Tropical forests play a key role in the terrestrial carbon (C) cycle and thereby moderate the impact of anthropogenic CO2 emissions (Beer et al. 2010). Hence, large scale initiatives have focused on in-depth monitoring and modelling forest carbon sinks across the tropics, and revealed that intact tropical forests act as a net C sink in both the Amazon (Phillips 1998) and the Congo basin (Lewis et al. 2009) through a CO2 fertilization effect. However, recent studies have clearly shown that increasing human pressure induces a land-use change and fragmentation at high rate. As such, we now have more secondary forests than ever (FAO 2010) with an estimated 1.7 Pg C uptake yr-1 in tropical regrowth forests vs. 1.0 Pg C uptake yr-1 in intact tropical forests (Pan et al. 2011), which urges research to shift towards a better understanding of secondary forest succession trajectories.Indeed, land-use change in the tropics is dominated by increasing rates of deforestation (Hansen et al. 2013) and forest regrowth, the latter provides a low-cost mechanism that yields a high C sequestration potential with multiple benefits for biodiversity and ecosystem services (Chazdon et al. 2016). As such, secondary forests in the tropics have the potential to sequester large quantities of atmospheric CO2, although it has been shown that the magnitude of this trajectory is dependent on its coupling with other nutrient cycles (Wieder et al. 2015; Powers & Marín-Spiotta 2017 and references therein). Understanding the biogeochemical interactions in forest succession is hence paramount.
The overarching goal of this study is to evaluate and understand the role of biogeochemical cycling of phosphorus in regrowth forests in central Africa. In specific, the study targets to assess three specific hypotheses concerning this overarching goal:
The hypotheses are impactful because no study has been carried out on C-N-P coupling in regrowth forests in Africa. Additionally, it is important to note that the need for detailed empirical work on the P cycle in tropical forests worldwide is high now, given its recent implementation in land-surface models which need proper parameterization (Wang et al. 2010; Goll et al. 2017).
To be able to evaluate these hypotheses, the specific goals of the study are: