Pedogenic Threshold in Acidity Explains Context-Dependent Tree Species Effects on Soil Carbon

Despite the general agreement that maximizing carbon storage and its persistence in forest soils are top priorities in the context of climate change mitigation, our knowledge on how to steer soil organic carbon (SOC) through forest management remains limited. For some soils, tree species selection based on litter quality has been shown a powerful measure to boost SOC stocks and stability, whereas on other locations similar efforts result in insignificant or even opposite effects. A better understanding of which mechanisms underpin such context-dependency is needed in order to focus and prioritize management efforts for carbon sequestration. Here we discuss the key role of acid buffering mechanisms in belowground ecosystem functioning and how threshold behavior in soil pH mediates tree species effects on carbon cycling. For most forests around the world, the threshold between the exchange buffer and the aluminum buffer around a pH-H2O of 4.5 is of particular relevance. When a shift between these buffer domains occurs, it triggers changes in multiple compartments in the soil, ultimately altering the way carbon is incorporated and transformed. Moreover, the impact of such a shift can be amplified by feedback loops between tree species, soil biota and cation exchange capacity (CEC). Hence, taking into account non-linearities related to acidity will allow more accurate predictions on the size and direction of the effect of litter quality changes on the way soil organic carbon is stored in forest soils. Consequently, this will allow developing more efficient, context-explicit management strategies to optimize SOC stocks and their stability.

Between virus correlations in the outcome of infection across host species: evidence of virus genotype by host species interactions

Virus host shifts are a major source of outbreaks and emerging infectious diseases, and predicting the outcome of novel host and virus interactions remains a key challenge for virus research. The evolutionary relationships between host species can explain variation in transmission rates, virulence, and virus community composition between hosts, but the potential for different viruses to interact with host species effects has yet to be established. Here, we measure correlations in viral load of four Cripavirus isolates across experimental infections of 45 Drosophilidae host species. We find positive correlations between every pair of viruses tested, suggesting that broadly susceptible host clades could act as reservoirs and donors for certain types of viruses. Additionally, we find evidence of genotype-by-genotype interactions between viruses and host species, highlighting the importance of both host and virus traits in determining the outcome of virus host shifts. More closely related viruses tended to be more strongly correlated, providing tentative evidence that virus evolutionary relatedness may be a useful proxy for determining the likelihood of novel virus emergence, which warrants further research.Impact SummaryMany new infectious diseases are caused by viruses jumping into novel host species. Estimating the probability that jumps will occur, what the characteristics of new viruses will be, and how they are likely to evolve after jumping to new host species are major challenges. To solve these challenges, we require a detailed understanding of the interactions between different viruses and hosts, or metrics that can capture some of the variation in these interactions. Previous studies have shown that the evolutionary relationships between host species can be used to predict traits of infections in different hosts, including transmission rates and the damage caused by infection. However, the potential for different viruses to influence the patterns of these host species effects has yet to be determined. Here, we use four viruses of insects in experimental infections across 45 different fruit fly host species to begin to answer this question. We find similarities in the patterns of replication and persistence between all four viruses, suggesting susceptible groups of related hosts could act as reservoirs and donors for certain types of virus. However, we also find evidence that different virus genotypes interact in different ways with some host species. Viruses that were more closely related tended to behave in similar ways, and so we suggest that virus evolutionary relatedness may prove to be a useful metric for predicting the traits of novel infections and should be explored further in future studies.

Detecting Tree Species Effects on Forest Canopy Temperatures with Thermal Remote Sensing: The Role of Spatial Resolution

Canopy temperatures are important for understanding tree physiology, ecology, and their cooling potential, which provides a valuable ecosystem service, especially in urban environments. Linkages between tree species composition in forest stands and air temperatures remain challenging to quantify, as the establishment and maintenance of onsite sensor networks is time-consuming and costly. Remotely-sensed land surface temperature (LST) observations can potentially acquire spatially distributed crown temperature data more efficiently. We analyzed how tree species modify canopy air temperature at an urban floodplain forest (Leipzig, Germany) site equipped with a detailed onsite sensor network, and explored whether mono-temporal thermal remote sensing observations (August, 2016) at different spatial scales could be used to model air temperatures at the tree crown level. Based on the sensor-network data, we found interspecific differences in summer air temperature to vary temporally and spatially, with mean differences between coldest and warmest tree species of 1 °C, and reaching maxima of up to 4 °C for the upper and lower canopy region. The detectability of species-specific differences in canopy surface temperature was found to be similarly feasible when comparing high-resolution airborne LST data to the airborne LST data aggregated to 30 m pixel size. To realize a spatial resolution of 30 m with regularly acquired data, we found the downscaling of Landsat 8 thermal data to be a valid alternative to airborne data, although detected between-species differences in surface temperature were less expressed. For the modeling of canopy air temperatures, all LST data up to the 30 m level were similarly appropriate. We thus conclude that satellite-derived LST products could be recommended for operational use to detect and monitor tree species effects on temperature regulation at the crown scale.