Trade-Offs for Climate-Smart Forestry in Europe Under Uncertain Future Climate

Forests mitigate climate change by storing carbon and reducing emissions via substitution effects of wood products. Additionally, they provide many other important ecosystem services (ESs), but are vulnerable to climate change; therefore, adaptation is necessary. Climate-smart forestry combines mitigation with adaptation, whilst facilitating the provision of many ESs. This is particularly challenging due to large uncertainties about future climate. Here, we combined ecosystem modeling with robust multi-criteria optimization to assess how the provision of various ESs (climate change mitigation, timber provision, local cooling, water availability, and biodiversity habitat) can be guaranteed under a broad range of climate futures across Europe. Our optimized portfolios contain 29% unmanaged forests, and implicate a successive conversion of 34% of coniferous to broad-leaved forests (11% vice versa). Coppices practically vanish from Southern Europe, mainly due to their high water requirement. We find the high shares of unmanaged forests necessary to keep European forests a carbon sink while broad-leaved and unmanaged forests contribute to local cooling through biogeophysical effects. Unmanaged forests also pose the largest benefit for biodiversity habitat. However, the increased shares of unmanaged and broad-leaved forests lead to reductions in harvests. This raises the question of how to meet increasing wood demands without transferring ecological impacts elsewhere or enhancing the dependence on more carbon-intensive industries. Furthermore, the mitigation potential of forests depends on assumptions about the decarbonization of other industries and is consequently crucially dependent on the emission scenario. Our findings highlight that trade-offs must be assessed when developing concrete strategies for climate-smart forestry

Model Ensembles of Ecosystem Services Fill Global Certainty and Capacity Gaps

Sustaining ecosystem services (ES) critical to human wellbeing is hindered by many practitioners lacking access to ES models (‘the capacity gap’) or knowledge of the accuracy of available models (‘the certainty gap’), especially in the world’s poorer regions. We developed ensembles of multiple models at an unprecedented global scale for five ES of high policy relevance. Ensembles were 2-14% more accurate than individual models. Ensemble accuracy was not correlated with proxies for research capacity – indicating accuracy is distributed equitably across the globe and that countries less able to research ES suffer no accuracy penalty. By making these ES ensembles and associated accuracy estimates freely available, we provide globally consistent ES information that can support policy and decision making in regions with low data availability or low capacity for implementing complex ES models. Thus, we hope to reduce the capacity and certainty gaps impeding local to global-scale movement towards ES sustainability

A continental-scale validation of ecosystem service models

Faced with environmental degradation, governments worldwide are developing policies to safeguard ecosystem services (ES). Many ES models exist to support these policies, but they are generally poorly validated, especially at large scales, which undermines their credibility. To address this gap, we describe a study of multiple models of five ES, which we validate at an unprecedented scale against 1675 data points across sub-Saharan Africa. We find that potential ES (biophysical supply of carbon and water) are reasonably well predicted by the existing models. These potential ES models can also be used as inputs to new models for realised ES (use of charcoal, firewood, grazing resources and water), by adding information on human population density. We find that increasing model complexity can improve estimates of both potential and realised ES, suggesting that developing more detailed models of ES will be beneficial. Furthermore, in 85% of cases, human population density alone was as good or a better predictor of realised ES than ES models, suggesting that it is demand, rather than supply that is predominantly determining current patterns of ES use. Our study demonstrates the feasibility of ES model validation, even in data-deficient locations such as sub-Saharan Africa. Our work also shows the clear need for more work on the demand side of ES models, and the importance of model validation in providing a stronger base to support policies which seek to achieve sustainable development in support of human well-being

B cells and monocytes from patients with active multiple sclerosis exhibit increased surface expression of both HERV-H Env and HERV-W Env, accompanied by increased seroreactivity

<p>Abstract</p> <p>Background</p> <p>The etiology of the neurogenerative disease multiple sclerosis (MS) is unknown. The leading hypotheses suggest that MS is the result of exposure of genetically susceptible individuals to certain environmental factor(s). Herpesviruses and human endogenous retroviruses (HERVs) represent potentially important factors in MS development. Herpesviruses can activate HERVs, and HERVs are activated in MS patients.</p> <p>Results</p> <p>Using flow cytometry, we have analyzed HERV-H Env and HERV-W Env epitope expression on the surface of PBMCs from MS patients with active and stable disease, and from control individuals. We have also analyzed serum antibody levels to the expressed HERV-H and HERV-W Env epitopes. We found a significantly higher expression of HERV-H and HERV-W Env epitopes on B cells and monocytes from patients with active MS compared with patients with stable MS or control individuals. Furthermore, patients with active disease had relatively higher numbers of B cells in the PBMC population, and higher antibody reactivities towards HERV-H Env and HERV-W Env epitopes. The higher antibody reactivities in sera from patients with active MS correlate with the higher levels of HERV-H Env and HERV-W Env expression on B cells and monocytes. We did not find such correlations for stable MS patients or for controls.</p> <p>Conclusion</p> <p>These findings indicate that both HERV-H Env and HERV-W Env are expressed in higher quantities on the surface of B cells and monocytes in patients with active MS, and that the expression of these proteins may be associated with exacerbation of the disease.</p

Food supply and bioenergy production within the global cropland planetary boundary

Supplying food for the anticipated global population of over 9 billion in 2050 under changing climate conditions is one of the major challenges of the 21st century. Agricultural expansion and intensification contributes to global environmental change and risks the long-term sustainability of the planet. It has been proposed that no more than 15% of the global ice-free land surface should be converted to cropland. Bioenergy production for land-based climate mitigation places additional pressure on limited land resources. Here we test normative targets of food supply and bioenergy production within the cropland planetary boundary using a global land-use model. The results suggest supplying the global population with adequate food is possible without cropland expansion exceeding the planetary boundary. Yet this requires an increase in food production, especially in developing countries, as well as a decrease in global crop yield gaps. However, under current assumptions of future food requirements, it was not possible to also produce significant amounts of first generation bioenergy without cropland expansion. These results suggest that meeting food and bioenergy demands within the planetary boundaries would need a shift away from current trends, for example, requiring major change in the demand-side of the food system or advancing biotechnologies

Modelling the response of yields and tissue C : N to changes in atmospheric CO₂ and N management in the main wheat regions of western Europe

Nitrogen (N) is a key element in terrestrial ecosystems as it influences both plant growth and plant interactions with the atmosphere. Accounting for carbon–nitrogen interactions has been found to alter future projections of the terrestrial carbon (C) cycle substantially. Dynamic vegetation models (DVMs) aim to accurately represent both natural vegetation and managed land, not only from a carbon cycle perspective but increasingly so also for a wider range of processes including crop yields. We present here the extended version of the DVM LPJ-GUESS that accounts for N limitation in crops to account for the effects of N fertilisation on yields and biogeochemical cycling. <br><br> The performance of this new implementation is evaluated against observations from N fertiliser trials and CO₂ enrichment experiments. LPJ-GUESS captures the observed response to both N and CO₂ fertilisation on wheat biomass production, tissue C to N ratios (C : N) and phenology. <br><br> To test the model's applicability for larger regions, simulations are subsequently performed that cover the wheat-dominated regions of western Europe. When compared to regional yield statistics, the inclusion of C–N dynamics in the model substantially increase the model performance compared to an earlier version of the model that does not account for these interactions. For these simulations, we also demonstrate an implementation of N fertilisation timing for areas where this information is not available. This feature is crucial when accounting for processes in managed ecosystems in large-scale models. Our results highlight the importance of accounting for C–N interactions when modelling agricultural ecosystems, and it is an important step towards accounting for the combined impacts of changes in climate, [CO₂] and land use on terrestrial biogeochemical cycles

Trade‐Offs for Climate‐Smart Forestry in Europe Under Uncertain Future Climate

Forests mitigate climate change by storing carbon and reducing emissions via substitution effects of wood products. Additionally, they provide many other important ecosystem services (ESs), but are vulnerable to climate change; therefore, adaptation is necessary. Climate‐smart forestry combines mitigation with adaptation, whilst facilitating the provision of many ESs. This is particularly challenging due to large uncertainties about future climate. Here, we combined ecosystem modeling with robust multi‐criteria optimization to assess how the provision of various ESs (climate change mitigation, timber provision, local cooling, water availability, and biodiversity habitat) can be guaranteed under a broad range of climate futures across Europe. Our optimized portfolios contain 29% unmanaged forests, and implicate a successive conversion of 34% of coniferous to broad‐leaved forests (11% vice versa). Coppices practically vanish from Southern Europe, mainly due to their high water requirement. We find the high shares of unmanaged forests necessary to keep European forests a carbon sink while broad‐leaved and unmanaged forests contribute to local cooling through biogeophysical effects. Unmanaged forests also pose the largest benefit for biodiversity habitat. However, the increased shares of unmanaged and broad‐leaved forests lead to reductions in harvests. This raises the question of how to meet increasing wood demands without transferring ecological impacts elsewhere or enhancing the dependence on more carbon‐intensive industries. Furthermore, the mitigation potential of forests depends on assumptions about the decarbonization of other industries and is consequently crucially dependent on the emission scenario. Our findings highlight that trade‐offs must be assessed when developing concrete strategies for climate‐smart forestry.Plain Language Summary: Forests help mitigate climate change by storing carbon and via avoided emissions when wood products replace more carbon‐intensive materials. At the same time, forests provide many other “ecosystem services (ESs)” to society. For example, they provide timber, habitat for various species, and they cool their surrounding regions. They are, however, also vulnerable to ongoing climate change. Forest management must consider all these aspects, which is particularly challenging considering the uncertainty about future climate. Here, we propose how this may be tackled by computing optimized forest management portfolios for Europe for a broad range of future climate pathways. Our results show that changes to forest composition are necessary. In particular, increased shares of unmanaged and broad‐leaved forests are beneficial for numerous ESs. However, these increased shares also lead to decreases in harvest rates, posing a conflict between wood supply and demand. We further show that the mitigation potential of forests strongly depends on how carbon‐intensive the replaced materials are. Consequently, should these materials become “greener” due to new technologies, the importance of wood products in terms of climate change mitigation decreases. Our study highlights that we cannot optimize every aspect, but that trade‐offs between ESs need to be made.Key Points: Strategies for climate‐smart forestry under a range of climate scenarios always lead to trade‐offs between different ecosystem services (ESs). Higher shares of unmanaged and broad‐leaved forests are beneficial for numerous ESs, but lead to decreased timber provision. The mitigation potential of forests strongly relies on substitution effects which depend on the carbon‐intensity of the alternative products.European Forest Institute (EFI) Networking Fund http://dx.doi.org/10.13039/501100013942Bayerisches Staatsministerium für Wissenschaft und Kunst, Bayerisches Netzwerk für Klimaforschung (BayKliF) http://dx.doi.org/10.13039/501100004563Swedish Research Council FormasGerman Federal Office for Agriculture and Food (BLE)https://doi.org/10.5281/zenodo.6667489https://doi.org/10.5281/zenodo.661295