Adaptive forest management improves stand-level resilience of temperate forests under multiple stressors.

Forests are expected to be strongly affected by modifications in climate and disturbance regimes, threatening their ability to sustain the provision of essential services. Promoting drought-tolerant species or functionally diverse stands have recently emerged as management options to cope with global change. Our study aimed at evaluating the impact of contrasting stand-level management scenarios on the resilience of temperate forests in eastern North America and central-western Europe using the individual process-based model HETEROFOR. We simulated the evolution of eight stands over 100 years under a future extreme climate according to four management scenarios (business as usual - BAU; climate change adaptation - CC; functional diversity approach - FD; no management - NM) while facing multiple disturbances, resulting in a total of 160 simulations. We found that FD demonstrated the greatest resilience regarding transpiration and tree biomass, followed by CC and then BAU, while these three scenarios were equivalent concerning the net primary production. These results were however dependent on forest type: increasing functional diversity was a powerful option to increase the resilience of coniferous plantations whereas no clear differences between BAU and adaptive management scenarios were detected in broadleaved and mixed stands. The FD promoted a higher level of tree species diversity than any other scenario, and all scenarios of management were similar regarding the amount of harvested wood. The NM always showed the lowest resilience, demonstrating that forest management could be an important tool to mitigate adverse effects of global change. Our study highlighted that tree-level process-based models are a relevant tool to identify suitable management options for adapting forests to global change provided that model limitations are considered, and that alternative management options, particularly those based on functional diversity, are promising and should be promoted from now on.

Biomass allocation and plant morphology explain the difference in shrub species abundance in a temperate forest.

In forested ecosystems, shrubs must succeed in persisting in low-light environments, while simultaneously having the ability to rapidly expand and occupy newly created canopy openings, yet little is known about the traits that make this possible. We hypothesize that shrub species that are abundant in the understory exhibit a specific set of functional traits that define their ability to persist during unfavorable periods and to rapidly exploit newly created habitats. We tested this by comparing field-measured functional traits such as biomass allocation, leaf display, crown morphology, and leaf traits, across individual size classes and two gap-forest environments of five shrub species. We observed significant differences in traits between species, size classes, and gap-forest environments. These differences were primarily related to biomass allocation traits, followed by leaf display, crown morphology, and leaf traits. Abundant shrubs like mountain maple (Acer spicatum) and hazelnut (Corylus cornuta) invested significantly more biomass in roots, had a larger total leaf area, and displayed leaves in a more efficient manner to intercept light. The high investment in root biomass can be interpreted as shrubs exploiting the persistence and colonization strategy through resprouting. Permanent sub-canopy status likely explains the importance of efficient leaf display, wherein abundant shrubs had a large leaf area with minimal support structures.

Cross-scale integration of knowledge for predicting species ranges: a metamodeling framework.

AIM: Current interest in forecasting changes to species ranges have resulted in a multitude of approaches to species distribution models (SDMs). However, most approaches include only a small subset of the available information, and many ignore smaller-scale processes such as growth, fecundity, and dispersal. Furthermore, different approaches often produce divergent predictions with no simple method to reconcile them. Here, we present a flexible framework for integrating models at multiple scales using hierarchical Bayesian methods. LOCATION: Eastern North America (as an example). METHODS: Our framework builds a metamodel that is constrained by the results of multiple sub-models and provides probabilistic estimates of species presence. We applied our approach to a simulated dataset to demonstrate the integration of a correlative SDM with a theoretical model. In a second example, we built an integrated model combining the results of a physiological model with presence-absence data for sugar maple (Acer saccharum), an abundant tree native to eastern North America. RESULTS: For both examples, the integrated models successfully included information from all data sources and substantially improved the characterization of uncertainty. For the second example, the integrated model outperformed the source models with respect to uncertainty when modelling the present range of the species. When projecting into the future, the model provided a consensus view of two models that differed substantially in their predictions. Uncertainty was reduced where the models agreed and was greater where they diverged, providing a more realistic view of the state of knowledge than either source model. MAIN CONCLUSIONS: We conclude by discussing the potential applications of our method and its accessibility to applied ecologists. In ideal cases, our framework can be easily implemented using off-the-shelf software. The framework has wide potential for use in species distribution modelling and can drive better integration of multi-source and multi-scale data into ecological decision-making.

Sustained yield forestry in Sweden and Russia: how does it correspond to sustainable forest management policy?

This paper analyzes how sustained yield (SY) forestry is defined and implemented in Sweden and Russia, two countries with different forest-industrial regimes. We first compare definitions of SY forestry in national legislation and policies. Then we study forest management planning in two large forest management units with respect to: delivered forest products and values, how the harvest level of timber is defined, where the harvest takes place, and what treatments are used to sustain desired forest products and values. In Sweden SY forestry is maximum yield based on high-input forest management, and in Russia it is forestry based on natural regeneration with minimum investments in silviculture. We conclude that how SY forestry contributes to SFM depends on the context. Finally, we discuss the consequences of SY forestry as performed in Sweden and Russia related to its ability to support diverse forest functions, as envisioned in sustainable forest management policy.