Tropical secondary forests comprise about half of the world’s tropical forests and are important as carbon sinks and to conserve biodiversity. Their rate of recovery varies widely; however, particularly older secondary forests are difficult to date so that the recovery rate is uncertain. As a consequence, factors affecting recovery are difficult to analyse. We used aerial surveys going back to 1968 to date 12 secondary forests in the wet tropics of SW Costa Rica and evaluated the recovery of aboveground biomass, tree species richness and tree species composition in relation to nearby old-growth forests and previous land use. To confirm the validity of the space-for-time substitution, the plots were re-censused after four years. We found fast rates of aboveground biomass accumulation, especially in the first years of succession. After 20 years AGB had reached c. 164 Mg/ha equivalent to 52% of the biomass in old-growth forests in the region. Species richness increased at a slower pace and had reached c. 31% of old-growth forests after 20 years. Recovery rates differed substantially among forests, with biomass at least initially recovering faster in forests after clearcuts whereas species numbers increased faster in forests recovering from pastures. Biomass recovery was positively related to the forest cover in the vicinity and negatively to species richness, whereas species richness was related to soil parameters. The change during the four years between the censuses is broadly in line with the initial chronosequence. While the recovery of tropical secondary forests has been studied in many places, our study shows that various environmental parameters affect the speed of recovery, which is important to include in efforts to manage and restore tropical landscapes.

In the marine environment, biological processes are strongly affected by oceanic currents, particularly by eddies (vortices) formed by the hydrodynamic flow field. Employing a kinematic flow field coupled to a population dynamical model for plankton growth, we study the impact of an intermittent upwelling of nutrients on triggering harmful algal blooms (HABs). Though it is widely believed that additional nutrients boost the formation of HABs or algal blooms in general, we show that the response of the plankton to nutrient plumes depends crucially on the mesoscale hydrodynamic flow structure. In general, nutrients can either be quickly washed out from the observation area, or can be captured by the vortices in the flow. The occurrence of either scenario depends on the relation between the time scales of the vortex formation and nutrient upwelling as well as the time instants at which upwelling pulses occur and how long they last. We show that these two scenarios result in very different responses in plankton dynamics which makes it very difficult to predict whether nutrient upwelling will lead to a HAB or not. This may in part explain why observational data are sometimes inconclusive in establishing a connection between upwelling events and plankton blooms.

Isotopic composition of soil‐emitted nitrous oxide (N2O), especially the intramolecular distribution of 15N in N2O known as site preference (SP), can be used to track the two major N2O emitting soil‐processes nitrification and denitrification. Online analysis of SP in ambient air has been achieved recently, yet those approaches only allowed addressing large areas (footprints) on the basis of strong changes in surface atmospheric N2O concentrations. Here, we combined laser spectroscopy with automated static flux chambers to measure, for the first time, SP of low N2O fluxes with high sensitivity and temporal resolution and to explore its spatial variability. The measurements were then used to test the N2O isotope module SIMONE in combination with the biogeochemical model LandscapeDNDC to identify N2O source processes. End‐member mixing analysis of the data revealed denitrification as the predominant N2O source. This finding was independent of the soil water content close to the soil surface, suggesting that N2O production in the subsoil under high water‐filled pore space conditions outweighed the potential production of N2O by nitrification closer to the surface. Applying the SIMONE‐LandscapeDNDC model framework to our field site showed that the modeled SP was on average 4.2‰ lower than the observed values. This indicates that the model parameterization reflects the dominant N2O production pathways but overestimates the contribution of denitrification by 6%. Applying the stable isotope‐based model framework at other sites and comparing with other models will help identifying model shortcomings and improve our capability to support N2O mitigation from agricultural ecosystems.