxes (100% and 98.5% of fluxes were above minimum detectable flux – MDF, respectively). This closure time was generally not suitable for a reliable estimation of the low N 2 O fluxes in this ecosystem but was sufficient for detecting rare major peak events. A closure time of 25 min was more appropriate for reliable estimation of most N 2 O fluxes (85.6% of measured fluxes are above MDF±0.002 nmolm -2 s -1 ). Our study highlights the importance of adjusted closure time for each gas. © Author(s) 2019.

Abstract: The 2015–2016 El Niño event ranks as one of the most severe on record in terms of the magnitude and extent of sea surface temperature (SST) anomalies generated in the tropical Pacific Ocean. Corresponding global impacts on the climate were expected to rival, or even surpass, those of the 1997–1998 severe El Niño event, which had SST anomalies that were similar in size. However, the 2015–2016 event failed to meet expectations for hydrologic change in many areas, including those expected to receive well above normal precipitation. To better understand how climate anomalies during an El Niño event impact soil moisture, we investigate changes in soil moisture in the humid tropics (between ±25∘) during the three most recent super El Niño events of 1982–1983, 1997–1998 and 2015–2016, using data from the Global Land Data Assimilation System (GLDAS). First, we use in situ soil moisture observations obtained from 16 sites across five continents to validate and bias-correct estimates from GLDAS (r2=0.54). Next, we apply a k-means cluster analysis to the soil moisture estimates during the El Niño mature phase, resulting in four groups of clustered data. The strongest and most consistent decreases in soil moisture occur in the Amazon basin and maritime southeastern Asia, while the most consistent increases occur over eastern Africa. In addition, we compare changes in soil moisture to both precipitation and evapotranspiration, which showed a lack of agreement in the direction of change between these variables and soil moisture most prominently in the southern Amazon basin, the Sahel and mainland southeastern Asia. Our results can be used to improve estimates of spatiotemporal differences in El Niño impacts on soil moisture in tropical hydrology and ecosystem models at multiple scales.