Post-disturbance recovery of forest carbon in a temperate forest landscape under climate change.

Disturbances alter composition, structure, and functioning of forest ecosystems, and their legacies persist for decades to centuries. We investigated how temperate forest landscapes may recover their carbon (C) after severe wind and bark beetle disturbance, while being exposed to climate change. We used the forest landscape and disturbance model iLand to quantify (i) the recovery times of the total ecosystem C, (ii) the effect of climate change on C recovery, and (iii) the differential factors contributing to C recovery. We reconstructed a recent disturbance episode (2008-2016) based on Landsat satellite imagery, which affected 39% of the forest area in the 16,000 ha study landscape. We subsequently simulated forest recovery under a continuation of business-asusual management until 2100. Our results indicated that the recovery of the pre-disturbance C stocks (C payback time) was reached 17 years after the end of the disturbance episode. The C stocks of a theoretical undisturbed development trajectory were reached 30 years after the disturbance episode (C sequestration parity). Drier and warmer climates delayed simulated C recovery. Without the fertilizing effect of CO2, C payback times were delayed by 5-9 years, while C parity was not reached within the 21st century. Recovery was accelerated by an enhanced C uptake compared to undisturbed conditions (disturbance legacy sink effect) that persisted for 35 years after the disturbance episode. Future climate could have negative impacts on forest recovery and thus further amplify climate change through C loss from ecosystems, but the effect is strongly contingent on the magnitude and persistence of alleviating CO2 effects. Our modelling study highlights the need to consider both negative and positive effects of disturbance (i.e., C loss immediately after an event vs. enhanced C uptake of the recovering forest) in order to obtain a comprehensive understanding of disturbance effects on the forest C cycle.

Identifying the generalizable controls on insect associations of native and non-native trees.

Trees growing outside their native geographic ranges often exhibit exceptional growth and survival due in part to the lack of co-evolved natural enemies that may limit their spread and suppress population growth. While most non-native trees tend to accumulate natural enemies over time, it remains uncertain which host and insect characteristics affect these novel associations and whether novel associations follow patterns of assembly similar to those of native hosts. Here, we used a dataset of insect-host tree associations in Europe to model which native insect species are paired with which native tree species, and then tested the model on its ability to predict which native insects are paired with which non-native trees. We show that native and non-native tree species closely related to known hosts are more likely to be hosts themselves, but that native host geographic range size, insect feeding guild, and sampling effort similarly affect insect associations. Our model had a strong ability to predict which insect species utilize non-native trees as hosts, but evolutionarily isolated tree species posed the greatest challenge to the model. These results demonstrate that insect-host associations can be reliably predicted, regardless of whether insect and host trees have co-evolved, and provide a framework for predicting future pest threats using a select number of easily attainable tree and insect characteristics.