Resource manipulation through experimental defoliation has legacy effects on allocation to reproductive and vegetative organs in Quercus ilex.

BACKGROUND AND AIMS: In plants, high costs of reproduction during some years can induce trade-offs in resource allocation with other functions such as growth, survival and resistance against herbivores or extreme abiotic conditions, but also with subsequent reproduction. Such trade-offs might also occur following resource shortage at particular moments of the reproductive cycle. Because plants are modular organisms, strategies for resource allocation to reproduction can also vary among hierarchical levels. Using a defoliation experiment, our aim was to test how allocation to reproduction was impacted by resource limitation. METHODS: We applied three levels of defoliation (control, moderate and intense) to branches of eight Quercus ilex trees shortly after fruit initiation and measured the effects of resource limitation induced by leaf removal on fruit development (survival, growth and germination potential) and on the production of vegetative and reproductive organs the year following defoliation. KEY RESULTS: We found that defoliation had little impact on fruit development. Fruit survival was not affected by the intense defoliation treatment, but was reduced by moderate defoliation, and this result could not be explained by an upregulation of photosynthesis. Mature fruit mass was not affected by defoliation, nor was seed germination success. However, in the following spring defoliated branches produced fewer shoots and compensated for leaf loss by overproducing leaves at the expense of flowers. Therefore, resource shortage decreased resource allocation to reproduction the following season but did not affect sex ratio. CONCLUSIONS: Our results support the idea of a regulation of resource allocation to reproduction beyond the shoot scale. Defoliation had larger legacy effects than immediate effects.

Can mixing Quercus robur and Quercus petraea with Pinus sylvestris compensate for productivity losses due to climate change?

The climate change scenarios RCP 4.5 and RCP 8.5, with a representative concentration pathway for stabilization of radiative forcing of 4.5 W m-2 and 8.5 W m-2 by 2100, respectively, predict an increase in temperature of 1-4.5° Celsius for Europe and a simultaneous shift in precipitation patterns leading to increased drought frequency and severity. The negative consequences of such changes on tree growth on dry sites or at the dry end of a tree species distribution are well-known, but rarely quantified across large gradients. In this study, the growth of Quercus robur and Quercus petraea (Q. spp.) and Pinus sylvestris in pure and mixed stands was predicted for a historical scenario and the two climate change scenarios RCP 4.5 and RCP 8.5 using the individual tree growth model PrognAus. Predictions were made along an ecological gradient ranging from current mean annual temperatures of 5.5-11.4 °C and with mean annual precipitation sums of 586-929 mm. Initial data for the simulation consisted of 23 triplets established in pure and mixed stands of Q. spp. and P. sylvestris. After doing the simulations until 2100, we fitted a linear mixed model using the predicted volume in the year 2100 as response variable to describe the general trends in the simulation results. Productivity decreased for both Q. spp. and P. sylvestris with increasing temperature, and more so, for the warmer sites of the gradient. P. sylvestris is the more productive tree species in the current climate scenario, but the competitive advantage shifts to Q. spp., which is capable to endure very high negative water potentials, for the more severe climate change scenario. The Q. spp.-P. sylvestris mixture presents an intermediate resilience to increased scenario severity. Enrichment of P. sylvestris stands by creating mixtures with Q. spp., but not the opposite, might be a right silvicultural adaptive strategy, especially at lower latitudes. Tree species mixing can only partly compensate productivity losses due to climate change. This may, however, be possible in combination with other silvicultural adaptation strategies, such as thinning and uneven-aged management.

A harmonized database of European forest simulations under climate change.

Process-based forest models combine biological, physical, and chemical process understanding to simulate forest dynamics as an emergent property of the system. As such, they are valuable tools to investigate the effects of climate change on forest ecosystems. Specifically, they allow testing of hypotheses regarding long-term ecosystem dynamics and provide means to assess the impacts of climate scenarios on future forest development. As a consequence, numerous local-scale simulation studies have been conducted over the past decades to assess the impacts of climate change on forests. These studies apply the best available models tailored to local conditions, parameterized and evaluated by local experts. However, this treasure trove of knowledge on climate change responses remains underexplored to date, as a consistent and harmonized dataset of local model simulations is missing. Here, our objectives were (i) to compile existing local simulations on forest development under climate change in Europe in a common database, (ii) to harmonize them to a common suite of output variables, and (iii) to provide a standardized vector of auxiliary environmental variables for each simulated location to aid subsequent investigations. Our dataset of European stand- and landscape-level forest simulations contains over 1.1 million simulation runs representing 135 million simulation years for more than 13,000 unique locations spread across Europe. The data were harmonized to consistently describe forest development in terms of stand structure (dominant height), composition (dominant species, admixed species), and functioning (leaf area index). Auxiliary variables provided include consistent daily climate information (temperature, precipitation, radiation, vapor pressure deficit) as well as information on local site conditions (soil depth, soil physical properties, soil water holding capacity, plant-available nitrogen). The present dataset facilitates analyses across models and locations, with the aim to better harness the valuable information contained in local simulations for large-scale policy support, and for fostering a deeper understanding of the effects of climate change on forest ecosystems in Europe.