Abstract. The African Tropics are hotspots of modern-day land use change and are, at the same time, of great relevance for the cycling of carbon (C) and nutrients between plants, soils, and the atmosphere. However, the consequences of land conversion on biogeochemical cycles are still largely unknown as they are not studied in a landscape context that defines the geomorphic, geochemical, and pedological framework in which biological processes take place. Thus, the response of tropical soils to disturbance by erosion and land conversion is one of the great uncertainties in assessing the carrying capacity of tropical landscapes to grow food for future generations and in predicting greenhouse gas fluxes from soils to the atmosphere and, hence, future earth system dynamics. Here we describe version 1.0 of an open-access database created as part of the project “Tropical soil organic carbon dynamics along erosional disturbance gradients in relation to variability in soil geochemistry and land use” (TropSOC). TropSOC v1.0 (Doetterl et al., 2021, https://doi.org/10.5880/fidgeo.2021.009) contains spatially and temporally explicit data on soil, vegetation, environmental properties, and land management collected from 136 pristine tropical forest and cropland plots between 2017 and 2020 as part of monitoring and sampling campaigns in the eastern Congo Basin and the East African Rift Valley system. The results of several laboratory experiments focusing on soil microbial activity, C cycling, and C stabilization in soils complement the dataset to deliver one of the first landscape-scale datasets to study the linkages and feedbacks between geology, geomorphology, and pedogenesis as controls on biogeochemical cycles in a variety of natural and managed systems in the African Tropics. The hierarchical and interdisciplinary structure of the TropSOC database allows linking of a wide range of parameters and observations on soil and vegetation dynamics along with other supporting information that may also be measured at one or more levels of the hierarchy. TropSOC's data mark a significant contribution to improve our understanding of the fate of biogeochemical cycles in dynamic and diverse tropical African (agro-)ecosystems. TropSOC v1.0 can be accessed through the Supplement provided as part of this paper or as a separate download via the websites of the Congo Biogeochemistry Observatory and GFZ Data Services where version updates to the database will be provided as the project develops.
Abstract. The African Tropics are hotspots of modern-day land-use change and are, at the same time, of great relevance for the cycling of carbon (C) and nutrients between plants, soils and the atmosphere. However, the consequences of land conversion on biogeochemical cycles are still largely unknown as they are not studied in a landscape context that defines the geomorphic, geochemically and pedological framework in which biological processes take place. Thus, the response of tropical soils to disturbance by erosion and land conversion is one of the great uncertainties in assessing the carrying capacity of tropical landscapes to grow food for future generations and in predicting greenhouse gas fluxes (GHG) from soils to the atmosphere and, hence, future earth system dynamics. Here, we describe version 1.0 of an open access database created as part of the project “Tropical soil organic carbon dynamics along erosional disturbance gradients in relation to variability in soil geochemistry and land use” (TropSOC). TropSOC v1.0 contains spatial and temporal explicit data on soil, vegetation, environmental properties and land management collected from 136 pristine tropical forest and cropland plots between 2017 and 2020 as part of several monitoring and sampling campaigns in the Eastern Congo Basin and the East African Rift Valley System. The results of several laboratory experiments focusing on soil microbial activity, C cycling and C stabilization in soils complement the dataset to deliver one of the first landscape scale datasets to study the linkages and feedbacks between geology, geomorphology and pedogenesis as controls on biogeochemical cycles in a variety of natural and managed systems in the African Tropics. The hierarchical and interdisciplinary structure of the TropSOC database allows for linking a wide range of parameters and observations on soil and vegetation dynamics along with other supporting information that may also be measured at one or more levels of the hierarchy. TropSOC’s data marks a significant contribution to improve our understanding of the fate of biogeochemical cycles in dynamic and diverse tropical African (agro-)ecosystems. TropSOC v1.0 can be accessed through the supplementary material provided as part of this manuscript or as a separate download via the websites of the Congo Biogeochemistry observatory and the GFZ data repository where version updates to the database will be provided as the project develops.
Abstract. Information on soil properties is crucial for soil preservation, the improvement of food security, and the provision of ecosystem services. In particular, for the African continent, spatially explicit information on soils and their ability to sustain these services is still scarce. To address data gaps, infrared spectroscopy has achieved great success as a cost-effective solution to quantify soil properties in recent decades. Here, we present a mid-infrared soil spectral library (SSL) for central Africa (CSSL) that can predict key soil properties, allowing for future soil estimates with a minimal need for expensive and time-consuming wet chemistry. Currently, our CSSL contains over 1800 soil samples from 10 distinct geoclimatic regions throughout the Congo Basin and along the Albertine Rift. For the analysis, we selected six regions from the CSSL, for which we built predictive models for total carbon (TC) and total nitrogen (TN) using an existing continental SSL (African Soil Information Service, AfSIS SSL; n=1902) that does not include central African soils. Using memory-based learning (MBL), we explored three different strategies at decreasing degrees of geographic extrapolation, using models built with (1) the AfSIS SSL only, (2) AfSIS SSL combined with the five remaining central African regions, and (3) a combination of AfSIS SSL, the remaining five regions, and selected samples from the target region (spiking). For this last strategy we introduce a method for spiking MBL models. We found that when using the AfSIS SSL only to predict the six central African regions, the root mean square error of the predictions (RMSEpred) was between 3.85–8.74 and 0.40–1.66 g kg−1 for TC and TN, respectively. The ratio of performance to the interquartile distance (RPIQpred) ranged between 0.96–3.95 for TC and 0.59–2.86 for TN. While the effect of the second strategy compared to the first strategy was mixed, the third strategy, spiking with samples from the target regions, could clearly reduce the RMSEpred to 3.19–7.32 g kg−1 for TC and 0.24–0.89 g kg−1 for TN. RPIQpred values were increased to ranges of 1.43–5.48 and 1.62–4.45 for TC and TN, respectively. In general, predicted TC and TN for soils of each of the six regions were accurate; the effect of spiking and avoiding geographical extrapolation was noticeably large. We conclude that our CSSL adds valuable soil diversity that can improve predictions for the Congo Basin region compared to using the continental AfSIS SSL alone; thus, analyses of other soils in central Africa will be able to profit from a more diverse spectral feature space. Given these promising results, the library comprises an important tool to facilitate economical soil analyses and predict soil properties in an understudied yet critical region of Africa. Our SSL is openly available for application and for enlargement with more spectral and reference data to further improve soil diagnostic accuracy and cost-effectiveness.
Globally, tropical forests are assumed to be an important source of atmospheric nitrous oxide (N2O) and sink for methane (CH4). Yet, although the Congo Basin comprises the second largest tropical forest and is considered the most pristine large basin left on Earth, in situ N2O and CH4 flux measurements are scarce. Here, we provide multi-year data derived from on-ground soil flux (n = 1558) and riverine dissolved gas concentration (n = 332) measurements spanning montane, swamp, and lowland forests. Each forest type core monitoring site was sampled at least for one hydrological year between 2016 - 2020 at a frequency of 7-14 days. We estimate a terrestrial CH4 uptake (in kg CH4-C ha−1 yr−1) for montane (−4.28) and lowland forests (−3.52) and a massive CH4 release from swamp forests (non-inundated 2.68; inundated 341). All investigated forest types were a N2O source (except for inundated swamp forest) with 0.93, 1.56, 3.5, and −0.19 kg N2O-N ha−1 yr−1 for montane, lowland, non-inundated swamp, and inundated swamp forests, respectively.
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